importance of technology in new normal education essay

Designing the New Normal: Enable, Engage, Elevate, and Extend Student Learning

The pandemic has provided educators with unprecedented opportunities to explore blended learning and identify the practices and approaches that provide real and lasting value for students.

Students and instructors have returned to classrooms on campuses across the country, with a strong desire to rediscover some normalcy following more than a year filled with Zoom meetings and learning apart. At the same time, instructors and students have changed during the pandemic and are coming back to the classroom with new skills and different perspectives. As a result, rather than resuming business as usual, instructors should take inventory of what went well during emergency remote teaching, as well as what they missed most about in-person teaching when they were apart from their students, and begin to blend the two to design the new normal. To help instructors through this process, we have developed a framework to draw their attention to important advantages of blended learning that they should consider as they evaluate what is possible moving forward. Specifically, we have built on previous research and frameworks—such as David Merrill's e 3 approach and Liz Kolb's Triple E Framework Footnote 1 —to develop the 4Es framework (see figure 1) that asks instructors whether their blended learning strategies:

• ENABLE new types of learning activities;
• ENGAGE students in meaningful interactions with others and the course content;
• ELEVATE the learning activities by including real-world skills that benefit students beyond the classroom; and
• EXTEND the time, place, and ways that students can master learning objectives.

Do Your Blended Learning Strategies ENABLE New Types of Learning Activities?

Royce Kimmons, Charles Graham, and Richard West used the RAT framework to explain that blended learning strategies can use technology in ways that replace, amplify, or transform learning activities (see figure 2). Footnote 2

Instructors have a long history of using technology to simply replace or digitize learning activities that were previously done without technology. For example:

• In-person lectures are replaced with Zoom lectures.
• Writing an essay by hand is replaced by typing an essay.
• Writing on a chalkboard is replaced by writing on a digital whiteboard.
• Chalk on a board is replaced by pixels on a screen.
• Reading a textbook is replaced by reading an e-book.

These replacements can be a fine use of technology. Digitizing learning activities can reduce costs and improve access. Additionally, replacing a learning activity by using technology can make some learning activities more efficient than they would be without technology. For instance, an essay typed in a word processor can be revised more easily and quickly than a handwritten essay. However, simply replacing an activity will not improve learning outcomes. In a best-case scenario, students will achieve the same learning outcomes, only more quickly and/or cheaply.

To enable new types of learning that improve learning outcomes, instructors need to use blended learning strategies that move beyond replacing in-person activities with online activities to using strategies that amplify or transform learning activities from what could be accomplished without technology.

Amplifying a learning activity requires instructors to introduce technology in ways that enable incremental improvements, even as the core of the activity remains largely unchanged. For instance, when they read students' essays, instructors may find that many of their students have met the target learning outcomes. As a result, the instructors may choose to amplify the essay-writing process by having students work in a shared document that enables better collaborative opportunities, peer reviews, instructor feedback, and editing. Students can also include multimedia elements to enhance what is written in the essay. Or instructors might use technology to allow students to publish and share their essays in authentic ways. Instructors might also use technology to improve pre-writing activities by engaging students in an online discussion activity to brainstorm and formulate ideas for their essays. What's important to recognize is that although the core activity—writing an essay—remains the same, technology enables incremental improvements, some of which could impact learning outcomes.

Transforming a learning activity is different from amplifying because the goal isn't to improve the activity but to use blended learning strategies in ways that introduce a new learning activity that wouldn't be possible without technology. For instance, rather than making improvements to the essay, instructors could choose to transform the learning activity by tasking students with writing a script, editing a video, and "premiering" their videos to those in the course and others who are invited to participate.

Do Your Blended Learning Strategies ENGAGE Students in Meaningful Interactions with Others and the Course Content?

"Engagement" is a term that is used frequently to mean a lot of different things. A 2020 review of research identified three dimensions of engagement: Footnote 3

• Behavioral: the physical behaviors required to complete the learning activity
• Emotional: the positive emotional energy associated with the learning activity
• Cognitive: the mental energy that a student exerts toward the completion of the learning activity

Instructors often refer to these three dimensions of engagement when they talk about engaging students' hands, hearts, and heads (see figure 3).

Of the three dimensions of engagement, behavioral engagement is the easiest to observe and categorize. Specifically, Kimmons, Graham, and West used the PIC framework to identify three types of behavioral engagement: passive, interactive, and creative (see figure 4). Footnote 4

Passive learning examples include students watching a video, listening to a podcast, and attending a lecture. In some ways, these passive learning tasks represent a lack of engagement because they don't require or even allow students to make meaningful contributions to the learning activity.

Interactive activities are dynamic and require students to actively participate. Interactive activities include tasks in which students interact with online content and tools. Interactive activities can also include opportunities for students to communicate with others such as the instructor, other students, and those outside the classroom (see figure 5).

Creative activities go beyond participation to actually creating something original such as a blog post, edited video, or website. Table 1 identifies some additional examples of online passive, interactive, and creative activities.

Table 1. Examples of Passive, Interactive, and Creative Activities

It's important to note that each type of behavioral engagement is important at different stages of the learning process. For instance, students may passively listen to a short lecture or watch a video before interacting with their peers regarding their thoughts about what they learned during the passive activity. Similarly, if students are tasked with creating a video essay, they will likely start with passive activities to develop a background understanding of the topic or to learn how to use the video-editing program. Students could then interact with their peers to collaboratively create the video. Instructors can also consider when and where passive learning activities occur. For example, sometimes a flipped classroom requires having a passive video-watching experience online to make time and space for an interactive/creative learning experience in person.

An important part of evaluating your blended teaching is to see the value of passive learning activities while also understanding that these types of activities are limited in terms of deepening students' learning. Passive activities such as watching a video or reading an article alone do not require students to demonstrate their comprehension of content or encourage higher levels of cognitive engagement, such as applying, evaluating, or creating. Because too much time spent in passive learning activities will limit students' engagement, instructors should be sure to leave ample time for interactive and creative activities.

Kimmons, Graham, and West combined the PIC and RAT frameworks to form the PICRAT framework and matrix, which allow instructors to chart how technology is being used in their blended learning strategies. Footnote 5 Figure 6 is an adaptation of Kimmons, Graham, and West's original matrix. The matrix is a helpful tool for instructors to consider what the technology adds to the activity and how students are interacting with that technology. Ask yourself the following questions:

• Is the technology being used to increase student engagement by making learning activities more interactive and/or creative?
• Is the technology being used simply to replace activities or to amplify and transform them?

When planning new blended or online activities, we recommend starting by focusing on the learning objective(s) and then pulling out a piece of paper or pulling up a word processing document and filling out the PICRAT matrix (see figure 7) with various ways that technology could be used to teach the learning objective(s).

Moving up and across the matrix will likely improve the learning activity by leveraging technology to make the experience more interactive or engaging and introducing new ways of learning, but note that the PICRAT matrix doesn't actually measure the quality of the learning activity. Instructors could transform a learning activity by having students create something that wouldn't be possible without technology, but that change might not actually improve students' learning or experience. In fact, students' learning can be transformed for the worse. For instance, using the example shared above, an instructor could transform an essay writing activity so that students create an edited video instead. Although this change may be positive for many students, some students might detest making an edited video and refuse to participate. Similarly, an instructor might transform a passive learning activity into a creative learning activity that isn't as aligned to the learning outcomes. As a result, when amplifying or transforming a learning activity to increase students' behavioral engagement, consider the other two dimensions of engagement—emotional engagement and cognitive engagement. Students will perceive the activity as "busy work" if instructors only engage their hands but fail to also engage their hearts and minds (see figure 8).

Do Your Blended Learning Strategies ELEVATE the Learning Activities to Include Real-World Skills That Benefit Students Beyond the Classroom?

In addition to creating learning activities aligned with the course learning objectives, blended learning strategies can elevate students' learning to also include real-world skills that benefit students beyond the classroom. For example, the Partnership for 21st Century Learning stresses the need for students to develop the 4Cs—communication, collaboration, critical thinking, and creativity skills. Footnote 6 While widely referenced and important, the 4Cs model takes a somewhat narrow view of the skills that students need to succeed beyond the classroom. For Ontario's education agenda, Michael Fullan expanded on the 4Cs to include character education and citizenship. Footnote 7 Social-emotional learning is also critical for human development. These skills are best developed in a social learning environment. Of course, students are unable to develop communication, collaboration, and citizenship skills in isolation. Even critical thinking and creativity skills are best developed when working with others. This reality provides more support for balancing passive activities with interactive and creative activities while urging instructors to elevate their instruction.

Learning activities are also best elevated when they are situated in authentic tasks and projects. Three levels of authenticity should be considered when choosing the problems students will be working on and the stakeholders that students will be working with (see figure 9):

• Unrealistic: These scenarios and problems can be out of this world—literally! Stakeholders and problems can be science fiction and include anything from time traveling to establishing a colony on Mars. They are intended to make the unit more exciting and emotionally engaging while still requiring students to demonstrate important knowledge and real-world skills.
• Realistic: These are scenarios and problems that feel like they are real but aren't. Real people can even serve as stakeholders, but they are just acting. For example, students might simulate creating a new business by coming up with a new product and working in groups to come up with the name of the product, a business plan, and a marketing plan. It is completely realistic, but they won't be really starting a new business.
• Real: This is the gold standard because you have real people who are genuinely interested in students' work and will benefit from it. These stakeholders can be of any age and in or out of the institution. For example, pre-service instructors in a course on teaching with technology may collaborate to develop a workshop on blended teaching for a local school district. Art students could also curate an actual art gallery showcasing works from local artists.

Authentic assessments are often renewable rather than disposable. As David Wiley explained, "A 'renewable assessment' differs in that the student's work won't be discarded at the end of the process, but will instead add value to the world in some way." Footnote 8 Consider the target audience of most assessments—for whom are students completing assessments? Themselves? Their community? The instructor? Often assessments are completed for an audience of one, the instructor. The instructor then evaluates the assessment, provides the student with some feedback, returns the assessment to the student, and hopes that the feedback enriches the student's learning before the assessment is thrown in the physical or digital trash can. David Wiley referred to these assessments as disposable assessments . They are meant to be used and then discarded without retaining any real-world value.

A movement toward assessments that can exist in a world larger than the four walls of a singular classroom can make learning more authentic and elevate what students learn and do beyond the content-based curriculum and contexts. For example, a community college instructor who worked with one of the authors found that having her students write an openly licensed textbook that would be shared with other students instead of traditional essays prompted them to submit higher quality work than they previously had. Students want to know that their work matters and is destined for more than the nearest trash can (see table 2 and the sidebar "Additional Resources about Assessments").

Table 2. Examples of Renewable and Disposable Assessments

Additional Resources about Assessments

Christina Hendricks, "Renewable Assignments: Student Work Adding Value to the World," Flexible Learning , University of British Columbia, October 29, 2015.

Christina Hendricks, "Non-Disposable Assignments in Intro to Philosophy," You're the Teacher , University of British Columbia, August 18, 2015.

"From Consumer to Creator: Students as Producers of Content," Flexible Learning , University of British Columbia, February 18, 2015.

David Wiley, "What Is Open Pedagogy," Improving Learning , October 21, 2013.

Do Your Blended Learning Strategies EXTEND the Time, Place, and Ways That Students Can Master Learning Objectives?

Another way that blended learning strategies can improve learning activities is by extending the time, location, and ways that students can complete them. Attempting to extend students' learning time and location is nothing new. For instance, students have long had flexibility in the time and location that they completed assignments. However, too often students are tasked with completing assignments outside class without adequate support, resulting in frustration and stress.

Using technology, instructors can not only provide students with more sensory-rich learning materials, but, within a learning management system (LMS), they can also provide digital scaffolding and direction to successfully complete learning activities using those materials. For instance, it is relatively easy for instructors to create short instructional videos that can help students learn new concepts or complete learning tasks. Kareem Farah explained that creating instructional videos allowed him to "clone" himself so students could receive his help the moment they needed it, not when he was presently available to help them. Footnote 9 Once instructors feel comfortable making quick videos, they can use them to provide targeted support anytime students find something confusing or difficult. This allows instructors to tailor lessons to specific students or course sections.

Instructors can also extend the ways in which students complete learning activities. For instance, instructors might provide multiple learning paths for students to choose from. Creating multiple activities that all lead toward mastery of learning objectives allows students choice in the learning path—hopefully with choices that will motivate them and inspire them to do their best work. Once learning has been extended, instructors can also provide students with opportunities to form their own learning path and/or set their own learning goals. The taxonomy of learner agency presents a scaffold for moving students from a "one size fits all" learning approach to an instructional approach that provides learners with guided choices for their own learning. Footnote 10 These choices could include setting performance or learning behavior goals related to learning objectives, choosing how to demonstrate learning and understanding, or choosing specific resources to use or topics to study within a given learning objective. At the highest levels of extending learner autonomy, learners may even create their own learning outcomes, assessments, and activities related to the goals of a course.

Combining in-person and online instruction doesn't mean that the blended learning will be high quality—or even good. As you begin to blend your students' learning, you will likely find that some lessons or even entire instructional units don't work as well as expected. The opposite will also be true, however, and you will find that some blended lessons and modules go incredibly well. It's important to carefully evaluate what works and what needs to be improved or even replaced. A J-curve should be expected anytime instructors try something new. Footnote 11 The 4Es framework can help you recognize quality blended teaching and learning. Specifically, as you plan new blended instructional units or evaluate previous blended instruction, ask if your instructional unit would or did:

• ENABLE new types of learning activities?
• ENGAGE students in meaningful interactions with others and the course content?
• ELEVATE the learning activities by including real-world skills that benefit students beyond the classroom?
• EXTEND the time, place, and ways that students can master learning objectives?
• M. David Merrill, "Finding e³ (effective, efficient, and engaging) Instruction," Educational Technology 49, no. 3 (May–June 2009): 15–26; Liz Kolb, Triple E Framework . Jump back to footnote 1 in the text. ↩
• Royce Kimmons, Charles R. Graham, and Richard E. West, "The PICRAT Model for Technology Integration in Teacher Preparation," Contemporary Issues in Technology and Teacher Education 20, no. 1 (2020). Jump back to footnote 2 in the text. ↩
• Jered Borup, Charles R. Graham, Richard E. West, Leanna Archambault, and Kristian J. Spring, "Academic Communities of Engagement: An Expansive Lens for Examining Support Structures in Blended and Online Learning," Educational Technology Research and Development 68 (February 14, 2020): 807–32. Jump back to footnote 3 in the text. ↩
• Kimmons, Graham, and West, "The PICRAT Model." Jump back to footnote 4 in the text. ↩
• Ibid. Jump back to footnote 5 in the text. ↩
• See "P21 Framework Definitions." Jump back to footnote 6 in the text. ↩
• Michael Fullan, Great to Excellent: Launching the Next Stage of Ontario's Education Agenda , Ontario Ministry of Education, 2013. Jump back to footnote 7 in the text. ↩
• David Wiley, "Toward Renewable Assessments," Improving Learning , July 7, 2016. Jump back to footnote 8 in the text. ↩
• Kareem Farah, "Blended Learning Built on Teacher Expertise," Edutopia , May 9, 2019. Jump back to footnote 9 in the text. ↩
• Charles R. Graham , Jered Borup, Michelle A. Jensen, Karen T. Arnesen, and Cecil R. Short, "K–12 Blended Teaching Competencies," (Provo, UT: EdTechBooks.org, 2021). Jump back to footnote 10 in the text. ↩
• Charles R. Graham, Jered Borup, Cecil R. Short, and Leanna Archambault, K–12 Blended Teaching: A Guide to Personalized Learning and Online Integration (Provo, UT: EdTechBooks.org, 2019). See, specifically, section 6.5 of "Blended Design in Practice." Jump back to footnote 11 in the text. ↩

Jered Borup is an Associate Professor in the Division of Learning Technologies at George Mason University.

Charles R. Graham is a Professor in the Department of Instructional Psychology and Technology at Brigham Young University.

Cecil Short is an Assistant Professor of Practice of Blended and Personalized Learning in the Department of Curriculum and Instruction at Texas Tech University.

Joan Kang Shin is an Associate Professor in the Division of Advanced Professional Teacher Development and International Education at George Mason University.

© 2022 Jered Borup, Charles R. Graham, Cecil Short, and Joan Kang Shin. The text of this work is licensed under a Creative Commons BY-SA 4.0 International License.

Information

• Author Services

Initiatives

You are accessing a machine-readable page. In order to be human-readable, please install an RSS reader.

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess .

Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.

Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Original Submission Date Received: .

• Active Journals
• Find a Journal
• Proceedings Series
• For Authors
• For Reviewers
• For Editors
• For Librarians
• For Publishers
• For Societies
• For Conference Organizers
• Open Access Policy
• Institutional Open Access Program
• Special Issues Guidelines
• Editorial Process
• Research and Publication Ethics
• Article Processing Charges
• Testimonials
• Preprints.org
• SciProfiles
• Encyclopedia

Article Menu

• Subscribe SciFeed
• Recommended Articles
• Author Biographies
• Google Scholar
• on Google Scholar
• Table of Contents

Find support for a specific problem in the support section of our website.

Please let us know what you think of our products and services.

Visit our dedicated information section to learn more about MDPI.

JSmol Viewer

Navigating the new normal: adapting online and distance learning in the post-pandemic era.

1. Introduction

1.1. background, 1.2. purpose of the review.

• Highlighting the multifaceted impact of the pandemic on education, including the disruptions caused by school closures and the subsequent shift to remote learning [ 1 ].
• Exploring innovative approaches and strategies employed by educators to ensure effective online teaching and learning experiences [ 2 , 4 ].
• Examining the role of technological solutions and platforms in facilitating remote education and their effectiveness in supporting teaching and learning processes [ 4 ].
• Investigating strategies for promoting student engagement and participation in virtual classrooms, considering the unique challenges and opportunities presented by online and distance learning [ 2 , 3 ].
• Evaluating the various assessment and evaluation methods employed in online education, considering their validity, reliability, and alignment with learning outcomes [ 4 ].
• Discussing the importance of supporting student well-being and academic success in the digital environment, addressing the social and emotional aspects of remote learning [ 3 ].
• Examining the professional development opportunities and resources available for educators to enhance their skills in online teaching and adapt to the changing educational landscape [ 4 ].
• Addressing equity and accessibility considerations in online and distance learning, developing strategies to ensure equitable opportunities for all learners and mitigate the digital divide [ 1 , 2 ].
• Identifying key lessons learned and best practices from the experiences of educators and students during the pandemic, providing insights for future educational practices [ 1 , 4 ].
• Discussing the potential for educational innovation and transformations in teaching and learning practices in the post-pandemic era, considering the lessons learned from the rapid transition to online and distance learning [ 4 ].

1.3. Significance of the Study

• To provide a comprehensive understanding of the impact of the pandemic on education. UNESCO (2020) reported that the widespread school closures caused by the pandemic disrupted traditional education practices and posed significant challenges for students, educators, and families [ 1 ]. As such, understanding the multifaceted impact of the pandemic is crucial for effective decision making and policy development.
• To highlight innovative approaches to online teaching and learning. Hodges et al. [ 4 ] emphasized the importance of instructional design principles and the use of educational technology tools in facilitating effective online education [ 4 ] by examining strategies employed by educators during the pandemic. This review paper aims to identify successful practices that can be applied in future online and blended learning environments.
• To explore the role of technology in supporting remote education. The rapid transition to online and distance learning has required the use of various technological solutions and platforms. With reference to this subject, Hodges et al. (2020) discussed the difference between emergency remote teaching and online learning, highlighting the importance of leveraging technology to create engaging and interactive virtual classrooms [ 4 ].
• To address equity and accessibility considerations. The pandemic has exacerbated existing inequities in access to education and technology. On this line, UNESCO (2020) emphasized the need to address equity issues and bridge the digital divide to ensure equitable opportunities for all learners. This review paper examines strategies and interventions aimed at promoting equitable access to online and distance learning.
• To provide insights for future educational practices by analyzing experiences, challenges, and successes encountered during the transition to online and distance learning. This review paper aims to provide valuable insights for educators, policymakers, and researchers. So, lessons learned from the pandemic can inform the development of effective educational policies, teacher training programs, and support systems for students.

1.4. Methodology of Search

2. impact of the covid-19 pandemic on education, 3. transitioning from traditional classrooms to online and distance learning, 4. challenges faced by educators during the lockdown period, 5. strategies for effective online teaching and learning, 6. technological solutions and platforms for remote education, 7. promoting student engagement and participation in the virtual classroom, 8. assessments and evaluation methods in online education, 9. supporting student well-being and academic success in the digital environment, 10. professional development for educators in online teaching, 11. addressing equity and accessibility in online and distance learning, 12. lessons learned and best practices for future educational practices, 13. innovations and transformations in education post-pandemic, 14. policy implications and recommendations for effective online education, 15. ethical considerations in online and distance learning, 16. innovations and practical applications in post-pandemic educational strategies.

• Impact Analysis Tools: Develop analytical tools to quantify the educational disruptions caused by the pandemic, focusing on metrics like attendance, engagement, and performance shifts due to remote learning.
• Online Pedagogy Workshops: Create workshops for educators to share and learn innovative online teaching strategies, focusing on interactivity, student-centered learning, and curriculum adaptation for virtual environments.
• Tech-Integration Frameworks: Develop frameworks for integrating and evaluating the effectiveness of various technological solutions in remote education, including LMS, interactive tools, and AI-based learning supports.
• Engagement-Boosting Platforms: Create platforms or tools that specifically target student engagement in virtual classrooms, incorporating gamification, interactive content, and real-time feedback mechanisms.
• Assessment Methodology Guides: Develop guidelines or toolkits for educators to design and implement valid and reliable online assessments aligned with learning outcomes.
• Well-being Monitoring Systems: Implement systems to monitor and support student well-being in digital learning environments, incorporating mental health resources and social-emotional learning components.
• Professional Development Portals: Develop online portals offering continuous professional development opportunities for educators, focusing on upskilling in digital pedagogy, content creation, and adaptive learning technologies.
• Equity and Accessibility Strategies: Formulate and implement strategies to ensure equitable access to online and distance learning, addressing the digital divide through resource distribution, adaptive technologies, and inclusive curriculum design.
• Best Practices Repository: Create a repository of best practices and lessons learned from the pandemic’s educational challenges, serving as a resource for future educational planning and crisis management.
• Post-Pandemic Educational Innovation Labs: Establish innovation labs to explore and pilot new teaching and learning practices in the post-pandemic era, emphasizing the integration of traditional and digital pedagogies.

17. Conclusions: Navigating the Path Forward in Online Education

Author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

• Reuge, N.; Jenkins, R.; Brossard, M.; Soobrayan, B.; Mizunoya, S.; Ackers, J.; Jones, L.; Taulo, W.G. Education response to COVID 19 pandemic, a special issue proposed by UNICEF: Editorial review. Int. J. Educ. Dev. 2021 , 87 , 102485. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Wang, C.; Cheng, Z.; Yue, X.-G.; McAleer, M. Risk Management of COVID-19 by Universities in China. J. Risk Financ. Manag. 2020 , 13 , 36. [ Google Scholar ] [ CrossRef ]
• Bao, W. COVID-19 and Online Teaching in Higher Education: A Case Study of Peking University. Hum. Behav. Emerg. Technol. 2020 , 2 , 113–115. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Hodges, C.B.; Moore, S.; Lockee, B.B.; Trust, T.; Bond, M.A. The Difference between Emergency Remote Teaching and Online Learning ; Educause: Boulder, CO, USA, 2020. [ Google Scholar ]
• Bashir, A.; Bashir, S.; Rana, K.; Lambert, P.; Vernallis, A. Post-COVID-19 Adaptations; the Shifts towards Online Learning, Hybrid Course Delivery and the Implications for Biosciences Courses in the Higher Education Setting. Front. Educ. 2021 , 6 , 310. [ Google Scholar ] [ CrossRef ]
• Akpa, V.O.; Akinosi, J.R.; Nwankwere, I.A.; Makinde, G.O.; Ajike, E.O. Strategic Innovation, Digital Dexterity and Service Quality of Selected Quoted Deposit Money Banks in Nigeria. Eur. J. Bus. Innov. Res. 2022 , 10 , 15–35. [ Google Scholar ]
• Loades, M.E.; Chatburn, E.; Higson-Sweeney, N.; Reynolds, S.; Shafran, R.; Brigden, A.; Linney, C.; McManus, M.N.; Borwick, C.; Crawley, E. Rapid Systematic Review: The Impact of Social Isolation and Loneliness on the Mental Health of Children and Adolescents in the Context of COVID-19. J. Am. Acad. Child Adolesc. Psychiatry 2020 , 59 , 1218–1239.e3. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Van Lancker, W.; Parolin, Z. COVID-19, School Closures, and Child Poverty: A Social Crisis in the Making. Lancet Public Health 2020 , 5 , e243–e244. [ Google Scholar ] [ CrossRef ]
• Brooks, S.K.; Webster, R.K.; Smith, L.E.; Woodland, L.; Wessely, S.; Greenberg, N.; Rubin, G.J. The Psychological Impact of Quarantine and How to Reduce It: Rapid Review of the Evidence. Lancet 2020 , 395 , 912–920. [ Google Scholar ] [ CrossRef ]
• Padmanabhanunni, A.; Pretorius, T.B. Teacher Burnout in the Time of COVID-19: Antecedents and Psychological Consequences. Int. J. Environ. Res. Public Health 2023 , 20 , 4204. [ Google Scholar ] [ CrossRef ]
• Al Lily, A.E.; Ismail, A.F.; Abunasser, F.M.; Alhajhoj Alqahtani, R.H. Distance Education as a Response to Pandemics: Coronavirus and Arab Culture. Technol. Soc. 2020 , 63 , 101317. [ Google Scholar ] [ CrossRef ]
• Means, B.; Toyama, Y.; Murphy, R.; Bakia, M.; Jones, K. Evaluation of Evidence-Based Practices in Online Learning: A Meta-Analysis and Review of Online Learning Studies ; Centre for Learning Technology: Hong Kong, China, 2009. [ Google Scholar ]
• Picciano, A.G. Theories and Frameworks for Online Education: Seeking an Integrated Model. In A Guide to Administering Distance Learning ; Brill: Leiden, The Netherlands, 2021; pp. 79–103. [ Google Scholar ]
• Burgstahler, S.E.; Cory, R.C. Universal Design in Higher Education: From Principles to Practice ; Harvard Education Press: Cambridge, MA, USA, 2010. [ Google Scholar ]
• Nicol, D.J.; Macfarlane-Dick, D. Formative Assessment and Self-regulated Learning: A Model and Seven Principles of Good Feedback Practice. Stud. High. Educ. 2006 , 31 , 199–218. [ Google Scholar ] [ CrossRef ]
• Stodel, E.J.; Thompson, T.L.; MacDonald, C.J. Learners’ Perspectives on What Is Missing from Online Learning: Interpretations through the Community of Inquiry Framework. Int. Rev. Res. Open Distrib. Learn. 2006 , 7 , 1–24. [ Google Scholar ] [ CrossRef ]
• Richardson, J.C.; Maeda, Y.; Lv, J.; Caskurlu, S. Social Presence in Relation to Students’ Satisfaction and Learning in the Online Environment: A Meta-Analysis. Comput. Hum. Behav. 2017 , 71 , 402–417. [ Google Scholar ] [ CrossRef ]
• Mayer, R.E. Using Multimedia for E-learning. J. Comput. Assist. Learn. 2017 , 33 , 403–423. [ Google Scholar ] [ CrossRef ]
• Swan, K. Building Learning Communities in Online Courses: The Importance of Interaction. Educ. Commun. Inf. 2002 , 2 , 23–49. [ Google Scholar ] [ CrossRef ]
• Sato, S.N.; Condes Moreno, E.; Villanueva, A.R.; Orquera Miranda, P.; Chiarella, P.; Bermudez, G.; Aguilera, J.F.T.; Clemente-Suárez, V.J. Psychological Impacts of Teaching Models on Ibero-American Educators during COVID-19. Behav. Sci. 2023 , 13 , 957. [ Google Scholar ] [ CrossRef ]
• Dennen, V.P.; Burner, K.J. The Cognitive Apprenticeship Model in Educational Practice. In Handbook of Research on Educational Communications and Technology ; Routledge: Oxfordshire, UK, 2008; pp. 425–439. [ Google Scholar ]
• Alturki, U.; Aldraiweesh, A. Application of Learning Management System (LMS) during the COVID-19 Pandemic: A Sustainable Acceptance Model of the Expansion Technology Approach. Sustainability 2021 , 13 , 10991. [ Google Scholar ] [ CrossRef ]
• Sun, A.; Chen, X. Online Education and Its Effective Practice: A Research Review. J. Inf. Technol. Educ. 2016 , 15 , 157–190. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• AIKTC; CITEL. Three Days National Conference on Innovative Teaching & Exuberant Learning (NCiTeL 2021) ; AIKTC: Navi Mumbai, India, 2021. [ Google Scholar ]
• Coggi, C. Innovare La Didattica e La Valutazione in Università: Il Progetto IRIDI per La Formazione Dei Docenti. In Innovare la Didattica e la Valutazione in Università ; Franco Angeli Edizioni: Milano, Italy, 2019; pp. 1–361. [ Google Scholar ]
• Hawa, D.M.; Ghoniem, E.; Saad, A.M. Integrating Problem-Based Learning Into Blended Learning To Enhance Students’ Programming Skills. J. Posit. Sch. Psychol. 2022 , 6 , 4479–4497. [ Google Scholar ]
• Lee, E.; Hannafin, M.J. A Design Framework for Enhancing Engagement in Student-Centered Learning: Own It, Learn It, and Share It. Educ. Technol. Res. Dev. 2016 , 64 , 707–734. [ Google Scholar ] [ CrossRef ]
• Mayer, R.E. How Multimedia Can Improve Learning and Instruction. In The Cambridge Handbook of Cognition and Education ; Cambridge University Press: Cambridge, UK, 2019. [ Google Scholar ]
• Dillenbourg, P.; Järvelä, S.; Fischer, F. The Evolution of Research on Computer-Supported Collaborative Learning BT-Technology-Enhanced Learning: Principles and Products ; Balacheff, N., Ludvigsen, S., de Jong, T., Lazonder, A., Barnes, S., Eds.; Springer: Dordrecht, The Netherlands, 2009. [ Google Scholar ]
• McNair, D.E.; Palloff, R.M.; Pratt, K. Lessons from the Virtual Classroom: The Realities of Online Teaching ; SAGE Publications: Los Angeles, CA, USA, 2015. [ Google Scholar ]
• Baran, E.; Correia, A.-P. A Professional Development Framework for Online Teaching. TechTrends 2014 , 58 , 95–101. [ Google Scholar ] [ CrossRef ]
• Gikandi, J.W.; Morrow, D.; Davis, N.E. Online Formative Assessment in Higher Education: A Review of the Literature. Comput. Educ. 2011 , 57 , 2333–2351. [ Google Scholar ] [ CrossRef ]
• Conole, G. Designing for Learning in an Open World ; Springer Science & Business Media: Berlin/Heidelberg, Germany, 2012; Volume 4. [ Google Scholar ]
• Black, P.; Wiliam, D. The Formative Purpose: Assessment Must First Promote Learning. Yearb. Natl. Soc. Study Educ. 2004 , 103 , 20–50. [ Google Scholar ] [ CrossRef ]
• Ruiz-Primo, M.A.; Briggs, D.; Iverson, H.; Talbot, R.; Shepard, L.A. Impact of Undergraduate Science Course Innovations on Learning. Science 2011 , 331 , 1269–1270. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Ismail, S.M.; Rahul, D.R.; Patra, I.; Rezvani, E. Formative vs. Summative Assessment: Impacts on Academic Motivation, Attitude toward Learning, Test Anxiety, and Self-Regulation Skill. Lang. Test. Asia 2022 , 12 , 40. [ Google Scholar ] [ CrossRef ]
• Nitko, A.J. Educational Assessment of Students ; ERIC: Washington, DC, USA, 1996. [ Google Scholar ]
• Cherner, T.; Halpin, P. Determining the Educational Value of Virtual Reality Apps Using Content Analysis. J. Interact. Learn. Res. 2021 , 32 , 245–280. [ Google Scholar ]
• Pirker, B.; Smolka, J. International Law and Linguistics: Pieces of an Interdisciplinary Puzzle. J. Int. Disput. Settl. 2020 , 11 , 501–521. [ Google Scholar ] [ CrossRef ]
• Panda, S. Analyzing Effectiveness of Learning Management System in Present Scenario: Conceptual Background and Practical Implementation. Int. J. Innov. Res. Adv. Stud. 2020 , 7 , 40–50. [ Google Scholar ]
• Coghlan, S.; Miller, T.; Paterson, J. Good Proctor or “Big Brother”? Ethics of Online Exam Supervision Technologies. Philos. Technol. 2021 , 34 , 1581–1606. [ Google Scholar ] [ CrossRef ]
• Shute, V.J.; Rahimi, S. Review of Computer-based Assessment for Learning in Elementary and Secondary Education. J. Comput. Assist. Learn. 2017 , 33 , 1–19. [ Google Scholar ] [ CrossRef ]
• Landers, R.N.; Callan, R.C. Casual Social Games as Serious Games: The Psychology of Gamification in Undergraduate Education and Employee Training. In Serious Games and Edutainment Applications ; Springer: London, UK, 2011; pp. 399–423. [ Google Scholar ]
• Hattie, J.; Timperley, H. The Power of Feedback. Rev. Educ. Res. 2007 , 77 , 81–112. [ Google Scholar ] [ CrossRef ]
• Schraw, G.; Crippen, K.J.; Hartley, K. Promoting Self-Regulation in Science Education: Metacognition as Part of a Broader Perspective on Learning. Res. Sci. Educ. 2006 , 36 , 111–139. [ Google Scholar ] [ CrossRef ]
• Przybylski, A.K.; Murayama, K.; DeHaan, C.R.; Gladwell, V. Motivational, Emotional, and Behavioral Correlates of Fear of Missing Out. Comput. Hum. Behav. 2013 , 29 , 1841–1848. [ Google Scholar ] [ CrossRef ]
• Bereznowski, P.; Atroszko, P.A.; Konarski, R. Work Addiction, Work Engagement, Job Burnout, and Perceived Stress: A Network Analysis. Front. Psychol. 2023 , 14 , 1130069. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Brock, A. Mitigating Burnout and Promoting Professional Well-Being in Advisors. In Academic Advising Administration ; Routledge: Oxfordshire, UK, 2023; pp. 332–344. [ Google Scholar ]
• Rovai, A.P.; Barnum, K.T. On-Line Course Effectiveness: An Analysis of Student Interactions and Perceptions of Learning. Int. J. E-Learn. Distance Educ. Int. Du E-Learn. La Form. Distance 2003 , 18 , 57–73. [ Google Scholar ]
• Topping, K.J. Trends in Peer Learning. Educ. Psychol. 2005 , 25 , 631–645. [ Google Scholar ] [ CrossRef ]
• Shea, P.; Li, C.S.; Pickett, A. A Study of Teaching Presence and Student Sense of Learning Community in Fully Online and Web-Enhanced College Courses. Internet High. Educ. 2006 , 9 , 175–190. [ Google Scholar ] [ CrossRef ]
• Wiggins, G. Educative Assessment. Designing Assessments To Inform and Improve Student Performance ; ERIC: Washington, DC, USA, 1998. [ Google Scholar ]
• Yukselturk, E.; Bulut, S. Predictors for Student Success in an Online Course. J. Educ. Technol. Soc. 2007 , 10 , 71–83. [ Google Scholar ]
• Deci, E.L.; Ryan, R.M. The “What” and “Why” of Goal Pursuits: Human Needs and the Self-Determination of Behavior. Psychol. Inq. 2000 , 11 , 227–268. [ Google Scholar ] [ CrossRef ]
• Locke, E.A.; Latham, G.P. A Theory of Goal Setting & Task Performance ; Prentice-Hall, Inc.: Hoboken, NJ, USA, 1990. [ Google Scholar ]
• Salmon, G. E-Tivities: The Key to Active Online Learning ; Routledge: Oxfordshire, UK, 2013. [ Google Scholar ]
• Koehler, M.; Mishra, P. What Is Technological Pedagogical Content Knowledge (TPACK)? Contemp. Issues Technol. Teach. Educ. 2009 , 9 , 60–70. [ Google Scholar ] [ CrossRef ]
• Petretto, D.R.; Carta, S.M.; Cataudella, S.; Masala, I.; Mascia, M.L.; Penna, M.P.; Piras, P.; Pistis, I.; Masala, C. The Use of Distance Learning and E-Learning in Students with Learning Disabilities: A Review on the Effects and Some Hint of Analysis on the Use during COVID-19 Outbreak. Clin. Pract. Epidemiol. Ment. Health 2021 , 17 , 92–102. [ Google Scholar ] [ CrossRef ]
• Lodder, J.; Heeren, B.; Jeuring, J. A Comparison of Elaborated and Restricted Feedback in LogEx, a Tool for Teaching Rewriting Logical Formulae. J. Comput. Assist. Learn. 2019 , 35 , 620–632. [ Google Scholar ] [ CrossRef ]
• Kocdar, S.; Bozkurt, A. Supporting Learners with Special Needs in Open, Distance, and Digital Education. In Handbook of Open, Distance and Digital Education ; Springer: Singapore, 2022; pp. 1–16. [ Google Scholar ]
• Tsai, Y.-S.; Rates, D.; Moreno-Marcos, P.M.; Muñoz-Merino, P.J.; Jivet, I.; Scheffel, M.; Drachsler, H.; Kloos, C.D.; Gašević, D. Learning Analytics in European Higher Education—Trends and Barriers. Comput. Educ. 2020 , 155 , 103933. [ Google Scholar ] [ CrossRef ]
• Ladson-Billings, G. Culturally Relevant Pedagogy 2.0: Aka the Remix. Harv. Educ. Rev. 2014 , 84 , 74–84. [ Google Scholar ] [ CrossRef ]
• Means, B.; Bakia, M.; Murphy, R. Learning Online: What Research Tells Us about Whether, When and How ; Routledge: Oxfordshire, UK, 2014. [ Google Scholar ]
• Gray, J.A.; DiLoreto, M. The Effects of Student Engagement, Student Satisfaction, and Perceived Learning in Online Learning Environments. Int. J. Educ. Leadersh. Prep. 2016 , 11 , n1. [ Google Scholar ]
• Garrison, D.R.; Cleveland-Innes, M. Facilitating Cognitive Presence in Online Learning: Interaction Is Not Enough. Am. J. Distance Educ. 2005 , 19 , 133–148. [ Google Scholar ] [ CrossRef ]
• Darling-Hammond, L.; Hyler, M.E.; Gardner, M. Effective Teacher Professional Development ; Learning Policy Institute: Palo Alto, CA, USA, 2017. [ Google Scholar ]
• Garrison, D.R.; Vaughan, N.D. Blended Learning in Higher Education: Framework, Principles, and Guidelines ; John Wiley & Sons: Hoboken, NJ, USA, 2008. [ Google Scholar ]
• Vygotsky, L.S.; Cole, M. Mind in Society: Development of Higher Psychological Processes ; Harvard University Press: Cambridge, MA, USA, 1978. [ Google Scholar ]
• Burlacu, M.; Coman, C.; Bularca, M.C. Blogged into the System: A Systematic Review of the Gamification in e-Learning before and during the COVID-19 Pandemic. Sustainability 2023 , 15 , 6476. [ Google Scholar ] [ CrossRef ]
• Yamani, H.A. A Conceptual Framework for Integrating Gamification in eLearning Systems Based on Instructional Design Model. Int. J. Emerg. Technol. Learn. 2021 , 16 , 14. [ Google Scholar ] [ CrossRef ]
• Siemens, G.; Baker, R.S.J.d. Learning Analytics and Educational Data Mining: Towards Communication and Collaboration. In Proceedings of the 2nd International Conference on Learning Analytics and Knowledge, Vancouver, BC, Canada, 29 April–2 May 2012; pp. 252–254. [ Google Scholar ]
• Li, L. Reskilling and Upskilling the Future-Ready Workforce for Industry 4.0 and Beyond. Inf. Syst. Front. 2022 . [ Google Scholar ] [ CrossRef ]
• Lythreatis, S.; Singh, S.K.; El-Kassar, A.-N. The Digital Divide: A Review and Future Research Agenda. Technol. Forecast. Soc. Change 2022 , 175 , 121359. [ Google Scholar ] [ CrossRef ]
• Tawfik, A.A.; Shepherd, C.E.; Gatewood, J.; Gish-Lieberman, J.J. First and Second Order Barriers to Teaching in K-12 Online Learning. TechTrends 2021 , 65 , 925–938. [ Google Scholar ] [ CrossRef ]
• Muñoz, F.; Matus, O.; Pérez, C.; Fasce, E. Blended Learning y El Desarrollo de La Comunicación Científica En Un Programa de Especialización Dental. Investig. En Educ. Médica 2017 , 6 , 180–189. [ Google Scholar ] [ CrossRef ]
• Barbour, M.K. Introducing a Special Collection of Papers on K-12 Online Learning and Continuity of Instruction after Emergency Remote Teaching. TechTrends 2022 , 66 , 298–300. [ Google Scholar ] [ CrossRef ]
• Khalil, M.; Slade, S.; Prinsloo, P. Learning Analytics in Support of Inclusiveness and Disabled Students: A Systematic Review. J. Comput. High. Educ. 2023 , 1–18. [ Google Scholar ] [ CrossRef ]
• Prinsloo, P.; Slade, S. Student Privacy Self-Management: Implications for Learning Analytics. In Proceedings of the Fifth International Conference on Learning Analytics and Knowledge, Poughkeepsie, NY, USA, 16–20 March 2015; pp. 83–92. [ Google Scholar ]
• Watson, G.R.; Sottile, J. Cheating in the Digital Age: Do Students Cheat More in Online Courses? Online J. Distance Learn. Adm. 2010 , 13 , 798–803. [ Google Scholar ]
• Bhattacharya, S.; Murthy, V.; Bhattacharya, S. The Social and Ethical Issues of Online Learning during the Pandemic and Beyond. Asian J. Bus. Ethics 2022 , 11 , 275–293. [ Google Scholar ] [ CrossRef ]
• Yadav, K.K.; Reddy, L.J. Psychological effects of technology on college students. J. Clin. Otorhinolaryngol. Head Neck Surg. 2023 , 27 , 1805–1816. [ Google Scholar ]
• Martin, F.; Bolliger, D.U. Engagement Matters: Student Perceptions on the Importance of Engagement Strategies in the Online Learning Environment. Online Learn. 2018 , 22 , 205–222. [ Google Scholar ] [ CrossRef ]
• Clemente-Suárez, V.J.; Dalamitros, A.A.; Beltran-Velasco, A.I.; Mielgo-Ayuso, J.; Tornero-Aguilera, J.F. Social and psychophysiological consequences of the COVID-19 pandemic: An extensive literature review. Front. Psychol. 2020 , 11 , 3077. [ Google Scholar ] [ CrossRef ]
• Clemente-Suárez, V.J.; Navarro-Jiménez, E.; Jimenez, M.; Hormeño-Holgado, A.; Martinez-Gonzalez, M.B.; Benitez-Agudelo, J.C.; Perez-Palencia, N.; Laborde-Cárdenas, C.C.; Tornero-Aguilera, J.F. Impact of COVID-19 Pandemic in Public Mental Health: An Extensive Narrative Review. Sustainability 2021 , 13 , 3221. [ Google Scholar ] [ CrossRef ]
• Clemente-Suárez, V.J.; Navarro-Jiménez, E.; Moreno-Luna, L.; Saavedra-Serrano, M.C.; Jimenez, M.; Simón, J.A.; Tornero-Aguilera, J.F. The Impact of the COVID-19 Pandemic on Social, Health, and Economy. Sustainability 2021 , 13 , 6314. [ Google Scholar ] [ CrossRef ]
• Rodriguez-Besteiro, S.; Beltran-Velasco, A.I.; Tornero-Aguilera, J.F.; Martínez-González, M.B.; Navarro-Jiménez, E.; Yáñez-Sepúlveda, R.; Clemente-Suárez, V.J. Social Media, Anxiety and COVID-19 Lockdown Measurement Compliance. Int. J. Environ. Res. Public Health 2023 , 20 , 4416. [ Google Scholar ] [ CrossRef ]
• Clemente-Suárez, V.J.; Navarro-Jiménez, E.; Simón-Sanjurjo, J.A.; Beltran-Velasco, A.I.; Laborde-Cárdenas, C.C.; Benitez-Agudelo, J.C.; Bustamante-Sánchez, Á.; Tornero-Aguilera, J.F. Mis–Dis Information in COVID-19 Health Crisis: A Narrative Review. Int. J. Environ. Res. Public Health 2022 , 19 , 5321. [ Google Scholar ] [ CrossRef ]
• Clemente-Suárez, V.J.; Navarro-Jiménez, E.; Ruisoto, P.; Dalamitros, A.A.; Beltran-Velasco, A.I.; Hormeño-Holgado, A.; Laborde-Cárdenas, C.C.; Tornero-Aguilera, J.F. Performance of Fuzzy Multi-Criteria Decision Analysis of Emergency System in COVID-19 Pandemic. An Extensive Narrative Review. Int. J. Environ. Res. Public Health 2021 , 18 , 5208. [ Google Scholar ] [ CrossRef ]
• Sato, S.N.; Condes Moreno, E.; Rico Villanueva, A.; Orquera Miranda, P.; Chiarella, P.; Tornero-Aguilera, J.F.; Clemente-Suárez, V.J. Cultural Differences between University Students in Online Learning Quality and Psychological Profile during COVID-19. J. Risk Financ. Manag. 2022 , 15 , 555. [ Google Scholar ] [ CrossRef ]
• Nomie-Sato, S.; Condes Moreno, E.; Villanueva, A.R.; Chiarella, P.; Tornero-Aguilera, J.F.; Beltrán-Velasco, A.I.; Clemente-Suárez, V.J. Gender Differences of University Students in the Online Teaching Quality and Psychological Profile during the COVID-19 Pandemic. Int. J. Environ. Res. Public Health 2022 , 19 , 14729. [ Google Scholar ] [ CrossRef ]
• Williamson, B.; Macgilchrist, F.; Potter, J. COVID-19 controversies and critical research in digital education. Learn. Media Technol. 2021 , 46 , 117–127. [ Google Scholar ] [ CrossRef ]
• Brammer, S.; Clark, T. COVID-19 and management education: Reflections on challenges, opportunities, and potential futures. Br. J. Manag. 2020 , 31 , 453. [ Google Scholar ] [ CrossRef ]
• Peytcheva-Forsyth, R.V.; Aleksieva, L.K. The effect of the teachers’ experience in online education during the pandemic on their views of strengths and weaknesses of e-learning (SU case). In Proceedings of the 22nd International Conference on Computer Systems and Technologies, Ruse, Bulgaria, 18–19 June 2021; pp. 1–11. [ Google Scholar ]
• Nguyen, T.; Netto, C.L.M.; Wilkins, J.F.; Bröker, P.; Vargas, E.E.; Sealfon, C.D.; Puthipiroj, P.; Li, K.S.; Bowler, J.E.; Hinson, H.R.; et al. Insights into students’ experiences and perceptions of remote learning methods: From the COVID-19 pandemic to best practice for the future. Front. Educ. 2021 , 6 , 91. [ Google Scholar ] [ CrossRef ]
• Goudeau, S.; Sanrey, C.; Stanczak, A.; Manstead, A.; Darnon, C. Why lockdown and distance learning during the COVID-19 pandemic are likely to increase the social class achievement gap. Nat. Hum. Behav. 2021 , 5 , 1273–1281. [ Google Scholar ] [ CrossRef ]
• Zhang, J.; Ding, Y.; Yang, X.; Zhong, J.; Qiu, X.; Zou, Z.; Xu, Y.; Jin, X.; Wu, X.; Huang, J.; et al. COVID-19′s impacts on the scope, effectiveness, and interaction characteristics of online learning: A social network analysis. PLoS ONE 2022 , 17 , e0273016. [ Google Scholar ] [ CrossRef ]
• Munoz-Najar, A.; Gilberto, A.; Hasan, A.; Cobo, C.; Azevedo, J.P.; Akmal, M. Remote Learning during COVID-19: Lessons from Today, Principles for Tomorrow ; World Bank: Washington, DC, USA, 2021. [ Google Scholar ]

Share and Cite

Sato, S.N.; Condes Moreno, E.; Rubio-Zarapuz, A.; Dalamitros, A.A.; Yañez-Sepulveda, R.; Tornero-Aguilera, J.F.; Clemente-Suárez, V.J. Navigating the New Normal: Adapting Online and Distance Learning in the Post-Pandemic Era. Educ. Sci. 2024 , 14 , 19. https://doi.org/10.3390/educsci14010019

Sato SN, Condes Moreno E, Rubio-Zarapuz A, Dalamitros AA, Yañez-Sepulveda R, Tornero-Aguilera JF, Clemente-Suárez VJ. Navigating the New Normal: Adapting Online and Distance Learning in the Post-Pandemic Era. Education Sciences . 2024; 14(1):19. https://doi.org/10.3390/educsci14010019

Sato, Simone Nomie, Emilia Condes Moreno, Alejandro Rubio-Zarapuz, Athanasios A. Dalamitros, Rodrigo Yañez-Sepulveda, Jose Francisco Tornero-Aguilera, and Vicente Javier Clemente-Suárez. 2024. "Navigating the New Normal: Adapting Online and Distance Learning in the Post-Pandemic Era" Education Sciences 14, no. 1: 19. https://doi.org/10.3390/educsci14010019

Article Metrics

Article access statistics, further information, mdpi initiatives, follow mdpi.

Subscribe to receive issue release notifications and newsletters from MDPI journals

Along with Stanford news and stories, show me:

• Student information
• Faculty/Staff information

We want to provide announcements, events, leadership messages and resources that are relevant to you. Your selection is stored in a browser cookie which you can remove at any time using “Clear all personalization” below.

Image credit: Claire Scully

New advances in technology are upending education, from the recent debut of new artificial intelligence (AI) chatbots like ChatGPT to the growing accessibility of virtual-reality tools that expand the boundaries of the classroom. For educators, at the heart of it all is the hope that every learner gets an equal chance to develop the skills they need to succeed. But that promise is not without its pitfalls.

“Technology is a game-changer for education – it offers the prospect of universal access to high-quality learning experiences, and it creates fundamentally new ways of teaching,” said Dan Schwartz, dean of Stanford Graduate School of Education (GSE), who is also a professor of educational technology at the GSE and faculty director of the Stanford Accelerator for Learning . “But there are a lot of ways we teach that aren’t great, and a big fear with AI in particular is that we just get more efficient at teaching badly. This is a moment to pay attention, to do things differently.”

For K-12 schools, this year also marks the end of the Elementary and Secondary School Emergency Relief (ESSER) funding program, which has provided pandemic recovery funds that many districts used to invest in educational software and systems. With these funds running out in September 2024, schools are trying to determine their best use of technology as they face the prospect of diminishing resources.

Here, Schwartz and other Stanford education scholars weigh in on some of the technology trends taking center stage in the classroom this year.

AI in the classroom

In 2023, the big story in technology and education was generative AI, following the introduction of ChatGPT and other chatbots that produce text seemingly written by a human in response to a question or prompt. Educators immediately worried that students would use the chatbot to cheat by trying to pass its writing off as their own. As schools move to adopt policies around students’ use of the tool, many are also beginning to explore potential opportunities – for example, to generate reading assignments or coach students during the writing process.

AI can also help automate tasks like grading and lesson planning, freeing teachers to do the human work that drew them into the profession in the first place, said Victor Lee, an associate professor at the GSE and faculty lead for the AI + Education initiative at the Stanford Accelerator for Learning. “I’m heartened to see some movement toward creating AI tools that make teachers’ lives better – not to replace them, but to give them the time to do the work that only teachers are able to do,” he said. “I hope to see more on that front.”

He also emphasized the need to teach students now to begin questioning and critiquing the development and use of AI. “AI is not going away,” said Lee, who is also director of CRAFT (Classroom-Ready Resources about AI for Teaching), which provides free resources to help teach AI literacy to high school students across subject areas. “We need to teach students how to understand and think critically about this technology.”

Immersive environments

The use of immersive technologies like augmented reality, virtual reality, and mixed reality is also expected to surge in the classroom, especially as new high-profile devices integrating these realities hit the marketplace in 2024.

The educational possibilities now go beyond putting on a headset and experiencing life in a distant location. With new technologies, students can create their own local interactive 360-degree scenarios, using just a cell phone or inexpensive camera and simple online tools.

“This is an area that’s really going to explode over the next couple of years,” said Kristen Pilner Blair, director of research for the Digital Learning initiative at the Stanford Accelerator for Learning, which runs a program exploring the use of virtual field trips to promote learning. “Students can learn about the effects of climate change, say, by virtually experiencing the impact on a particular environment. But they can also become creators, documenting and sharing immersive media that shows the effects where they live.”

Integrating AI into virtual simulations could also soon take the experience to another level, Schwartz said. “If your VR experience brings me to a redwood tree, you could have a window pop up that allows me to ask questions about the tree, and AI can deliver the answers.”

Gamification

Another trend expected to intensify this year is the gamification of learning activities, often featuring dynamic videos with interactive elements to engage and hold students’ attention.

“Gamification is a good motivator, because one key aspect is reward, which is very powerful,” said Schwartz. The downside? Rewards are specific to the activity at hand, which may not extend to learning more generally. “If I get rewarded for doing math in a space-age video game, it doesn’t mean I’m going to be motivated to do math anywhere else.”

Gamification sometimes tries to make “chocolate-covered broccoli,” Schwartz said, by adding art and rewards to make speeded response tasks involving single-answer, factual questions more fun. He hopes to see more creative play patterns that give students points for rethinking an approach or adapting their strategy, rather than only rewarding them for quickly producing a correct response.

Data-gathering and analysis

The growing use of technology in schools is producing massive amounts of data on students’ activities in the classroom and online. “We’re now able to capture moment-to-moment data, every keystroke a kid makes,” said Schwartz – data that can reveal areas of struggle and different learning opportunities, from solving a math problem to approaching a writing assignment.

But outside of research settings, he said, that type of granular data – now owned by tech companies – is more likely used to refine the design of the software than to provide teachers with actionable information.

The promise of personalized learning is being able to generate content aligned with students’ interests and skill levels, and making lessons more accessible for multilingual learners and students with disabilities. Realizing that promise requires that educators can make sense of the data that’s being collected, said Schwartz – and while advances in AI are making it easier to identify patterns and findings, the data also needs to be in a system and form educators can access and analyze for decision-making. Developing a usable infrastructure for that data, Schwartz said, is an important next step.

With the accumulation of student data comes privacy concerns: How is the data being collected? Are there regulations or guidelines around its use in decision-making? What steps are being taken to prevent unauthorized access? In 2023 K-12 schools experienced a rise in cyberattacks, underscoring the need to implement strong systems to safeguard student data.

Technology is “requiring people to check their assumptions about education,” said Schwartz, noting that AI in particular is very efficient at replicating biases and automating the way things have been done in the past, including poor models of instruction. “But it’s also opening up new possibilities for students producing material, and for being able to identify children who are not average so we can customize toward them. It’s an opportunity to think of entirely new ways of teaching – this is the path I hope to see.”

The changing role of teachers and technologies amidst the COVID 19 pandemic: key findings from a cross-country study

Maria barron, cristóbal cobo, alberto munoz-najar, inaki sanchez ciarrusta.

“Whoever teaches learns in the act of teaching and whoever learns teaches in the act of learning" wrote the Brazilian pedagogue Paulo Freire in his famous book “Pedagogy of Freedom” (1996). 

Despite the overwhelming consequences of the pandemic, this global crisis has also been an extraordinary time for learning. We are learning how adaptable and resilient educational systems, policy makers, teachers, students and families can be. In this blog (which is part of a series highlighting key lessons learned from a study to understand the perceived effectiveness of remote learning solutions, forthcoming) we summarize lessons learned in different countries, with special focus on teachers and how they had to quickly reimagine human connections and interactions to facilitate learning. The role of teachers is rapidly evolving becoming in many ways more difficult than when learning took place only in person. 

How has the pandemic changed the role of teachers?

Two crucial factors have shifted due to the pandemic. First, pedagogical adaptations have proven to be pivotal as the traditional lecturing in-person models do not translate to a remote learning environment. No matter the type of channel used (radio, TV, mobile, online platforms, etc.) teachers need to adapt their practices and be creative to keep students engaged as every household has become a classroom - more often than not - without an environment that supports learning. Some countries are supporting teachers with this. In Sierra Leone , where the main remote learning channel is radio, a ‘live’ and toll-free phone line is open for students to call teachers with questions and schedules of radio lessons allow time for children to help their families with daily chores.

Second, the pandemic has recalibrated how teachers divide their time between teaching, engaging with students, and administrative tasks. In Brazil according to a survey conducted by Instituto Peninsula, 83% of teachers did not consider being prepared to teach remotely, 67% were anxious, 38% felt tired, and less than 10% were happy or satisfied. The pandemic has highlighted the need for flexibility and more time for student-teacher interactions. For example, in Estonia teachers were given autonomy to adjust the curriculum, lesson plans, and their time allocation. 

How systems have supported teachers in their new role?

Almost 90% of countries that responded to the survey of Ministries of Education on National Responses to COVID-19 conducted by UNESCO, UNICEF, and the World Bank (2020) supported teachers by sharing guidelines stressing the importance of: providing feedback to students, maintaining constant communication with caregivers, and reporting to local education units to keep track of learning. Fewer governments took a different approach: Costa Rica developed a digital toolbox with pedagogical resources such as a guide for autonomous work, the state of São Paulo in Brazil organized frequent two-hour conversations between Secretary Rossieli Soares and teachers  through the mobile application developed by the state. These conversations and tools allowed governments to have an open line of communication with teachers to better understand their concerns and adjust remote learning programs.

As teachers started to implement these guidelines and recommendations, they found themselves balancing educating and providing feedback to students remotely, filling administrative reports, and taking care of their families. Some governments recognized early-on that their well-intentioned teacher support systems ended up generating burnout. Peru’s Ministry of Education was open to receive feedback and reacted rapidly by changing the guidelines to reduce teacher’s administrative workload. The state of Minas Gerais in Brazil developed the mobile application ‘Conexao Escola’ to encourage teacher-student interaction during designated time after each class, avoiding a situation in which students contacted teachers through WhatsApp or text message throughout the day. In Uruguay, teachers were expected to fill administrative information, but instead of requesting new information from them, the government decided to use GURI, a digital platform that has been used by Uruguayan teachers for over 10 years to report information such as student attendance and grades.

Beyond providing guidelines and tools, some governments have leveraged existing professional development programs that worked before the pandemic. The state of Edo in Nigeria trained all 11 thousand primary school teachers who are part of the Edo-BEST program in the past two years to effectively use digital technologies in the classroom; during the pandemic, this in-service teacher training program transitioned from in-person to remote training. Similarly, in Uruguay, The Institute for in-Service Teacher Training took an existing coaching program online to provide remote pedagogical support and Ceibal strengthened its teacher training program and Open Educational Resources repository. While over 90% of Uruguayan teachers were satisfied with the remote training received during the pandemic, some expressed the need for further training.

What impact have technologies generated in this changing role?  

Faced with the pandemic, countries have combined high-tech and low-tech approaches to help teachers better support student learning . In Cambodia, for example, education leaders designed a strategy that combines SMS, printed handouts, and continuous teacher feedback , taking advantage of the high mobile phone penetration in the country. The approach goes beyond providing low-tech materials: it gives information on how to access learning programs, ensures students access paper-based learning materials, and includes home visits to monitor distance learning activities. Teachers are also expected to provide weekly paper-based resources to students and meet them weekly to provide their marked worksheets and issue new ones for the week ahead.  

Technology has also enhanced government-teacher support , adapting existing coaching programs to be delivered remotely (as the mentioned cases of Nigeria and Uruguay), creating spaces for peer support programs (for example the Virtual EdCamps initiative, created to facilitate peer-to-peer learning among teachers) or establishing EdTech hotlines for teachers (like in Estonia, where the HITSA – the Information Technology Foundation for Education - opened an educational technology information line to solve any technological question teachers might have).

Technology interventions should enhance teacher engagement with students , through improved access to content, data and networks, helping teachers better support student learning, as laid out in the World Bank’s Platform for Successful Teachers , where effective use of technology is one of the key principles to ensure cadres of effective teachers. 

How policymakers can support teachers during the reopening of schools?

In order to build back stronger education systems, countries will need to apply those teaching initiatives that have proved to be effective during the remote learning phase and integrate them into the regular education system. It is critical to empower teachers , investing in the necessary skills development and capacity building to exploit the full potential of remote and blended learning. 

Equally important is to free teachers’ time from administrative tasks (as Brazil, Peru and Uruguay did), focus on what is pedagogically effective, and provide socio-emotional support for teachers.  The pandemic and the extended school closures have changed the role of teachers and most of them were not prepared for such change; a comprehensive strategy is required for socio-emotional monitoring and psychosocial support to ensure teacher wellbeing and avoid burnout.

• COVID-19 (coronavirus)

Get updates from Education for Global Development

Thank you for choosing to be part of the Education for Global Development community!

Your subscription is now active. The latest blog posts and blog-related announcements will be delivered directly to your email inbox. You may unsubscribe at any time.

Research Analyst and Co-lead of the World Bank EdTech team

Senior Education Specialist

Consultant, World Bank Group

Analyst, EdTech

Join the Conversation

• Share on mail
• comments added

• Instructional Technology
• Blended Learning

Integrating Technologies in the New Normal: A Study of Blended Learning

• December 2020
• International Journal of Quantitative Research and Modeling 1(4):181-193
• 1(4):181-193
• This person is not on ResearchGate, or hasn't claimed this research yet.

Discover the world's research

• 25+ million members
• 160+ million publication pages
• 2.3+ billion citations
• Galih Dewanti

• Widiyanto Widiyanto
• Amri Hartanto
• Muhammad Fikri Taufik
• Rahma Sakina
• Shadam Hussaeni Handi Pratama

• Rabaa Mmazhair
• Haady Abdilnibi Altememy
• Hayder Ali Hussein
• Mohamed Amer Alseidi
• Berti Yolida
• Rini Rita T. Marpaung
• Median Agus Priadi
• Aripati Sulika
• Rizki Amelia
• Ayunda . Wulandari

• Yetty Hastiana
• Saleh Hidayat
• Siti Rohmah

• Reza Rachmadtullah

• Masashi Inoue
• Wipanee Pengnate
• John W Creswell

• Recruit researchers
• Join for free
• Login Email Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google Welcome back! Please log in. Email · Hint Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google No account? Sign up

Home > Blog > Tips for Online Students > Discovering the Importance of Technology in Education 

Higher Education News , Tips for Online Students

Discovering the Importance of Technology in Education 

Updated: June 19, 2024

Published: May 24, 2019

Technology has taken over our world and has dramatically changed the way we live, work, and learn. In the education sector, technology has been a game-changer and has transformed the traditional methods of teaching and learning.  In a classroom setting, students are often given a lot of information to process quickly. This can be overwhelming and cause confusion. Technology provides access to numerous online resources that support independent learning and research. It also helps simplify the learning process by making concepts easier to understand, for example through instructional videos.   

Gone are the days of rote memorization and blackboard lectures. Today’s students are digital natives, who have grown up surrounded by technology and are accustomed to a more interactive, dynamic learning experience. Let’s take a closer look at the importance of technology in education.  

How Important is Technology in Education?  

Technology enhances the learning experience for students by providing them with the tools and resources necessary to succeed. From online resources that help simplify complex concepts to interactive learning experiences that keep students engaged, technology provides students with the support they need to thrive in the classroom and beyond. 

Here are reasons why technology is important in education. They include more engaged students, support for multiple learning styles, better collaboration, more instant feedback for teachers, and preparation for the future.   Let’s take a closer look at the importance of technology in education:  

Enhances Creativity and Innovation  

Technology has opened up a world of opportunities for students to be creative and innovative. With access to a wealth of information and resources at their fingertips, students can experiment, explore and bring their ideas to life.   

This type of hands-on learning is much more engaging and enjoyable for students and helps to foster critical thinking skills. For example, students can use graphic design software to create posters, animations, or videos to present their ideas.   

They can use 3D printing to design and create prototypes of their inventions. They can even use virtual and augmented reality to bring their ideas to life and make them more interactive.  

Supports Personalized Learning  

One of the biggest benefits of technology in education is personalized learning. With online resources and educational software, students can find information that is tailored to their needs, interests, and learning style.   

They can work at their own pace, repeat lessons if they need to, and access information that is relevant to their studies. This type of individualized learning can help students to stay motivated and achieve better results.  

Improves Communication and Collaboration  

Technology has revolutionized the way students, teachers, and administrators communicate and collaborate. With online platforms and social media, students can share ideas, work on projects, and stay connected no matter where they are. They can even work on projects with classmates from other schools or countries, breaking down geographical barriers and building a sense of community in the classroom.   

Furthermore, teachers can use technology to create interactive lessons, online quizzes and tests, and provide instant feedback to students, helping them to stay on track and improve their performance.  

Teaches Students How to be Responsible Online  

With so many social media options out there, it’s no surprise that students are already digital natives. But by bringing technology into the classroom, teachers get to help these students learn how to be responsible and make positive impacts in the digital world. The classroom becomes a mini version of the online world where students get to practice communicating, searching, and interacting with others just like they would in the real digital world.   

Makes Learning More Fun  

Students today are heavily reliant on technology in their daily lives outside the classroom. But incorporating technology in the classroom can not only make learning more interesting, but also help to reinforce the material taught. One innovative teaching method, game-based learning (GBL), involves using interactive games and leaderboards to deliver lessons, making the learning process much more engaging for students.  

With technology, students can also create multimedia projects and share their work with classmates, adding a creative element to the learning experience. Thanks to virtual reality (VR) and augmented reality (AR), students can take virtual field trips and simulations that can offer hands-on experiences that bring subjects to life.   

Prepares Students for the Future  

Technology is a critical tool for preparing students for the future. The workforce is rapidly evolving and technology is playing a significant role. Students need to be equipped with the skills they need to succeed in the digital age.   

Technology provides students with the tools and resources they need to develop a range of essential skills such as problem-solving, critical thinking, and collaboration. It also provides them with exposure to a variety of digital tools and platforms, helping them to become confident and proficient users.  

What Is the Role of Technology in Education?: The Future  

Wondering what is the role of technology in education ? The 3 important roles technology plays in education are increased collaboration and communication, personalized learning opportunities, and engaging content.  

The future of technology in education is bright and full of possibilities. From virtual and augmented reality to artificial intelligence and machine learning, technology is constantly evolving, and there is so much more to come. Virtual and augmented reality will soon become an integral part of the education experience, allowing students to immerse themselves in interactive, 3D simulations of real-life scenarios. Some benefits of technology in education include improved adaptability, more enriched collaboration, more enjoyable learning experiences, enhanced feedback, better connections, improved tech skills, and reduced costs.  

Artificial intelligence will also play a big role, with chatbots and AI-powered tutors providing instant feedback and support to students. Machine learning will also help to personalize the learning experience, making it more effective and efficient.  

In conclusion, technology has transformed the way we learn, and its impact on education has been profound. It has opened up new avenues for creativity and innovation, supported personalized learning, improved communication and collaboration, and prepared students for the future. As technology continues to evolve, it will be exciting to see how it will continue to shape and improve the education sector.  

In this article

At UoPeople, our blog writers are thinkers, researchers, and experts dedicated to curating articles relevant to our mission: making higher education accessible to everyone. Read More

Home — Essay Samples — Information Science and Technology — Technology in Education — The Role of Technology in Education

The Role of Technology in Education

• Categories: Children and Technology Technology in Education

About this sample

Words: 689 |

Published: Jun 24, 2024

Words: 689 | Pages: 2 | 4 min read

Cite this Essay

Let us write you an essay from scratch

• 450+ experts on 30 subjects ready to help
• Custom essay delivered in as few as 3 hours

Get high-quality help

Prof Ernest (PhD)

Verified writer

• Expert in: Information Science and Technology

+ 120 experts online

By clicking “Check Writers’ Offers”, you agree to our terms of service and privacy policy . We’ll occasionally send you promo and account related email

No need to pay just yet!

Related Essays

2 pages / 926 words

1 pages / 429 words

2 pages / 866 words

3 pages / 1670 words

Remember! This is just a sample.

You can get your custom paper by one of our expert writers.

121 writers online

Still can’t find what you need?

Browse our vast selection of original essay samples, each expertly formatted and styled

Related Essays on Technology in Education

Important to evaluate different subjects based on specific criteria to determine their effectiveness, value, quality, and significance. This essay will provide an evaluation of a given subject based on these criteria. The [...]

The emergence of e-learning has revolutionized the way we approach education. With the advancement of technology, traditional classroom settings are no longer the sole method of learning. E-learning, also known as online [...]

Education has long been heralded as the cornerstone of societal advancement. From ancient civilizations to modern-day societies, the role of education in shaping the minds and futures of individuals cannot be overstated. It [...]

Cell phones in schools have been a topic of debate for years, and the discourse continues to evolve. The core question remains: should cell phones be allowed in school? In this argumentative essay, we will delve deeper into this [...]

Technology in the classroom could possibly be the most important addition in the past two decades. Things like computers and tablets are used as educational tools to keep a classroom fun but also productive, but then why do [...]

The author's passion for technology and the impact of technology on the world Interest in problem-solving and its connection to technology Pursuing a diploma course in technology after secondary school Work [...]

Related Topics

By clicking “Send”, you agree to our Terms of service and Privacy statement . We will occasionally send you account related emails.

Where do you want us to send this sample?

By clicking “Continue”, you agree to our terms of service and privacy policy.

Be careful. This essay is not unique

This essay was donated by a student and is likely to have been used and submitted before

Download this Sample

Free samples may contain mistakes and not unique parts

Sorry, we could not paraphrase this essay. Our professional writers can rewrite it and get you a unique paper.

Please check your inbox.

We can write you a custom essay that will follow your exact instructions and meet the deadlines. Let's fix your grades together!

Get Your Personalized Essay in 3 Hours or Less!

We use cookies to personalyze your web-site experience. By continuing we’ll assume you board with our cookie policy .

• Instructions Followed To The Letter
• Deadlines Met At Every Stage
• Unique And Plagiarism Free

Advertisement

Special issue: What will be the new normal? Digital competence and 21st-century skills: critical and emergent issues in education

• Guest Editorial
• Published: 05 August 2023
• Volume 29 , pages 7697–7705, ( 2024 )

Cite this article

• Fazilat Siddiq 1 ,
• Anders D. Olofsson 2 ,
• J. Ola Lindberg 2 &
• Lukasz Tomczyk 3  

3502 Accesses

9 Citations

6 Altmetric

Explore all metrics

Avoid common mistakes on your manuscript.

1 Introduction

The practice of digital technology in education was redefined in many ways by the first lockdown due to the Covid-19 pandemic. While the pandemic, as in May 2023, is still changing and varies substantially across and within countries all over the world, educational institutional systems are constantly trying to find and adjust to what in this special issue is understood as ‘a new normal’. A new and different educational state-of-the-art emerged, characterised by its mode of leadership and teaching (online, blended, face-to-face) and content to be emphasised (e.g. subject knowledge and/or more generic competences such as (professional) digital competence, critical thinking, computational thinking, digital citizenship, in-depth learning, problem solving, and collaborative learning). Even though the focus and emphasis on digital competence and 21st-century skills were at large before the pandemic, it has certainly accelerated its acknowledgement and importance (Howard et al., 2021 ; Scherer et al., 2021 ). Moreover, the pandemic has brought the quality of both online and blended teaching, as well as the importance of digital technology and digital competence, to the forefront of educational transformation (Olofsson et al., 2021a ). The pandemic forced K–12 and higher education teachers and students to perform online and/or blended teaching and learning, and the quality of this endeavour has been reported as inconsistent between and within educational institutions and contexts (Howard et al., 2021 ; Scherer et al., 2021 ). Moreover, it was much characterised by a crisis-prompted situation and not necessarily a situation for which neither educational institutions, teachers, nor students were prepared (Ewing & Cooper, 2021 ).

Given the somewhat challenging and complex educational situation described above – ‘a new normal’ – it is at the same time interesting to notice that research studies presenting experiences during the pandemic have revealed examples of novel and motivating teaching and learning practices suggesting that teacher educators, teachers, student teachers and students have adapted to more digital environments (see for example, Ferdig et al., 2020 ; Khlaif et al., 2021 ). In light of such findings, it is an equally interesting observation that educational institutions in different parts of the world have been adapting and renewing educational policy and curricula to include digital competence and 21st-century skills as a formal part of national compulsory education for nearly two decades (Erstad & Siddiq, 2023 ; Olofsson et al., 2021b ; OECD, 2016 ). However, research has shown that the extent to which, and with which content and focus, these competence areas are taught, and teachers’ and students’ competencies and skills within these domains vary considerably (Howard et al., 2021 ; Siddiq et al., 2016 ). For example, Olofsson et al. ( 2021b ) argue that such variations can be due to the fact that the concept of digital competence can be considered plastic, temporal, and n-dimensional, a concept “that carries an intended meaning, which can be translated and negotiated relative to national educational needs and beliefs and with a possibility to be enacted in different ways in a situated local practice” (p. 323). Concerning the concept of 21st -century skills, which is oftentimes considered broad, and including a number of competence areas such as critical thinking, creativity, problem solving, computational thinking, collaboration, and ICT literacy, and defined as “the skills, knowledge, and expertise students must master to succeed in work and life – a blend of content, knowledge, specific skills, expertise, and literacies” (Partnership for 21st Century Skills, 2010, p. 8). Similarly, as with digital competence, 21st -century skills keep evolving along with the changes and needs in society (Erstad & Siddiq, 2023 ; Siddiq et al., 2017 ), such as including new competence areas, e.g., AI (artificial intelligence) literacy, and algorithmic literacy.

To sum up, this special issue includes papers that address, analyse, and discuss the challenging, nevertheless important, opportunity for educational institutions and research to investigate and consider the emergent issues related to digital competence and 21st-century skills. Our goal with this special issue is to contribute knowledge on how K–12 and higher education – in a time for considering ‘the new normal’ – work with digital competence and 21st-century skills, the lessons learned and how they are transforming to cope with unforeseen situations. Moreover, in this issue, we aim to contribute relevant knowledge and new perspectives on how we can move the field of digital technology in education forward – learning from the close past.

For this special issue, we initially received 104 original abstract submissions, of which 48 proceeded through the journal’s rigorous review process. Furthermore, the number of submitted full papers was 34, of which 15 were rejected, one delayed and one withdrawn. Hence, our call attracted researchers from around the world, and this issue consists of 17 papers written by 45 scholars from four continents: Asia, Australia, Europe, and North America. Moreover, they are from 9 different countries: Australia, Denmark, Hong Kong, Lithuania, Norway, Spain, Sweden, Switzerland and the USA. In the papers briefly presented below, three of them focused on literature reviews (Siddiq et al.; Ortiz-López et al.; and Bertel et al.), five on teacher education (Brianza et al.; Martín Bylund & Stenliden; Han et al.; Velander et al.; and Örtegren), four on digital integration, including voices from school leaders and teachers (Reis-Andersson; Löfving; Stumbrienė et al.; and Serrano Ausejo & Mårell-Olsson), and five on teaching, learning, and professional development with an online focus (Hathaway et al.; Prestridge et al.; Godhe; Kohnke et al.; and Svihus).

1.1 Theme 1 – literature reviews

While empirical research during post-Covid has increased in pace, there is also a need to develop theory in the field of digitalisation of education. This is utterly important in the view of ‘a new normal’ —to be able to understand and align with novel research and practice. The use of literature reviews as a methodology has gained increased ground in educational research over the last two decades. Systematic literature reviews are considered an adequate methodology for identifying what is considered state-of-the-art in a given field, and in particular for investigating research gaps and proposing further research needs (Petticrew & Roberts, 2006 ).

In this special issue, three different review types are included, focusing on digital agency, e-assessment, and emerging digital practices for supporting student-centred learning. The first paper is written by Siddiq, Mørk Røkenes, Lund, and Scherer. This study applies a conceptual systematic review methodology, and focuses on the concept of digital agency. Given the appearance of the digital agency concept in recent literature, it is being used interchangeably with the more established concept of (professional) digital competence. The researchers investigate conceptualisations of digital agency, its underlying theoretical frameworks, and how they relate to digital competence and similar concepts. The findings show that few studies explicitly define digital agency. Moreover, during the last three years, digital agency has been more frequently used in the literature, highlighting the need to include transformative perspectives when designing teaching and learning with technology. The second paper is conducted by Ortiz-López, Olmos-Migueláñez, and Sánchez-Prieto, and applies a mapping review methodology focusing on e-assessments in digital environments. This study investigates the state-of-the-art in this field, including the evolution of publications, the authors, the tools used, the contexts, the objectives of studies using e-assessment, and future avenues of research. The third paper is written by Bertel, Otto, Markman, Andersen, Lyngdorf, and Ryberg. It uses a systematic review methodology focusing on emerging digital practices that support student-centred learning environments in higher education. This study maps the general landscape of the online, hybrid, and blended digital practices applied in existing student-centred learning environments in higher education since the onset of the pandemic. The findings highlight critical factors and barriers related to emerging practices that support students’ interactions with teachers, content, and each other, as well as the emerging competencies that these practices will require.

1.2 Theme 2 – teacher education

As mentioned previously, the question of digital competence and PDC in teacher education (TE) and in K–12 schools has intensified in educational policy, research, and practice during the last few years. The answer to ‘why’, thus, is probably multi-faceted but jointly related to what in this special issue is termed ‘the new normal’. As mentioned previously, the first possible answer to why there is an extensively increased global interest in digital competence and PDC could be due to the pandemic. Teacher education institutions all over the world were forced overnight to make a transition into an emergency remote teaching (ERT) practice facilitated by digital technology (Ryberg, 2021 ). However, the pandemic in that sense cared little about the current level of neither teacher educators’ level of PDC nor their former experience of using digital technology in teaching and learning (see Bonk, 2020 ). The first paper, written by Brianza, Schmid, Tondeur, and Petko, is framed by this crisis-prompted condition for educational activities. Using TPACK as a theoretical lens, the authors investigated whether the experience of emergency remote teaching during the lockdown forced by the pandemic impacted teacher educators’ knowledge and beliefs about their future teaching with digital technology. One main finding in their work is that teacher educators maintained positive beliefs towards digital technology during the pandemic and were even able to draw benefits from the experience of lockdown. In line with this paper, the second paper, written by Martín Bylund and Stenliden, addresses the online lives of teacher educators and student teachers during the pandemic. Using a post-humanist problematization of communication, the authors investigated the body-sensory dimensions of presence in ERT. A central take-home message is the importance of being aware of how the material setting of online encounters affects the body and thus the didactic conditions for building meaningful relationships in an ERT environment.

The third paper is written by Han, Mørk Røkenes, and Krumsvik. It is also framed by the pandemic but more specifically focuses on TE in post-pandemic times. However, this paper also offers a second possible answer to the question of ‘why’ raised previously: a rapid digital integration in TE that can enhance pedagogical designs and methods probably not used in TE before the pandemic. In this case, this rapidly developed enhancement refers to the flipped classroom (FC). In that respect, this paper aims to provide evidence of student teachers’ perceptions of the FC to help teacher educators be knowledgeable about implementing a FC in a way that supports student teachers to reflect on the value of a FC in their teaching practice, a focus that also puts the spotlight on the dual didactical task to be performed by teacher educators (see Lindfors et al., 2021 ). One main finding reported is that even if student teachers prefer more courses flipped in their studies, they still seem hesitant about flipping their own courses in their teaching practice. The fourth paper, written by Velander, Taiye, Otero, and Milrad, provides an example of highly advanced digital technology making its way into TE, namely artificial intelligence (AI). Taking a theoretical stance in TPACK, the researchers explored both teacher educators’ and in-service teachers’ understanding and preconceptions of AI to inform TE and professional development. In the paper, Velander et al. report findings about teachers’ AI-related content knowledge, which is generally said to be gained through incidental learning and often results in pre- and misconceptions of AI.

A third, and final, possible answer of ‘why’ is to be found in the paper by Örtegren. According to Örtegren, given the highly digitalised society of today, including the increased presence of online deep fakes or disinformation, young people’s digital citizenship is a crucial aspect of democratic education in K–12 schools. This calls for student teachers to develop relevant PDC and teacher educators able to perform the dual didactical task of teaching student teachers how to teach digital citizenship in school. This paper offers a close reading of three conceptualisations of digital citizenship that could inform teacher educators’ dual didactical tasks in this matter. One main message of the paper is that conceptions of digital citizenship in TE need to be unpacked as they may impact future teachers’ preparation to teach for digital citizenship and, in turn, pupils’ digital citizenship formation.

1.3 Theme 3 – digital integration, including voices from school leaders and teachers

The pandemic has brought an increased awareness of how digital technologies are entering and redefining education, and school leaders, as well as teachers, have been made aware of how this leads to an expectancy for developing new competencies. In this theme, we have gathered papers that make this awareness apparent in different ways, and together, they give voice to school leaders and teachers on digital integration in different areas—from leadership to the classroom.

The first paper is written by Reis-Andersson, and accentuates the importance of school leaders in the digitalisation of education. Digitalisation in education creates opportunities that could lead to positive effects if digital technologies are applied correctly. However, insufficient integration of digital technologies can trigger a negative development – for example, increasing workload due to nonfriendly user interfaces in software and reducing the motivation to apply digital technologies in education due to a lack of digital competence. In this paper, Reis-Andersson utilises group interviews and a survey to show that school leaders describe the digitalisation process in the form of digital competence for teachers, access to hardware and software, and a shared culture. School leaders explain that clear guidelines, collaboration between teachers, and enough time enable digitalisation in education. Conversely, the lack of support and resources constrain digitalisation in education.

The second paper by Löfving, explores the complexity of teachers’ work in an increasingly digital society. Teachers are stipulated to carry out policy directives on both core knowledge and on more vaguely described cross-curricular competencies. In her study of 41 teachers in three lower secondary schools, she tried to make sense of and negotiate their students’ digital competence and cater to and develop this competence further. She shows that three main themes were discovered concerning how teachers make sense of students’ digital competence: digital content, creativity, and avoidance of digital usage. The findings showed there were discrepancies between what the teachers reported regarding their students’ digital competence and how the teachers handled the different aspects in their teaching practices, which raises questions on what adequate digital competence teachers need to address, and how it can be acted upon as a cross-curricular concept. However, it seems to be left to the teachers to make sense of this by themselves. One main conclusion is the importance of letting teachers regularly discuss students’ digital competence so that it is catered to and developed in a reflected, holistic, and thorough way.

The third paper by Stumbrienė, Jevsikova, and Kontvainė concerns the adoption of digital technology in educational practice. This study aims to identify the key factors that influence teachers’ motivations to transfer technology-enabled educational innovation in primary education. The findings show that motivation to transfer is significantly influenced by five domains: perceived value factors, personal characteristics, social practices, organisational factors, and technology-enabled innovation factors. Motivation to transfer innovation varies according to teachers’ perceived digital technology integration skills, which underpin the importance of applying different roles and strategies based on the teachers’ skills. The authors suggest that the findings could be a basis for designing effective professional development of in-service teachers and creating a suitable environment in schools for the adoption of innovation in post-pandemic education.

In the fourth and final paper of this theme, written by Serrano Ausejo and Mårell-Olsson, the use of immersive technologies, such as virtual reality (VR) and augmented reality (AR), in teaching organic chemistry is explored. The study aims to understand how these technologies might foster students’ spatial ability and 21st-century skills in K–12 education. Using design-based research methods, this exploratory study utilised immersive technologies as an instrument within three different groups in grade 8. The results show that in implementing teaching activities, it is necessary for a teacher to possess technological know-how regarding immersive technologies to achieve the intended motives and goals for the teaching activity. Moreover, there is a need to develop knowledge about the added value these immersive technologies offer to increase students’ learning processes and foster their spatial and 21st-century skills.

1.4 Theme 4 – teaching, learning, and professional development with an online focus

The pandemic was a milestone in the digitalisation of education around the globe. The transition to ERT represented, on the one hand, an organisational and technological challenge and, on the other hand, a revelation of the real level of digital competence among stakeholders around and within educational institutions (Abdel-Hameed et al., 2021 ). On the basis of the cumulative experience of ERT (Walter & Pyżalski, 2022 ), new areas of research have emerged, together with new postulates among teachers and directors of formal and non-formal educational institutions. Given the need to transform the educational system while taking into account the rich palette of experiences from the pandemic period, this theme focuses on several key areas related to learning, teaching, and professional development.

The first paper, by Hathaway, Gudmundsdottir, and Korona, reports from a comparative study between Norway and the US – two societies considered to be leaders in the digitalisation of education. Despite the relatively high level of digitalisation in both countries, the authors highlighted critical areas of digital competence that need improvement in both Norway and the US. This paper also highlights the universality of the global challenges relating to the ability to integrate ICT into teaching, and organisational processes, as faced by teaching staff during the period of the pandemic.

The second paper, written by Prestridge, Main, and Schmid, focuses on issues related to the different forms of online and blended presence. Based on qualitative research, the findings highlight the important issue of understanding and adapting forms of distance learning in the context of students’ and teachers’ needs for co-presence and engagement. The paper offers a ground for reflection for media educators and teachers who have struggled during ERT with the lack of physically mediated interactions typical of classroom teaching.

The third paper, written by Godhe, investigates the challenges faced by teachers in Sweden during the first months of the pandemic. The findings suggest that technological aspects do not represent the biggest barriers to the transition to ERT. Rather, other dimensions, such as pedagogical (methodological) and social issues, are key. Further, the paper shows that the ‘soft’ areas (not directly related to the technological dimension) of distance teaching and learning were a challenge that teachers faced during the pandemic and that the same challenges may still need to be faced in the future. This is an area to which special attention should be paid when shaping PDC among future and current teachers.

Kohnke, Foung, and Zou highlight several key issues related to the digitalisation of education. This team explored teachers’ professional development in online and blended learning through microlearning. Drawing on both qualitative and quantitative data, their findings show that microlearning was perceived as flexible and allowed the teachers to focus on small, relevant, and immediate tasks that nurtured the development of their digital competence. Moreover, the results show that previous PDC development programmes were perceived as too general, requiring further development to better prepare teachers for online and blended teaching.

In the final paper of this special issue, written by Larsen Svihus, the implications of ERT in the working lives of teachers in the higher education sector were considered. Svihus used qualitative interviews to capture challenges faced by academics in new media-mediated university classes (e.g., the inability to meet student activation needs, and dealing with modes of interaction on different platforms). A key finding of this study is that the challenges that emerged during the pandemic were typical among both experienced teaching staff and newcomers to higher education teaching.

1.5 Some concluding remarks

This special issue aimed to contribute relevant knowledge and new perspectives on how researchers and practitioners can move the field of digitalisation of education forward – learning from the close past in a time for considering ‘the new normal’. Our goal was to contribute knowledge on how K–12 education, including schools, leadership, teachers, and students, work with digital competence and 21st-century skills, and how they are transforming to cope with unforeseen situations. We have succeeded in providing examples of how the role of teachers and students has changed in an uncertain situation, a role requiring stepping in and out of face-to-face, online, hybrid, and/or blended teaching and learning. Moreover, we seek to better understand how local or national educational policy is concerned with issues related to digital competence and 21st-century skills, as well as how theoretical and conceptual changes are taking place within these domains.

The 17 papers included in this special issue encompass a wide range of research addressing the areas above through original research on the four different themes of the issue. Together, they provide literature reviews, research on teacher education and digital integration, as well as on teaching, learning, and professional development. In the continuing shift into a ‘new normal’, this special issue at several aggregation levels considers critical and emergent issues regarding digital competence and 21st-century skills in K–12 and in higher education.

We welcome you to engage with the included papers and enjoy the perspectives on ‘the new normal’ presented.

Fazilat Siddiq, Anders D. Olofsson, J. Ola Lindberg, and Lukasz Tomczyk

Guest Editors, August 02, 2023

Abdel-Hameed, F. S. M., Tomczyk, Ł., & Hu, C. (2021). The editorial of special issue on education, IT, and the Covid-19. Pandemic. Education and Information Technologies , 26 (6), 6563–6566. https://doi.org/10.1007/s10639-021-10781-z .

Article   Google Scholar  

Bonk, C. J. (2020). Pandemic ponderings, 30 years to today: Synchronous signals, saviors, or survivors? Distance Education , 41 (4), 589–599.

Erstad, O., & Siddiq, F. (2023). Educational assessment of 21st century skills—Novel initiatives, yet a /lack of systemic transformation. Editor(s): Robert J. Tierney, Fazal Rizvi, Kadriye Erkican, International Encyclopedia of Education (Fourth Edition), Elsevier, 2023, Pages 245–255, ISBN 9780128186299, https://doi.org/10.1016/B978-0-12-818630-5.09038-2 .

Ewing, L. A., & Cooper, H. (2021). Technology-enabled remote learning during Covid-19: Perspectives of australian teachers, students and parents. Technology Pedagogy and Education , 30 (1), 39–54. https://doi.org/10.1080/1475939X.2020.1868562 .

Ferdig, R. E., Baumgartner, E., Hartshorne, R., Kaplan-Rakowski, R., & Mouza, C. (Eds.). (2020). Teaching, technology, and teacher education during the Covid-19 pandemic: Stories from the field . Association for the Advancement of Computing in Education (AACE). Retrieved March 2023 from https://www.learntechlib.org/p/216903/ .

Howard, K. S., Tondeur, J., Siddiq, F., & Scherer, R. (2021). Ready, set, go! Profiling teachers’ readiness for online teaching in secondary education. Technology Pedagogy and Education , 30 (1), 141–158. https://doi.org/10.1080/1475939X.2020.1839543 .

Khlaif, Z. N., Salha, S., Affouneh, S., Rashed, H., & ElKimishy, L. A. (2021). The Covid-19 epidemic: Teachers’ responses to school closure in developing countries. Technology Pedagogy and Education , 30 (1), 95–109. https://doi.org/10.1080/1475939X.2020.1851752 .

Lindfors, M., Pettersson, F., & Olofsson, A. D. (2021). Conditions for professional digital competence: The teacher educators’ view. Education Inquiry , 12 (4), 390–409.

Skills for a digital world: 2016 ministerial meeting on the digital economy background report. OECD Digital Economy Papers, 250, OECD OECD, & Publishing (2016). https://doi.org/10.1787/5jlwz83z3wnw-en .

Olofsson, A. D., Lindberg, J. O., & Fransson, G. (2021a). Swedish upper secondary school teachers’ experiences with coping with emergency remote teaching (ERT) - emerging pedagogical issues in pandemic times. Education in the North , 28 (3), 85–99.

Google Scholar  

Olofsson, A. D., Lindberg, J. O., Young Pedersen, A., Arstorp, A. T., Dalsgaard, C., Einum, E., Caviglia, F., Ilomäki, L., Veermans, M., Häkkinen, P., & Willermark, S. (2021b). Digital competence across boundaries: Beyond a common nordic model of the digitalisation of K–12 schools? Education Inquiry , 12 (4), 317–328.

P21 (Partnership for 21st Century Skills) (2012). Learn for the 21st century. A report and mile guide for 21st century skills. Partnership for 21st Century Skills. Retrieved 12.02.2015 from http://www.p21.org/storage/documents/P21_Report.pdf .

Petticrew, M., & Roberts, H. (2006). Systematic reviews in the Social Sciences . A practical guide: Blackwell Publishing.

Book   Google Scholar  

Ryberg, T. (2021). Postdigital research, networked learning, and Covid-19. Postdigital Science and Education , 3 , 226–271.

Scherer, R., Howard, K. S., Tondeur, J., & Siddiq, F. (2021). Profiling teachers’ readiness for online teaching and learning in higher education: Who’s ready? Computers in human behavior 118. https://doi.org/10.1016/j.chb.2020.106675 .

Siddiq, F., Hatlevik, O. E., Olsen, R. V., Throndsen, I., & Scherer, R. (2016). Taking a future perspective by learning from the past: A systematic review of assessment instruments that aim to measure primary and secondary school students’ ICT literacy. Educational Research Review , 19 , 58–84.

Siddiq, F., Gochyyev, P., & Wilson, M. (2017). Learning in digital networks – ICT literacy: A novel assessment of students’ 21st century skills. Computers & Education , 109 , 11–37. https://doi.org/10.1016/j.compedu.2017.01.014 .

Walter, N., & Pyżalski, J. (2022). Lessons learned from Covid-19 emergency remote education. Adaptation to crisis distance education of teachers by developing new or modified digital competencies. Lecture Notes in Educational Technology , 7–23.

Download references

Author information

Authors and affiliations.

Unit for Digitalisation and Educational Quality (eDU), University of South-Eastern Norway, Postboks 4, Borre, 3199, Norway

Fazilat Siddiq

Umeå University, Umeå, Sweden

Anders D. Olofsson & J. Ola Lindberg

Jagiellonian University, Kraków, Poland

Lukasz Tomczyk

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Fazilat Siddiq .

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Siddiq, F., Olofsson, A.D., Lindberg, J.O. et al. Special issue: What will be the new normal? Digital competence and 21st-century skills: critical and emergent issues in education. Educ Inf Technol 29 , 7697–7705 (2024). https://doi.org/10.1007/s10639-023-12067-y

Download citation

Published : 05 August 2023

Issue Date : April 2024

DOI : https://doi.org/10.1007/s10639-023-12067-y

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Find a journal
• Publish with us
• Track your research

• Entertainment
• Environment
• Information Science and Technology
• Social Issues

Home Essay Samples Information Science and Technology Technology in Education

Technology in Education: An Argumentative Perspective

Table of contents, introduction, enhanced engagement and interaction, personalized learning and flexibility, development of 21st-century skills, the risks of overreliance and inequity, the balance between tradition and innovation, works cited.

*minimum deadline

Cite this Essay

To export a reference to this article please select a referencing style below

• A Day Without Technology
• Computer Graphics
• 3D Printing
• Digital Era
• Computer Science

Related Essays

Need writing help?

You can always rely on us no matter what type of paper you need

*No hidden charges

100% Unique Essays

Absolutely Confidential

Money Back Guarantee

By clicking “Send Essay”, you agree to our Terms of service and Privacy statement. We will occasionally send you account related emails

You can also get a UNIQUE essay on this or any other topic

Thank you! We’ll contact you as soon as possible.

• Research article
• Open access
• Published: 21 December 2020

Transitioning to the “new normal” of learning in unpredictable times: pedagogical practices and learning performance in fully online flipped classrooms

• Khe Foon Hew   ORCID: orcid.org/0000-0003-4149-533X 1 ,
• Chengyuan Jia 1 ,
• Donn Emmanuel Gonda 1 &
• Shurui Bai 1  

International Journal of Educational Technology in Higher Education volume  17 , Article number:  57 ( 2020 ) Cite this article

469k Accesses

95 Citations

12 Altmetric

Metrics details

The COVID-19 outbreak has compelled many universities to immediately switch to the online delivery of lessons. Many instructors, however, have found developing effective online lessons in a very short period of time very stressful and difficult. This study describes how we successfully addressed this crisis by transforming two conventional flipped classes into fully online flipped classes with the help of a cloud-based video conferencing app. As in a conventional flipped course, in a fully online flipped course students are encouraged to complete online pre-class work. But unlike in the conventional flipped approach, students do not subsequently meet face-to-face in physical classrooms, but rather online. This study examines the effect of fully online flipped classrooms on student learning performance in two stages. In Stage One, we explain how we drew on the 5E framework to design two conventional flipped classes. The 5E framework consists of five phases—Engage, Explore, Explain, Elaborate, and Evaluate. In Stage Two, we describe how we transformed the two conventional flipped classes into fully online flipped classes. Quantitative analyses of students’ final course marks reveal that the participants in the fully online flipped classes performed as effectively as participants in the conventional flipped learning classes. Our qualitative analyses of student and staff reflection data identify seven good practices for videoconferencing - assisted online flipped classrooms.

Introduction

“It’s now painfully clear that schools ought to have had more robust disaster-preparedness plans in place in the event of interruptions in their campus operations. But because many schools did not have such plans in place…online learning is about to get a bad reputation at many campuses, I suspect.” Michael Horn, cited in Lederman ( 2020 ), ‘Inside Higher Ed’.

In early January 2020, scientists identified a new infectious disease caused by a novel coronavirus. Since then, the COVID-19 pandemic has caused widespread disruptions to schools and universities. According to UNESCO, as of April 10, 2020, more than 188 countries had implemented nationwide school and university closures, impacting over 91% of the world’s student population (UNESCO n.d.).

During these school closures, all face-to-face lessons were cancelled, compelling many institutions, including our own university, to immediately transition from face-to-face in-person learning to completely online lessons. The abrupt switch to fully online learning has been particularly stressful for many instructors and students who prefer in-person instruction. Online learning is often stigmatized as a weaker option that provides a lower quality education than in-person face-to-face learning (Hodges et al. 2020 ). Indeed, such negative attitudes to fully online learning were revealed by a large EDUCAUSE survey (Pomerantz and Brooks 2017 ). The survey of 11,141 faculty members from 131 U.S. institutions found that only 9% of faculty prefer to teach a fully online course. In other words, a whopping 91% of faculty do not wish to teach in a completely online environment. Students’ opinions of fully online courses are not much better; a recent student survey by EDUCAUSE of more than 40,000 students across 118 American universities revealed that as many as 70% of the respondents mostly or completely prefer face-to-face learning environments (Gierdowski 2019 ).

Clearly, many faculty members and students do not see the value of fully online learning, despite the fact that online learning has been around for many decades. During the current health crisis, many instructors have had to improvise quick online learning solutions (Hodges et al. 2020 ). For example, in our own university, there are anecdotal reports of a myriad of emergency online methods. Some instructors, for example, merely uploaded their PowerPoint slides or papers onto a learning management system such as Moodle and asked students to read them on their own. Any questions were asked asynchronously on the Moodle forum. Other instructors recorded their own lectures (usually at least one hour long) and asked students to asynchronously watch the video lectures and then ask individual questions later. Still others talked for more than two hours via synchronous video platforms watched by students in their own homes. Although these online methods may be an efficient method of delivering content, they are not particularly effective in promoting active learning and interest (Bates and Galloway 2012 ). As one student remarked, “Sitting in front of my computer to watch a 2-h live lecture without any active learning activities such as group work is pretty boring!” Indeed, without any active learning activities such as peer interaction, a fully online course will feel more like an interactive book than a classroom (Sutterlin 2018 ).

Well-planned active online learning lessons are markedly different from the emergency online teaching offered in response to a crisis (Hodges et al. 2020 ). One promising strategy for promoting online active learning is the fully online flipped classroom pedagogical approach, hereafter referred to as the online flipped classroom approach. An online flipped classroom is a variant of the conventional flipped model. A conventional flipped classroom model consists of online learning of basic concepts before class, followed by face-to-face learning activities (Bishop and Verleger 2013 ). The conventional flipped model has become very popular in recent years due to its association with active learning, which emphasizes students’ active learning (Xiu and Thompson 2020 ). Active learning activities such as peer discussions can help students construct better understandings of the subject material (Deslauriers et al. 2019 ). Recent meta-analyses have provided consistent overall support for the superiority of the conventional flipped classroom approach over traditional learning for enhancing student learning (e.g., Låg and Sæle 2019 ; Lo and Hew 2019 ; Shi et al. 2019 ; van Alten et al. 2019 ).

The online flipped classroom is similar to the conventional flipped classroom model in that students are encouraged to prepare for class by completing some pre-class activities (e.g., watching video lectures, completing quizzes). However, unlike the conventional flipped classroom approach, students in online flipped classrooms do not meet face-to-face, but online (Stohr et al. 2020 ). Although the online flipped classroom appears to be gathering momentum in higher education, very few studies have examined its effectiveness (for an exception, see Stohr et al. 2020 , who compared the online flipped classroom format with a conventional non-flipped teaching format). So far, we are not cognizant of any research that evaluated the efficacy of the fully online flipped classroom relative to the conventional flipped classroom. Establishing the effectiveness of online flipped classrooms is important, as practitioners need to know whether this active learning approach can be used during prolonged school closures.

Against this backdrop, this study compares the effects of online flipped classrooms versus conventional flipped classrooms on student learning outcomes. To this end, two conventional flipped classes in the Faculty of Education are transformed into online flipped classrooms. Students in both the online and flipped classes participated in the online pre-class activity asynchronously using a learning management system. However, students in the online flipped classes joined the online in-class learning synchronously using a video conferencing app whereas their counterparts in the conventional flipped classes attended face-to-face classes. The online flipped courses were designed using the 5E conceptual framework and used a cloud-based video conferencing app. We used the Zoom application after careful consideration of many different videoconferencing platforms. Our reasons for doing so are given in the Section of “Stage Two: Transforming conventional flipped classes into online flipped classes”.

The 5E framework consists of five phases—Engage, Explore, Explain, Elaborate, and Evaluate (Bybee et al. 2006 ).

Engage—The first phase aims to engage students in the learning process. Methods to engage students usually include using a real-world scenario, or problem, asking students questions that allow them to brainstorm or think critically, and helping them to create connections to their past experiences.

Explore—In the exploration phase, the teacher, who works as a facilitator or coach, gives the students time and opportunity to explore the content and construct their own understanding of the topic at hand.

Explain—This phase starts with students attempting to explain specific aspects of the engagement and exploration experiences. Based on these explanations, the teacher introduces terminology in a direct and explicit manner to facilitate concept building.

Elaborate—In this phase, the teacher provided more detailed information about the subject content through the use of mini lectures and/or whole class discussions. Students are also given the opportunity to apply what they have learned and receive feedback from the teacher and their peers.

Evaluate—Formative assessments (e.g., quizzes) can be used to evaluate students’ mastery of the subject material at the beginning and throughout the 5E phases, and teachers can complete a summative assessment after the elaboration phase (e.g., final exams).

We adopted the 5E framework for the following reasons. First, the 5E framework, which is based on various educational theories and models (e.g., Herbart’s instructional model, Dewey’s instructional model, Atkin-Karplus Learning Cycle) (Bybee et al. 2006 ), provides a sound instructional sequence for designing a course and planning activities. The 5E framework can help instructors organize and integrate both the in-class and out-of-class learning activities (Lo 2017 ).

Second, previous research has shown the positive effect of the 5E framework on student achievement. These positive effects were initially established in science education (e.g., Akar 2005 ; Boddy et al. 2003 ). Recently, the 5E model has yielded positive results when applied to various subject areas and when used to design inquiry- and interaction-based learning activities. Mullins ( 2017 ), for example, found that undergraduate students in a 5E-supported class outperformed their peers in a traditional lecture setting. Hew et al. ( 2018 ) designed two postgraduate courses based on the 5E model in order to foster students’ active learning. Ninety-two percent of the participants agreed that the 5E supported courses were more engaging than traditional classroom instruction.

The rest of this paper is structured as follows. First, we describe our study design and methodology. This is followed by a description of our two stages of research. In Stage One, we explain how we use the 5E framework to design our two conventional flipped classes; In Stage Two, we describe how we transformed the two conventional flipped classes into fully online flipped classes, using a cloud-based video conferencing app. We describe the various pedagogical practices that Zoom videoconferencing can facilitate before and during online flipped classes. In this paper, we use the term “pedagogical practices” to refer to specific activities that are used to structure teaching and learning. This study is guided by the following two questions.

What effect does the change from a conventional flipped classroom format to an online flipped format have on student learning performance?

What are the good practices for videoconferencing - assisted online flipped classrooms, as perceived by students and/or teaching staff?

This study was conducted in a large public Asian university. Four classes were involved: (a) conventional flipped Course 1, (b) conventional flipped Course 2, (c) online flipped Course 1, and (d) online flipped Course 2. Conventional flipped Courses 1 and 2 were the control group. Online flipped Courses 1 and 2 were the experimental group. To avoid any potential instructor confounding bias, the same professor and teaching assistants (TAs) taught the conventional and online flipped formats of each class. Ethical approval to conduct the study was obtained from the Institutional Review Board at the University of Hong Kong and consent forms from all participants in the study were collected.

Data collection and analysis

To reiterate, this study had two purposes: (a) to determine the effect of an online flipped classroom on student learning performance as determined by student final course marks, and (b) to determine good practices for videoconferencing - assisted online flipped classrooms, as perceived by the participants (students and teaching staff). We adopted a mixed methods involving quantitative and qualitative approaches to provide a deeper understanding of the research problem (Ivankova et al. 2006 ).

The data collection spanned across two semesters, which corresponded to the aforementioned two stages of the research. The conventional flipped classes were implemented in conventional flipped Courses 1 and 2 during the semester of 2019 Fall before the pandemic (Stage One). Due to the outbreak of Covid-19, all courses were required to be delivered online in our university in the 2020 Spring semester. Therefore, the online flipped classes were conducted in online flipped Courses 1 and 2 during the pandemic in 2020 Spring (Stage Two). Students’ knowledge and skills of the course content were checked at the beginning of the each course. Students final course marks in each course were collected and used as measure of the student learning outcomes at the end of the semester (See Fig.  1 for the research timeline).

Timeline of data collection: 2019 Fall (before the pandemic), 2020 Spring (during the pandemic)

To address the first purpose, we compared the students’ final course marks in the online flipped classrooms and conventional flipped classrooms. Quantitative data from 99 students were collected (see Table 1 ). We used the students’ final course marks to measure performance.

To identify the perceived good practices for videoconferencing - assisted online flipped classrooms, we invited students and the teaching staff to complete a self-reflection exercise based on the following question: “What do you perceive as good practices in a videoconferencing-supported online flipped classroom?” The qualitative data collected from students and instructors were analyzed as follows. The first step was an initial reading of all of the response data to obtain an overall impression. The first author then applied the grounded approach (Strauss and Corbin 1990 ) to the qualitative data to generate relevant codes. Similar codes were organized into themes. In order to increase the consistency of coding, several exemplary quotes that clearly illustrated each constructed theme were identified. We also allowed new themes (if any) to emerge inductively during the coding process. The second author coded the data. There was perfect agreement with the coding. Table 2 summarizes how the data for each research question were collected and analyzed.

Stage one: designing conventional flipped classes using the 5E framework

In this section, we first describe how we use the 5E framework to design our two conventional flipped classes (Course 1: E-Learning Strategies , and Course 2: Engaging Adult Learners ). In the next section, we describe how we transform these two conventional flipped classes into fully online flipped classes. Figure  2 shows the 5E framework that guided our design of the conventional flipped classes. Table 3 shows some of the teaching and learning activities used in each of the 5E phases.

5E framework used to design the two conventional flipped classes

Conventional flipped course 1: E-learning strategies

This course discussed the various e-learning strategies that can be employed to foster six types of learning, including problem-solving, attitude learning, factual learning, concept learning, procedural learning, and principle learning. There were eight sessions in the course. The first seven sessions were flipped—each consisting of an online pre-class learning component and a 3-h face-to-face in-class component. The last session was devoted to students’ presentations. Figure  3 shows an example of how the 5E framework was used in Course 1.

Example of a pre-class activity in Course 1

For instance, in the pre-class phase of Session 2: Instructional Design—Part 1 , we posted a video that posed the question “What do we mean by ‘understand’”. This video engaged students’ curiosity about the importance of writing clear and measurable learning objectives. The instructor in the video highlighted the pitfalls of using vague words such as “know” and “understand” when writing learning objectives. Students then explored and explained their own individual learning objectives using the ABCD model (audience, behavior, condition, degree). Students were able to use a mobile instant messaging (MIM) app such as WeChat to ask questions of their peers or instructor. When a message arrived, a notification appeared on the receiver’s phone screen, encouraging timely feedback and frequent interaction (Rosenfeld et al. 2018 ).

During the face-to-face in-class session, the instructor re-engaged students’ attention by discussing basic instructional design issues such as “How do we write good lesson objectives?” The instructor conducted short debriefing sessions to discuss the strengths and weaknesses of students’ pre-class work. The instructor also facilitated class or small group discussions to build students’ understanding of how to write measurable lesson objectives that help students to achieve specific learning outcomes (e.g., factual learning). These discussions allowed students to elaborate on good lesson objectives practices. To evaluate the students’ understanding, the instructor asked them to work in groups of four on an instructional design scenario (e.g., teaching participants how to deal with angry customers), and then write a learning objective for the lesson in an online forum; their peers then commented on the posted learning objectives (Fig.  4 ).

Example of an in-class activity in Course 1

Conventional flipped course 2: engaging adult learners

This course discussed the key principles of adult learning, as well as strategies used in adult education (e.g., transformational learning theory). There were eight sessions in the course, each session lasted three hours. An example of how the 5E instructional model was used is shown in Fig.  5 .

Example of a pre-class activity in Course 2

For example, in the pre-class session for Session 3: Motivation, we uploaded a four-minute video that briefly described the concepts of reinforcement and punishment. The aim of the video was to engage students’ attention on the focal topic. To help students explore the topic in further, they were asked to respond to the following question: “After watching the video, can you think of other positive reinforcers, negative reinforcers, and punishment methods?” Students posted their opinions ( explained ) on a discussion forum. Students also used the WeChat app to ask questions of their peers or instructor.

During the subsequent face-to-face lesson (Fig.  6 ), the instructor facilitated whole class discussions using relevant questions to elaborate on the topics covered in the pre-class video. An example of a question used was ‘When should we employ positive reinforcement, negative reinforcement, or punishment?’ Based on the students’ responses, the instructor was able to provide more in-depth explanation of the subject matter, or correct any student misunderstanding. This will help enhance students’ comprehension of the subject content. The instructor also discussed the notion of intrinsic motivation (e.g., the self-determination theory). In addition to elaborating on the content, the instructor also evaluated the students’ understanding by asking students to complete small group discussion activities. An example of a small group discussion activity was ‘Did you have any experience where you did not like learning a subject or doing an activity? How would you motivate yourself in that situation? Please try to use a mixture of intrinsic and extrinsic motivation factors.’ Upon completion of the small group activity, students from each group presented their views to the whole class. The instructor, as well as the rest of the classmates provided feedback.

Example of an in-class activity in Course 2

Stage two: transforming conventional flipped classes into online flipped classes

The outbreak of COVID-19 inspired us to transform the two conventional flipped classes discussed above into fully online flipped classes. After careful consideration, the Zoom videoconferencing app was used for the synchronized online meetings (see Table 4 ). The whole transformation process took about one week with the bulk of the time was spent on exploring and testing the features of Zoom.

Zoom is a Web videoconferencing service that allows users to communicate online with individuals in real time via computer, tablet, or mobile device. We chose Zoom because of its ease of use (Kim 2017 ; Sutterlin 2018 ), its lower bandwidth requirements (Sutterlin 2018 ), and its ability to record and store sessions without recourse to third-party software (Archibald et al. 2019 ). More importantly, Zoom was chosen because its functions could easily support the implementation of our online flipped classroom. For instance, it allows instructors to easily create breakout rooms for group discussions. It also makes team-teaching possible by allowing more than one host and giving all of the hosts administrative capabilities such as sharing screens and remote control over shared screens (Johnston 2020 ).

To keep our online meetings secure, we activated the “ only authenticated users can join ” option. Specifically, we only allowed participants using our own university’s email domain to join the online meetings. In addition, we enabled the “ waiting room ” feature so that we could screen all of participants in the “ waiting room ” and admit only students officially enrolled in our classes into the online meeting. After all of the participants had entered, we then locked the meeting using the “ Lock the meeting ” feature. Once we had locked a meeting, no new participants could join.

The same learning materials used in the conventional flipped classes were used in the online flipped classes. Table 4 shows some of the teaching and learning activities. Students in the online flipped classes completed pre-class activities that were similar to those used in the conventional flipped classes, but these were not followed by face-to-face meetings, but by online meetings conducted on the Zoom videoconferencing app.

Online flipped course 1: E-learning strategies

Like the conventional flipped course, the online flipped Course 1 consisted of eight sessions. The first seven sessions were flipped—students were encouraged to complete a set of pre-class sessions asynchronously (similar to Fig.  3 ). Students also used the WeChat MIM app to ask questions of their peers or instructors. However, unlike the conventional flipped approach, the “in-class” session for the online flipped students was conducted completely online through Zoom videoconferencing. In the final session (Session 8), the online flipped students also presented their work on Zoom. Each online “in-class” session lasted three hours—similar in duration to the in-class component of the conventional flipped format.

In the online synchronous “in-class” sessions, the instructor started by reminding students to switch on their webcams and to mute their microphones when not speaking. Next, the instructor lead a short class debriefing session to elaborate on the materials covered in the pre-class session. This was similar to the structure of the conventional flipped class format. For example, the instructor might discuss the students’ completed pre-class work and highlight the overall strengths and weaknesses. The main purpose of these short debriefing sessions was to clarify students’ initial doubts or misconceptions. Following the debriefing sessions, the instructor facilitated class discussions that delved deeper into the subject content. To evaluate students’ understanding of the materials, students were asked to work individually or participate in small group discussions on specific questions similar to those used in the conventional flipped classes. Students then presented their work online to the whole class, and received peer and instructor feedback.

To engage the participants, the instructor used a number of features of the Zoom videoconferencing system. For example, the instructor posed questions during the whole class discussion and used the polling feature to rapidly collect and analyze student responses. The polling feature provided a function similar to a clicker or student response system. Based on the poll results, the instructor then addressed students’ misunderstandings. To enable small group discussions, the instructor used the breakout rooms feature of Zoom . Each student was assigned to one of several groups. Each group consisted of four to five students. Other students could not “drop” into other groups, but the instructor could drop into any group and participate in the discussions. When it was time for the small groups to return to the whole class, students would receive a time indicator reminding them that they were rejoining the whole class. Table 5 shows how the specific features of Zoom helped support the online “in-class” teaching and learning activities. Figure  7 illustrates some of the Zoom features used in the course.

Examples of Zoom features used in Course 1

Online flipped course 2: engaging adult learners

Similar to the conventional flipped course, the online flipped course had eight sessions. The pre-class and in-class activities used in the conventional flipped course were also used in the online flipped course (see Fig.  5 for an example of a pre-class activity). Students also used the WeChat MIM app to ask questions of their peers or instructors. The last three sessions were used for students’ online presentations via videoconferencing. Each online “in-class” session lasted three hours—similar in duration to the in-class component of the conventional flipped class. In the online synchronous “in-class” sessions, the instructor reminded students to switch on their webcams and to mute their microphones when not speaking. The instructor used the features of the Zoom videoconferencing system shown in Table 5 and Fig.  7 .

Results and discussion

Conventional flipped versus online flipped course 1: e-learning strategies.

To address Research Question 1, the learning outcomes of students in the conventional flipped Course 1 and the online flipped Course 1 were measured and compared. The main purpose of both courses was to teach students the skills needed to create an e-learning storyboard and to develop a fully online course based on the 5E framework on Moodle. At the beginning of both the conventional flipped and online flipped classes, students were surveyed if they had any experience creating storyboards or fully online courses. None of the students had any such prior experience. Therefore, we assumed that both groups of students had similar levels of prior knowledge/skill. Next, we used both groups of students’ final course marks as a measure of the student learning outcomes. The maximum final marks in the final assessment was 100.

We first checked the normality of the final course marks data. If there were a significant deviation from normality, the Mann–Whitney U would be the most appropriate test for comparing the groups; otherwise, an independent samples t -test would be appropriate. The results showed that the course marks for both the conventional flipped ( W (23) = 0.920, p  = 0.068) and online flipped classes ( W (26) = 0.964, p  = 0.479) were normally distributed, as assessed by the Shapiro–Wilk’s test. There was also homogeneity in the variances for the course marks, as assessed by Levene’s test for equality of variances ( p  = 0.652). In addition, there were no outliers in the data, as assessed by an inspection of the boxplots (Fig.  8 ).

The boxplots of final marks in Course 1 for conventional flipped class and online flipped class

An independent-samples t -test was therefore conducted to determine if there were differences in the final marks of the conventional flipped and online flipped classes. The results suggested that online flipped participants ( M  = 66.00, SD = 11.63) performed as effectively as participants in the conventional flipped learning format ( M  = 65.04, SD = 11.80), t (47) = 0.285, p  = 0.777.

Conventional flipped versus online flipped course 2: engaging adult learners

The main purpose of both the conventional flipped and online flipped Engaging Adult Learners courses was to introduce students to the key characteristics of adult learners, the key principles of adult learning, and strategies for adult education. First, to test if there were any initial differences in students’ prior knowledge of the course content, a short quiz was administered to both groups at the start of the semester. The Mann–Whitney U test found no significant initial differences between the conventional flipped group ( Mdn  = 0) and the online flipped group ( Mdn  = 0.5), U  = 218.5, p  = 0.06.

Next, we used the students’ final course marks as a measure of the student learning outcomes. The final assessment included individual written reflections on course topics and relevant articles, and a group demonstration of an adult-teaching strategy. The maximum final marks for the final assessment was 100. As in the above analysis, we first checked the normality of the final course mark data. The course marks for both the conventional flipped and online flipped classes were normally distributed, as assessed by Shapiro–Wilk’s test: W (25) = 0.963, p  = 0.470 for the conventional flipped course and W (24) = 0.930, p  = 0.096 for the online flipped course. There was also a homogeneity of variances, as assessed by Levene’s test for equality of variances ( p  = 0.304). In addition, there were no outliers in the data, as assessed by an inspection of the boxplots (Fig.  9 ).

The boxplots of final marks in Course 2 for conventional flipped class and online flipped class

We subsequently carried out an independent-samples t-test to examine if there was any significant difference in the final course marks of the conventional flipped and online flipped classes. The results suggested that online flipped learning participants ( M  = 83.25, SD = 4.56) performed as effectively as participants in the conventional flipped learning classes ( M  = 83.40, SD = 5.51), t (47) = 0.104, p  = 0.918.

What are the good practices for videoconferencing-assisted online flipped classrooms, as perceived by students and/or teaching staff?

The analyses of the participants’ comments identified the following seven good practices for videoconferencing-assisted online flipped classrooms.

Remind participants to mute their microphones when not speaking to eliminate undesirable background noise . According to Gazzillo ( 2018 ), muting participants’ microphones allows the speaker to have center stage while eliminating the distraction of audio feedback. As one teaching staff member said, .

It’s a good practice at the beginning to mute all of the participants by selecting the “Mute All” button at the bottom of the participants panel. This will eliminate all background noise (e.g., television sounds, audio feedback). I will then ask the participants to turn their audio back on if they wish to talk

In terms of Zoom functionality, by pressing and holding the “space bar” allows the participants to temporarily switch on their microphone. We also ask the participants to install an AI-enabled application called “Krisp” to minimize the background noise of the participants.

Remind participants before the online “in-class” session begins to switch on their webcams . Webcams show a person’s face to other people on the video call, which can help to increase online social presence among classmates (Conrad and Donaldson 2011 ). Online social presence is positively correlated with student satisfaction and student perceived learning (Richardson et al. 2017 ). The participants also strongly prefer to see a face during instruction as it is perceived as more educational (Kizilcec et al. 2014 ). Students’ facial expressions are also a valuable source of feedback for the instructor to know whether the students could understand the subject matter (Sathik and Jonathan 2013 ). An instructor can use students’ facial expressions to determine whether to speed up, or slow down, or provide further elaborations. Feedback from the teaching staff included the following comments.

It is important to ask students to turn on their cameras. Students will be more focused and interactive and teaching will be better when teachers can see students’ responses.

As an instructor, I do not feel as if I’m talking to a wall when I can see some actual faces. Students also feel they are talking to someone rather than to an empty black screen. But it’s important to inform the students in advance to switch on their webcams so that they can do their hair properly or put on makeup beforehand—this was what some students actually told me!

During teaching, seeing your students' faces will give you another form of feedback. For example, when they look confused or nod their heads, it allows me to fine-tune the delivery of the content. These reactions give me visual feedback on whether I need further explanations or examples to elaborate on the topic.

Feedback from the students included the following comments.

Showing our faces is really helpful as we can see our classmates’ faces and remember them. Also, it makes the class more alive because we can see their expressions. Showing our faces is very helpful! It can make me feel like I’m in a real class! I enjoy the feeling of having a class with my classmates.

Turning on the camera helps us be more attentive in the online class.

To avoid showing any undesirable background objects (e.g., a messy bedroom) during the video meeting, participants can choose to replace their actual background with a virtual background. The participants can easily do this using the Zoom virtual background feature.

Manage the transition to the online flipped classroom approach for students . Not every student will be familiar with the videoconferencing app or the flipped classroom approach. Therefore, to promote student buy-in of this new pedagogical approach, it is important for the staff to directly address two main issues: (a) the structure and activities of the online flipped course, and (b) the functions of the video conferencing app. Feedback from the students included the following comments.

If teachers would like to use some functions in Zoom, they need to first help students get familiar with it. A brief introduction to Zoom at the beginning of the class is helpful.

First, I informed the students that these two courses would have two components: a pre-class session and an online “in-class” session. This helped students understand the flipped approach better. Next, my teaching assistant and I conducted a short introduction to using Zoom online before the class began. This helped students get familiar with the features we would be using in Zoom.

Constant fine-tuning is also a key element in managing the transition to the online flipped classroom. Asking the students what works and what doesn’t have become our practice every after the lesson. These comments allow us to rethink and re-plan for the next online synchronous session.

Feedback from the teaching staff included the following comments.

Having a technical-related orientation session before the actual class starts helps a lot for students who are not familiar with the videoconferencing tool.

Instructors should use dual monitors to simulate, as close as possible, the look and feel of a face-to-face class—one monitor to view all the participants in “gallery view,” and the other to view the presentation material . It is very useful for instructors and teaching assistants to use the dual-monitor display function, which allows the video layout and screen share content to be presented on two separate monitors. One monitor can be used to view the participants (up to 49) in “gallery view,” and the other to display the presentation materials. In the “gallery view,” the instructor can see thumbnail displays of all of the participants in a grid pattern that expands and contracts automatically as participants join and leave the meeting (Zoom Video Communications 2019 ). The use of a dual monitor feature is also useful for PowerPoint presentations and hiding notes from the participants. Feedback from the teaching staff included:

During the preparation for this course, we would like to simulate, as close as possible, the look and feel of a face-to-face class. This thinking brought us to the dual monitor layout for our Zoom sessions. The first monitor is for the teaching assistant; in this case, it acts as a co-host for the Zoom session. The teaching assistant extends the computer screen to a monitor to show the participants’ faces or the “gallery view.” This monitor acts as a “classroom” in the traditional face-to-face class. During the session, this first monitor also serves as a tool for classroom management. This view is where the “chat” and “raise hand” functions can be seen. The second monitor is where the instructor places the presentation materials. This view acts as the projector in the traditional face-to-face class. Occasionally, we added a third screen, which is an iPad to do real-time annotation. This iPad can is a replacement of the conventional “whiteboard” in a face-to-face class.

Activate and evaluate students’ pre-class learning with a short review. At the beginning of the online “in-class” sessions, instructors should use short formative assessment methods (e.g., a quiz) to activate and evaluate students’ understanding of the pre-class activities. The activation of prior learning enhances student learning because it is the foundation for the new material presented in the classroom (Merrill 2002 ). Indeed, recent meta-analyses have suggested that flipped learning is more effective when formative assessments (e.g., quizzes or reviews) are used before and/or during class time (e.g., Hew and Lo 2018 ; Låg and Sæle 2019 ; Lo et al. 2017 ; van Alten et al. 2019 ). Students in this study reported positive benefits of using short formative assessments such as reviews or quizzes. Examples of student feedback include the following comments.

I find the reviews at the beginning of the “in-class” sessions very helpful! It’s good to start from something we are familiar with, and then go to the new materials. The reviewing of pre-class work is great because we can know what points we do not understand well and how we can improve.

The reviews helped me understand the issue more deeply. I could find out what my misunderstandings of the content are.

I find the teachers’ explanation and review of the pre-class work helpful.

Use an MIM app on mobile phones to foster quicker online response times and to communicate with students during their online breakout sessions . Although students can ask questions via discussion forums or email, the asynchronicity of these apps creates a time lag between postings and replies which can discourage students from communicating with each other (Hew et al. 2018 ). In contrast, MIM apps such as WhatsApp and WeChat allow users to engage in quasi synchronous communications on their mobile phones. When communication needs are urgent, many students may only have their phones available. As soon as an MIM message is sent, a notification automatically shows up on the user’s phone screen, which encourages timely response (Hew et al. 2018 ; Rosenfeld et al. 2018 ). In addition, MIM is more popular than voice calls, emails, and even face-to-face communication among young people (Lenhart et al. 2010 ). As of March 2019, more than 41 million mobile instant messages are sent every minute (Clement 2019 ). Student feedback on using MIM in classrooms included the following comments.

I like using MIM such as WeChat because it allows us to communicate with other people immediately.

I enjoy using WeChat to ask questions and get immediate feedback from my classmates and teaching staff.

Use a variety of presentation media as well as a variety of activities to sustain student interest . No matter how interested a learner is in the topic of a presentation or discussion, that interest will wane in the face of monotony (Driscoll 2000 ). Therefore, it is recommended that instructors sustain student interest by varying the use of presentation media. Instructors, for example, can alternate the use of PowerPoint slides with digital handwriting on an iPad. The instructor in this study made the following comments.

I find continual use of PowerPoint slides to be boring. It’s always the same style: a bullet list of information with some animations or pictures. I find it useful to sustain my students’ attention by writing on an iPad.

Comments from the students were also positive.

I find the instructor writing on an iPad helps to focus my attention better than PowerPoint slides.

Writing on the iPad is like writing on a whiteboard in real face-to-face classrooms. It helps me develop a better understanding of the topic.

Digital writing on an iPad can help learners see the progressive development of the subject content (Hulls 2005 ), and follow the instructor’s cognitive process better than pre-prepared PowerPoint presentations (Lee and Lim 2013 ). Writing on an iPad can also enable an instructor to immediately adjust his or her instruction in response to the students’ needs. Using digital writing can significantly improve students’ understanding of conceptual knowledge when compared to PowerPoint-based presentation lectures (Lee and Lim 2013 ).

In addition to varying the presentation media, an instructor should also use different activities, including guest speakers, during the online class session. Feedback from the students included the following comments.

The use of different functions in Zoom, such as breakout rooms for group activities, voting, and raising hands, is useful because they help us to be involved. It helps increase the learner-learner and learner-instructor interaction, which may be lacking in a fully online class.

During the three-hour online class, we had not only the teacher’s explanations, but also had a guest speaker and online group discussions via breakout rooms, which made the class engaging.

In this study, the instructor invited a United Kingdom-based practicing instructional designer as a guest speaker in the two online flipped courses to talk about her experience in developing e-learning courses and engaging adult learners. Guest speakers enhance students’ educational experience by giving them real-world knowledge (Metrejean and Zarzeski 2001 ). Guest speakers can offer students a different point of view, one that students may better understand. Guest speakers can also alleviate the monotony of listening to a single instructor.

Amidst the burgeoning use of online learning during the unpredictable present, this study evaluates the efficacy of a videoconferencing - supported fully online flipped classroom. It compares student outcomes in four higher education classes: conventional flipped Course 1 versus online flipped Course 1, and conventional flipped Course 2 versus online flipped Course 2. Overall, this study makes three contributions to the literature on flipped classrooms. First, it provides a thick description of the development of the conventional flipped classroom approach based on the 5E framework, and the transformation of the conventional flipped classroom into a fully online flipped classroom. A thick description of the development of the flipped classrooms is provided to encourage replication by other researchers and practitioners. Second, our findings reveal that the online flipped classroom approach can be as effective as the conventional flipped classroom. Third, we identify seven good practices for using videoconferencing to support online flipped classrooms. This set of good practices can provide useful guidelines for other instructors who might be interested in implementing an online flipped approach.

One potential limitation of our study is that it was relatively short in duration (8 weeks). However, according to Fraenkel et al. ( 2014 ), some researchers do collect data within a fairly short time. A short-term data collection period enables researchers to collect and analyze data to see if an intervention is workable before committing to a longer study (Creswell 2015 ). We therefore urge future researchers to examine the use of videoconferencing - supported online flipped classrooms over a longer period of time, such as one year or more, to verify the results of this study.

Another interesting area for future work will be examining how instructors can support learners’ self-regulation during online flipped classroom (Cheng et al. 2019 ), as well as what strategies can best motivate students to complete the pre-class work.

Availability of data and materials

The anonymized datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Akar, E. (2005). Effectiveness of 5e learning cycle model on students’ understanding of acid-base concepts . MS Thesis, Middle East Technical University, Ankara.

Archibald, M. M., Ambagtsheer, R. C., Casey, M. G., & Lawless, M. (2019). Using Zoom videoconferencing for qualitative data collection: perceptions and experiences of researchers and participants. Int J Qual Methods, 18, 1–8. https://doi.org/10.1177/1609406919874596 .

Article   Google Scholar  

Bates S, Galloway R. The inverted classroom in a large enrolment introductory physics course: A case study. https://www.heacademy.ac.uk/assets/documents/stem-conference/PhysicalSciences/Simon_Bates_Ross_Galloway.pdf (2012)

Bishop, J. L., & Verleger, M. A. (2013). The flipped classroom: A survey of the research. 120 Am Soc Eng Educ Annu Conf Expo, 30, 1–18.

Google Scholar  

Boddy, N., Watson, K., & Aubusson, P. (2003). A trial of the five e’s: a referent model for constructivist teaching and learning. Research in Science Education , 33 , 27–42. https://doi.org/10.1023/A:1023606425452 .

Bond, M. (2020). Facilitating student engagement through the flipped learning approach in K-12: A systematic review. Computers & Education . https://doi.org/10.1016/j.compedu.2020.103819

Bybee, R. W., et al. (2006). The BSCS 5E instructional model: origins and effectiveness. Off Sci Educ Natl Inst Health, 2006, 1–80.

Cheng, L., Ritzhaupt, A. D., & Antonenko, P. (2019). Effects of the flipped classroom instructional strategy on students’ learning outcomes: a meta-analysis. Etr&D, 67 (4), 793–824. https://doi.org/10.1007/s11423-018-9633-7

Clement J. Global number of mobile messaging users 2018–2022. Statista. https://www.statista.com/statistics/483255/number-of-mobile-messaging-usersworldwide/ (2019)

Conrad, R. M., & Donaldson, J. A. (2011). Engaging the online learner: activities and resources for creative instruction . San Francisco, CA: Jossey-Bass.

Creswell, J. W. (2015). Educational research: planning, conducting, and evaluating quantitative and qualitative research . Boston, MA: Pearson Education.

Deslauriers, L., et al. (2019). Measuring actual learning versus feeling of learning in response to being actively engaged in the classroom. Proceedings of the National Academy of Sciences, 116 (39), 19251–19257. https://doi.org/10.1073/pnas.1821936116

Driscoll, M. P. (2000). Psychology of learning for instruction (2nd ed.). Boston: Allyn and Bacon.

Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2014). How to design and evaluate research in education . New York: McGraw-Hill.

Gazzillo L. Tech tip: muting participants in Zoom. Yale Library IT News . https://campuspress.yale.edu/libraryitnews/2018/01/23/tech-tip-muting-participants-in-zoom/ (2018)

Gierdowski DC. 2019 study of undergraduate students and information technology. EDUCAUSE Center for Analysis and Research. https://library.educause.edu/resources/2019/10/2019-study-of-undergraduate-students-and-information-technology (2019)

Hew, K. F., & Lo, C. K. (2018). Flipped classroom improves student learning in health professions education: a meta-analysis. BMC Medical Education . https://doi.org/10.1186/s12909-018-1144-z

Hew, K., et al. (2018). Examining a WeChat-supported 5E-flipped classroom pedagogical approach. Int J Serv Stand, 12, 224–242.

Hodges C, Moore S, Lockee B, Trust T, Bond, A. The difference between emergency remote teaching and online learning. Educause Review. https://er.educause.edu/articles/2020/3/the-difference-between-emergency-remote-teaching-and-online-learning (2020)

Hulls CCW. Using a tablet PC for classroom instruction. In Proceedings of the 35th Annual Conference of Frontiers in Education, Indianapolis, Indiana, 19–22 October

Ivankova, N. V., Creswell, J. W., & Stick, S. L. (2006). Using mixed-methods sequential explanatory design: From theory to practice. Field Methods, 18 (1), 3–20.

Johnston N. Google Hangouts Meet vs. Zoom: Which conferencing tool is better for you? https://www.androidcentral.com/google-hangouts-meet-vs-zoom (2020)

Kim J. Zoom is hot in higher ed. Inside Higher Ed . Retrieved from https://www.insidehighered.com/blogs/technology-and-learning/zoom-hot-higher-ed (2017)

Kizilcec RF, Papadopoulos K, Sritanyaratana L. Showing face in video instruction: Effects on information retention, visual attention, and affect. In Proceedings of SIGCHI Conference on Human Factors in Computing Systems (pp. 2095–2102). New York, NY: Association for Computing Machinery (2014)

Låg, T., & Sæle, R. G. (2019). Does the flipped classroom improve student learning and satisfaction? A systematic review and meta-analysis. AERA Open, 5 (3), 1–17.

Lederman D. Will shift to remote teaching be boon or bane for online learning? Inside Higher Ed . Retrieved from https://www.insidehighered.com/digital-learning/article/2020/03/18/most-teaching-going-remote-will-help-or-hurt-online-learning (2014)

Lee, H. W., & Lim, K. Y. (2013). Does digital handwriting of instructors using the iPad enhance student learning? Asia-Pacific Educ Res, 22 (3), 241–245.

Lenhart A, et al. Social media & mobile internet use among teens and young adults. Pew Internet and American Life Project, 2010 (2010).

Lo, C. K. (2017). Toward a flipped classroom instructional model for history education: a call for research. Int J Cult Hist, 3 (1), 36–43.

Lo, C. K., & Hew, K. F. (2019). The impact of flipped classrooms on student achievement in engineering education: a meta-analysis of 10 years of research. Journal of Engineering Education, 108 (4), 523–546.

Lo, C. K., Hew, K. F., & Chen, G. (2017). Toward a set of design principles for mathematics flipped classrooms: a synthesis of research in mathematics education. Educ Res Rev, 22, 50–73. https://doi.org/10.1016/j.edurev.2017.08.002

Merrill, M. D. (2002). First principles of instruction. Educ Technol Res Dev, 50 (3), 43–59.

Metrejean, C., & Zarzeski, M. (2001). Bring the world to the classroom. J Account, 19 (3), 73–76.

Mullins, M. H. (2017). Actively teaching research methods with a process oriented guided inquiry learning approach. J Teach Soc Work, 37 (4), 309–332.

Pomerantz J, Brooks DC. ECAR study of faculty and information technology. Research report . Louisville, CO: ECAR. https://library.educause.edu/-/media/files/library/2017/10/facultyitstudy2017.pdf (2017)

Richardson, J. C., Maeda, Y., Lv, J., & Caskurlu, S. (2017). Social presence in relation to students’ satisfaction and learning in the online environment: a meta-analysis. Computers in Human Behavior, 71, 402–417. https://doi.org/10.1016/j.chb.2017.02.001

Rosenfeld, A., Sina, S., Sarne, D., Avidov, O., & Kraus, S. (2018). WhatsApp usage patterns and prediction of demographic characteristics without access to message content. Demographic Research , 39 (22), 647–670. https://doi.org/10.4054/DemRes.2018.39.22 .

Sathik, M., & Jonathan, S. G. (2013). Effect of facial expressions on student’s comprehension recognition in virtual educational environments. SpringerPlus, 2, 455. https://doi.org/10.1186/2193-1801-2-455

Shi, Y., Ma, Y., MacLeod, J., & Yang, H. H. (2019). College students’ cognitive learning outcomes in flipped classroom instruction: a meta-analysis of the empirical literature. J Comput Educ . https://doi.org/10.1007/s40692-019-00142-8

Stohr, C., Demaziere, C., & Adawi, T. (2020). The polarizing effect of the online flipped classroom. Computers & Education . https://doi.org/10.1016/j.compedu.2019.103789

Strauss, A., & Corbin, J. (1990). Basics of qualitative research: grounded theory procedures and techniques . Newbury Park: Sage Publications.

Sutterlin J. Learning is social with Zoom videoconferencing in your classroom. eLearn magazine . https://elearnmag.acm.org/featured.cfm?aid=3236697 (2018)

UNESCO. (n.d.). COVID-19 educational disruption and response. https://en.unesco.org/themes/education-emergencies/coronavirus-school-closures

van Alten, D. C. D., Phielix, C., Janssen, J., & Kester, L. (2019). Effects of flipping the classroom on learning outcomes and satisfaction: a meta-analysis. Educ Res Rev, 28, 100281. https://doi.org/10.1016/j.edurev.2019.05.003

Xiu, Y., & Thompson, P. (2020). Flipped university class: a study of motivation and learning. J Inform Technol Educ, 19, 41–63.

Zoom Video Communications Inc. Displaying participants in gallery view. https://support.zoom.us/hc/en-us/articles/360000005883-Displaying-participants-in-gallery-view (2019)

Download references

Acknowledgements

Not applicable.

Author information

Authors and affiliations.

Faculty of Education, The University of Hong Kong, Pok Fu Lam, Hong Kong SAR

Khe Foon Hew, Chengyuan Jia, Donn Emmanuel Gonda & Shurui Bai

You can also search for this author in PubMed   Google Scholar

Contributions

KFH conceptualized the study, analysed the data, and wrote the initial draft. CJ analysed the data, and revised the draft. DEG provided critical feedback and edited the manuscript. SB provided Zoom support and critical feedback. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Khe Foon Hew .

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Hew, K.F., Jia, C., Gonda, D.E. et al. Transitioning to the “new normal” of learning in unpredictable times: pedagogical practices and learning performance in fully online flipped classrooms. Int J Educ Technol High Educ 17 , 57 (2020). https://doi.org/10.1186/s41239-020-00234-x

Download citation

Received : 24 June 2020

Accepted : 28 September 2020

Published : 21 December 2020

DOI : https://doi.org/10.1186/s41239-020-00234-x

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Online flipped classroom
• Flipped learning
• Good practices

Essay on Impact of Technology on Education

Students are often asked to write an essay on Impact of Technology on Education in their schools and colleges. And if you’re also looking for the same, we have created 100-word, 250-word, and 500-word essays on the topic.

Let’s take a look…

100 Words Essay on Impact of Technology on Education

Introduction.

Technology has greatly influenced education. It has changed the way we learn and teach, making education more accessible and engaging.

Interactive Learning

Technology has introduced interactive learning tools like smart boards and tablets. They make lessons more engaging and fun, helping students understand better.

Online Education

With the internet, learning is not limited to classrooms. Online courses, video lectures, and digital libraries have made education accessible to everyone, everywhere.

Improved Communication

Technology has improved communication between students and teachers. Emails, chats, and video calls make it easier to discuss and solve doubts.

250 Words Essay on Impact of Technology on Education

The advent of technology in education.

The advent of technology has revolutionized various sectors, with education being one of the most impacted. It has transformed traditional teaching methods, making learning more engaging, accessible, and efficient.

Enhancing Accessibility and Flexibility

Technology has democratized education, breaking down geographical barriers. Online learning platforms and digital libraries provide easy access to a vast range of resources. This flexibility allows students to learn at their own pace, fostering a self-driven learning environment.

Interactive Learning Experience

Technological tools like virtual reality, digital simulations, and gamified learning apps have made education more interactive. These tools cater to different learning styles, enhancing comprehension, and retention of knowledge.

Collaborative Learning

Tools like cloud-based applications and social media platforms promote collaborative learning. They enable students to work together on projects, share ideas, and gain diverse perspectives, fostering critical thinking and problem-solving skills.

Challenges Posed by Technology

Despite its benefits, technology also poses challenges. The digital divide, where some students lack access to technology, can exacerbate educational inequalities. Additionally, over-reliance on technology might hinder the development of interpersonal skills and critical thinking.

500 Words Essay on Impact of Technology on Education

The advent of technology has dramatically transformed various sectors globally, and education is no exception. Over the years, technology has played a pivotal role in reshaping educational landscapes, creating new opportunities for both students and educators. This essay explores the impact of technology on education, focusing on its benefits, challenges, and future implications.

The Benefits of Technology in Education

One of the most significant benefits of technology in education is the democratization of knowledge. Digital platforms such as online libraries, e-books, and educational websites have made information accessible to anyone with an internet connection, breaking down geographical and socio-economic barriers.

The Challenges of Technology in Education

Despite the numerous benefits, technology’s integration into education is not without challenges. One of the primary issues is the digital divide, which refers to the disparity in access to technology between different socioeconomic groups. This divide exacerbates educational inequalities, as students who lack access to digital resources are disadvantaged.

Another challenge is the potential for distraction. With the proliferation of digital devices, students may be tempted to use them for non-educational purposes, which can hinder their academic progress. Additionally, the over-reliance on technology may diminish critical thinking and problem-solving skills, as students may resort to quick online solutions rather than engaging in deep, thoughtful analysis.

Future Implications

However, as technology continues to evolve, it is crucial to address its challenges. Policymakers and educators must work together to bridge the digital divide, ensuring that all students can benefit from technological advancements. Additionally, digital literacy programs should be implemented to teach students how to use technology responsibly and effectively.

In conclusion, technology has had a profound impact on education, offering numerous benefits but also presenting significant challenges. As we navigate the digital age, it is essential to harness technology’s potential to enhance education while mitigating its drawbacks. This balanced approach will ensure that technology serves as a powerful tool in shaping a more equitable, engaging, and efficient educational landscape.

That’s it! I hope the essay helped you.

Apart from these, you can look at all the essays by clicking here .

Happy studying!

Leave a Reply Cancel reply

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Springer Nature - PMC COVID-19 Collection

The “new normal” in education

José augusto pacheco.

Research Centre on Education (CIEd), Institute of Education, University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal

Effects rippling from the Covid 19 emergency include changes in the personal, social, and economic spheres. Are there continuities as well? Based on a literature review (primarily of UNESCO and OECD publications and their critics), the following question is posed: How can one resist the slide into passive technologization and seize the possibility of achieving a responsive, ethical, humane, and international-transformational approach to education? Technologization, while an ongoing and evidently ever-intensifying tendency, is not without its critics, especially those associated with the humanistic tradition in education. This is more apparent now that curriculum is being conceived as a complicated conversation. In a complex and unequal world, the well-being of students requires diverse and even conflicting visions of the world, its problems, and the forms of knowledge we study to address them.

From the past, we might find our way to a future unforeclosed by the present (Pinar 2019 , p. 12)

Texts regarding this pandemic’s consequences are appearing at an accelerating pace, with constant coverage by news outlets, as well as philosophical, historical, and sociological reflections by public intellectuals worldwide. Ripples from the current emergency have spread into the personal, social, and economic spheres. But are there continuities as well? Is the pandemic creating a “new normal” in education or simply accenting what has already become normal—an accelerating tendency toward technologization? This tendency presents an important challenge for education, requiring a critical vision of post-Covid-19 curriculum. One must pose an additional question: How can one resist the slide into passive technologization and seize the possibility of achieving a responsive, ethical, humane, and international-transformational approach to education?

The ongoing present

Unpredicted except through science fiction, movie scripts, and novels, the Covid-19 pandemic has changed everyday life, caused wide-scale illness and death, and provoked preventive measures like social distancing, confinement, and school closures. It has struck disproportionately at those who provide essential services and those unable to work remotely; in an already precarious marketplace, unemployment is having terrible consequences. The pandemic is now the chief sign of both globalization and deglobalization, as nations close borders and airports sit empty. There are no departures, no delays. Everything has changed, and no one was prepared. The pandemic has disrupted the flow of time and unraveled what was normal. It is the emergence of an event (think of Badiou 2009 ) that restarts time, creates radical ruptures and imbalances, and brings about a contingency that becomes a new necessity (Žižek 2020 ). Such events question the ongoing present.

The pandemic has reshuffled our needs, which are now based on a new order. Whether of short or medium duration, will it end in a return to the “normal” or move us into an unknown future? Žižek contends that “there is no return to normal, the new ‘normal’ will have to be constructed on the ruins of our old lives, or we will find ourselves in a new barbarism whose signs are already clearly discernible” (Žižek 2020 , p. 3).

Despite public health measures, Gil ( 2020 ) observes that the pandemic has so far generated no physical or spiritual upheaval and no universal awareness of the need to change how we live. Techno-capitalism continues to work, though perhaps not as before. Online sales increase and professionals work from home, thereby creating new digital subjectivities and economies. We will not escape the pull of self-preservation, self-regeneration, and the metamorphosis of capitalism, which will continue its permanent revolution (Wells 2020 ). In adapting subjectivities to the recent demands of digital capitalism, the pandemic can catapult us into an even more thoroughly digitalized space, a trend that artificial intelligence will accelerate. These new subjectivities will exhibit increased capacities for voluntary obedience and programmable functioning abilities, leading to a “new normal” benefiting those who are savvy in software-structured social relationships.

The Covid-19 pandemic has submerged us all in the tsunami-like economies of the Cloud. There is an intensification of the allegro rhythm of adaptation to the Internet of Things (Davies, Beauchamp, Davies, and Price 2019 ). For Latour ( 2020 ), the pandemic has become internalized as an ongoing state of emergency preparing us for the next crisis—climate change—for which we will see just how (un)prepared we are. Along with inequality, climate is one of the most pressing issues of our time (OECD 2019a , 2019b ) and therefore its representation in the curriculum is of public, not just private, interest.

Education both reflects what is now and anticipates what is next, recoding private and public responses to crises. Žižek ( 2020 , p. 117) suggests in this regard that “values and beliefs should not be simply ignored: they play an important role and should be treated as a specific mode of assemblage”. As such, education is (post)human and has its (over)determination by beliefs and values, themselves encoded in technology.

Will the pandemic detoxify our addiction to technology, or will it cement that addiction? Pinar ( 2019 , pp. 14–15) suggests that “this idea—that technological advance can overcome cultural, economic, educational crises—has faded into the background. It is our assumption. Our faith prompts the purchase of new technology and assures we can cure climate change”. While waiting for technology to rescue us, we might also remember to look at ourselves. In this way, the pandemic could be a starting point for a more sustainable environment. An intelligent response to climate change, reactivating the humanistic tradition in education, would reaffirm the right to such an education as a global common good (UNESCO 2015a , p. 10):

This approach emphasizes the inclusion of people who are often subject to discrimination – women and girls, indigenous people, persons with disabilities, migrants, the elderly and people living in countries affected by conflict. It requires an open and flexible approach to learning that is both lifelong and life-wide: an approach that provides the opportunity for all to realize their potential for a sustainable future and a life of dignity”.

Pinar ( 2004 , 2009 , 2019 ) concevies of curriculum as a complicated conversation. Central to that complicated conversation is climate change, which drives the need for education for sustainable development and the grooming of new global citizens with sustainable lifestyles and exemplary environmental custodianship (Marope 2017 ).

The new normal

The pandemic ushers in a “new” normal, in which digitization enforces ways of working and learning. It forces education further into technologization, a development already well underway, fueled by commercialism and the reigning market ideology. Daniel ( 2020 , p. 1) notes that “many institutions had plans to make greater use of technology in teaching, but the outbreak of Covid-19 has meant that changes intended to occur over months or years had to be implemented in a few days”.

Is this “new normal” really new or is it a reiteration of the old?

Digital technologies are the visible face of the immediate changes taking place in society—the commercial society—and schools. The immediate solution to the closure of schools is distance learning, with platforms proliferating and knowledge demoted to information to be exchanged (Koopman 2019 ), like a product, a phenomenon predicted decades ago by Lyotard ( 1984 , pp. 4-5):

Knowledge is and will be produced in order to be sold, it is and will be consumed in order to be valued in a new production: in both cases, the goal is exchange. Knowledge ceases to be an end in itself, it loses its use-value.

Digital technologies and economic rationality based on performance are significant determinants of the commercialization of learning. Moving from physical face-to-face presence to virtual contact (synchronous and asynchronous), the learning space becomes disembodied, virtual not actual, impacting both student learning and the organization of schools, which are no longer buildings but websites. Such change is not only coterminous with the pandemic, as the Education 2030 Agenda (UNESCO 2015b ) testified; preceding that was the Delors Report (Delors 1996 ), which recoded education as lifelong learning that included learning to know, learning to do, learning to be, and learning to live together.

Transnational organizations have specified competences for the 21st century and, in the process, have defined disciplinary and interdisciplinary knowledge that encourages global citizenship, through “the supra curriculum at the global, regional, or international comparative level” (Marope 2017 , p. 10). According to UNESCO ( 2017 ):

While the world may be increasingly interconnected, human rights violations, inequality and poverty still threaten peace and sustainability. Global Citizenship Education (GCED) is UNESCO’s response to these challenges. It works by empowering learners of all ages to understand that these are global, not local issues and to become active promoters of more peaceful, tolerant, inclusive, secure and sustainable societies.

These transnational initiatives have not only acknowledged traditional school subjects but have also shifted the curriculum toward timely topics dedicated to understanding the emergencies of the day (Spiller 2017 ). However, for the OECD ( 2019a ), the “new normal” accentuates two ideas: competence-based education, which includes the knowledges identified in the Delors Report , and a new learning framework structured by digital technologies. The Covid-19 pandemic does not change this logic. Indeed, the interdisciplinary skills framework, content and standardized testing associated with the Programme for International Student Assessment of the OECD has become the most powerful tool for prescribing the curriculum. Educationally, “the universal homogenous ‘state’ exists already. Globalization of standardized testing—the most prominent instance of threatening to restructure schools into technological sites of political socialization, conditioning children for compliance to a universal homogeneous state of mind” (Pinar 2019 , p. 2).

In addition to cognitive and practical skills, this “homogenous state of mind” rests on so-called social and emotional skills in the service of learning to live together, affirming global citizenship, and presumably returning agency to students and teachers (OECD 2019a ). According to Marope ( 2017 , p. 22), “this calls for higher flexibility in curriculum development, and for the need to leave space for curricula interpretation, contextualization, and creativity at the micro level of teachers and classrooms”. Heterogeneity is thus enlisted in the service of both economic homogeneity and disciplinary knowledge. Disciplinary knowledge is presented as universal and endowed with social, moral, and cognitive authority. Operational and effective knowledge becomes central, due to the influence of financial lobbies, thereby ensuring that the logic of the market is brought into the practices of schools. As Pestre ( 2013 , p. 21) observed, “the nature of this knowledge is new: what matters is that it makes hic et nunc the action, its effect and not its understanding”. Its functionality follows (presumably) data and evidence-based management.

A new language is thus imposed on education and the curriculum. Such enforced installation of performative language and Big Data lead to effective and profitable operations in a vast market concerned with competence in operational skills (Lyotard 1984 ). This “new normal” curriculum is said to be more horizontal and less hierarchical and radically polycentric with problem-solving produced through social networks, NGOs, transnational organizations, and think tanks (Pestre 2013 ; Williamson 2013 , 2017 ). Untouched by the pandemic, the “new (old) normal” remains based on disciplinary knowledge and enmeshed in the discourse of standards and accountability in education.

Such enforced commercialism reflects and reinforces economic globalization. Pinar ( 2011 , p. 30) worries that “the globalization of instrumental rationality in education threatens the very existence of education itself”. In his theory, commercialism and the technical instrumentality by which homogenization advances erase education as an embodied experience and the curriculum as a humanistic project. It is a time in which the humanities are devalued as well, as acknowledged by Pinar ( 2019 , p. 19): “In the United States [and in the world] not only does economics replace education—STEM replace the liberal arts as central to the curriculum—there are even politicians who attack the liberal arts as subversive and irrelevant…it can be more precisely characterized as reckless rhetoric of a know-nothing populism”. Replacing in-person dialogical encounters and the educational cultivation of the person (via Bildung and currere ), digital technologies are creating uniformity of learning spaces, in spite of their individualistic tendencies. Of course, education occurs outside schools—and on occasion in schools—but this causal displacement of the centrality of the school implies a devaluation of academic knowledge in the name of diversification of learning spaces.

In society, education, and specifically in the curriculum, the pandemic has brought nothing new but rather has accelerated already existing trends that can be summarized as technologization. Those who can work “remotely” exercise their privilege, since they can exploit an increasingly digital society. They themselves are changed in the process, as their own subjectivities are digitalized, thus predisposing them to a “curriculum of things” (a term coined by Laist ( 2016 ) to describe an object-oriented pedagogical approach), which is organized not around knowledge but information (Koopman 2019 ; Couldry and Mejias 2019 ). This (old) “new normal” was advanced by the OECD, among other international organizations, thus precipitating what some see as “a dynamic and transformative articulation of collective expectations of the purpose, quality, and relevance of education and learning to holistic, inclusive, just, peaceful, and sustainable development, and to the well-being and fulfilment of current and future generations” (Marope 2017 , p. 13). Covid-19, illiberal democracy, economic nationalism, and inaction on climate change, all upend this promise.

Understanding the psychological and cultural complexity of the curriculum is crucial. Without appreciating the infinity of responses students have to what they study, one cannot engage in the complicated conversation that is the curriculum. There must be an affirmation of “not only the individualism of a person’s experience but [of what is] underlining the significance of a person’s response to a course of study that has been designed to ignore individuality in order to buttress nation, religion, ethnicity, family, and gender” (Grumet 2017 , p. 77). Rather than promoting neuroscience as the answer to the problems of curriculum and pedagogy, it is long-past time for rethinking curriculum development and addressing the canonical curriculum question: What knowledge is of most worth from a humanistic perspective that is structured by complicated conversation (UNESCO 2015a ; Pinar 2004 , 2019 )? It promotes respect for diversity and rejection of all forms of (cultural) hegemony, stereotypes, and biases (Pacheco 2009 , 2017 ).

Revisiting the curriculum in the Covid-19 era then expresses the fallacy of the “new normal” but also represents a particular opportunity to promote a different path forward.

Looking to the post-Covid-19 curriculum

Based on the notion of curriculum as a complicated conversation, as proposed by Pinar ( 2004 ), the post-Covid-19 curriculum can seize the possibility of achieving a responsive, ethical, humane education, one which requires a humanistic and internationally aware reconceptualization of curriculum.

While beliefs and values are anchored in social and individual practices (Pinar 2019 , p. 15), education extracts them for critique and reconsideration. For example, freedom and tolerance are not neutral but normative practices, however ideology-free policymakers imagine them to be.

That same sleight-of-hand—value neutrality in the service of a certain normativity—is evident in a digital concept of society as a relationship between humans and non-humans (or posthumans), a relationship not only mediated by but encapsulated within technology: machines interfacing with other machines. This is not merely a technological change, as if it were a quarantined domain severed from society. Technologization is a totalizing digitalization of human experience that includes the structures of society. It is less social than economic, with social bonds now recoded as financial transactions sutured by software. Now that subjectivity is digitalized, the human face has become an exclusively economic one that fabricates the fantasy of rational and free agents—always self-interested—operating in supposedly free markets. Oddly enough, there is no place for a vision of humanistic and internationally aware change. The technological dimension of curriculum is assumed to be the primary area of change, which has been deeply and totally imposed by global standards. The worldwide pandemic supports arguments for imposing forms of control (Žižek 2020 ), including the geolocation of infected people and the suspension—in a state of exception—of civil liberties.

By destroying democracy, the technology of control leads to totalitarianism and barbarism, ending tolerance, difference, and diversity. Remembrance and memory are needed so that historical fascisms (Eley 2020 ) are not repeated, albeit in new disguises (Adorno 2011 ). Technologized education enhances efficiency and ensures uniformity, while presuming objectivity to the detriment of human reflection and singularity. It imposes the running data of the Curriculum of Things and eschews intellectual endeavor, critical attitude, and self-reflexivity.

For those who advocate the primacy of technology and the so-called “free market”, the pandemic represents opportunities not only for profit but also for confirmation of the pervasiveness of human error and proof of the efficiency of the non-human, i.e., the inhuman technology. What may possibly protect children from this inhumanity and their commodification, as human capital, is a humane or humanistic education that contradicts their commodification.

The decontextualized technical vocabulary in use in a market society produces an undifferentiated image in which people are blinded to nuance, distinction, and subtlety. For Pestre, concepts associated with efficiency convey the primacy of economic activity to the exclusion, for instance, of ethics, since those concepts devalue historic (if unrealized) commitments to equality and fraternity by instead emphasizing economic freedom and the autonomy of self-interested individuals. Constructing education as solely economic and technological constitutes a movement toward total efficiency through the installation of uniformity of behavior, devaluing diversity and human creativity.

Erased from the screen is any image of public education as a space of freedom, or as Macdonald ( 1995 , p. 38) holds, any image or concept of “the dignity and integrity of each human”. Instead, what we face is the post-human and the undisputed reign of instrumental reality, where the ends justify the means and human realization is reduced to the consumption of goods and experiences. As Pinar ( 2019 , p. 7) observes: “In the private sphere…. freedom is recast as a choice of consumer goods; in the public sphere, it converts to control and the demand that freedom flourish, so that whatever is profitable can be pursued”. Such “negative” freedom—freedom from constraint—ignores “positive” freedom, which requires us to contemplate—in ethical and spiritual terms—what that freedom is for. To contemplate what freedom is for requires “critical and comprehensive knowledge” (Pestre 2013 , p. 39) not only instrumental and technical knowledge. The humanities and the arts would reoccupy the center of such a curriculum and not be related to its margins (Westbury 2008 ), acknowledging that what is studied within schools is a complicated conversation among those present—including oneself, one’s ancestors, and those yet to be born (Pinar 2004 ).

In an era of unconstrained technologization, the challenge facing the curriculum is coding and STEM (science, technology, engineering, and mathematics), with technology dislodging those subjects related to the human. This is not a classical curriculum (although it could be) but one focused on the emergencies of the moment–namely, climate change, the pandemic, mass migration, right-wing populism, and economic inequality. These timely topics, which in secondary school could be taught as short courses and at the elementary level as thematic units, would be informed by the traditional school subjects (yes, including STEM). Such a reorganization of the curriculum would allow students to see how academic knowledge enables them to understand what is happening to them and their parents in their own regions and globally. Such a cosmopolitan curriculum would prepare children to become citizens not only of their own nations but of the world. This citizenship would simultaneously be subjective and social, singular and universal (Marope 2020 ). Pinar ( 2019 , p. 5) reminds us that “the division between private and public was first blurred then erased by technology”:

No longer public, let alone sacred, morality becomes a matter of privately held values, sometimes monetized as commodities, statements of personal preference, often ornamental, sometimes self-servingly instrumental. Whatever their function, values were to be confined to the private sphere. The public sphere was no longer the civic square but rather, the marketplace, the site where one purchased whatever one valued.

New technological spaces are the universal center for (in)human values. The civic square is now Amazon, Alibaba, Twitter, WeChat, and other global online corporations. The facts of our human condition—a century-old phrase uncanny in its echoes today—can be studied in schools as an interdisciplinary complicated conversation about public issues that eclipse private ones (Pinar 2019 ), including social injustice, inequality, democracy, climate change, refugees, immigrants, and minority groups. Understood as a responsive, ethical, humane and transformational international educational approach, such a post-Covid-19 curriculum could be a “force for social equity, justice, cohesion, stability, and peace” (Marope 2017 , p. 32). “Unchosen” is certainly the adjective describing our obligations now, as we are surrounded by death and dying and threatened by privation or even starvation, as economies collapse and food-supply chains are broken. The pandemic may not mean deglobalization, but it surely accentuates it, as national borders are closed, international travel is suspended, and international trade is impacted by the accompanying economic crisis. On the other hand, economic globalization could return even stronger, as could the globalization of education systems. The “new normal” in education is the technological order—a passive technologization—and its expansion continues uncontested and even accelerated by the pandemic.

Two Greek concepts, kronos and kairos , allow a discussion of contrasts between the quantitative and the qualitative in education. Echoing the ancient notion of kronos are the technologically structured curriculum values of quantity and performance, which are always assessed by a standardized accountability system enforcing an “ideology of achievement”. “While kronos refers to chronological or sequential time, kairos refers to time that might require waiting patiently for a long time or immediate and rapid action; which course of action one chooses will depend on the particular situation” (Lahtinen 2009 , p. 252).

For Macdonald ( 1995 , p. 51), “the central ideology of the schools is the ideology of achievement …[It] is a quantitative ideology, for even to attempt to assess quality must be quantified under this ideology, and the educational process is perceived as a technically monitored quality control process”.

Self-evaluation subjectively internalizes what is useful and in conformity with the techno-economy and its so-called standards, increasingly enforcing technical (software) forms. If recoded as the Internet of Things, this remains a curriculum in allegiance with “order and control” (Doll 2013 , p. 314) School knowledge is reduced to an instrument for economic success, employing compulsory collaboration to ensure group think and conformity. Intertwined with the Internet of Things, technological subjectivity becomes embedded in software, redesigned for effectiveness, i.e., or use-value (as Lyotard predicted).

The Curriculum of Things dominates the Internet, which is simultaneously an object and a thing (see Heidegger 1967 , 1971 , 1977 ), a powerful “technological tool for the process of knowledge building” (Means 2008 , p. 137). Online learning occupies the subjective zone between the “curriculum-as-planned” and the “curriculum-as-lived” (Pinar 2019 , p. 23). The world of the curriculum-as-lived fades, as the screen shifts and children are enmeshed in an ocularcentric system of accountability and instrumentality.

In contrast to kronos , the Greek concept of kairos implies lived time or even slow time (Koepnick 2014 ), time that is “self-reflective” (Macdonald 1995 , p. 103) and autobiographical (Pinar 2009 , 2004), thus inspiring “curriculum improvisation” (Aoki 2011 , p. 375), while emphasizing “the plurality of subjectivities” (Grumet 2017 , p. 80). Kairos emphasizes singularity and acknowledges particularities; it is skeptical of similarities. For Shew ( 2013 , p. 48), “ kairos is that which opens an originary experience—of the divine, perhaps, but also of life or being. Thought as such, kairos as a formative happening—an opportune moment, crisis, circumstance, event—imposes its own sense of measure on time”. So conceived, curriculum can become a complicated conversation that occurs not in chronological time but in its own time. Such dialogue is not neutral, apolitical, or timeless. It focuses on the present and is intrinsically subjective, even in public space, as Pinar ( 2019 , p. 12) writes: “its site is subjectivity as one attunes oneself to what one is experiencing, yes to its immediacy and specificity but also to its situatedness, relatedness, including to what lies beyond it and not only spatially but temporally”.

Kairos is, then, the uniqueness of time that converts curriculum into a complicated conversation, one that includes the subjective reconstruction of learning as a consciousness of everyday life, encouraging the inner activism of quietude and disquietude. Writing about eternity, as an orientation towards the future, Pinar ( 2019 , p. 2) argues that “the second side [the first is contemplation] of such consciousness is immersion in daily life, the activism of quietude – for example, ethical engagement with others”. We add disquietude now, following the work of the Portuguese poet Fernando Pessoa. Disquietude is a moment of eternity: “Sometimes I think I’ll never leave ‘Douradores’ Street. And having written this, it seems to me eternity. Neither pleasure, nor glory, nor power. Freedom, only freedom” (Pesssoa 1991 ).

The disquietude conversation is simultaneously individual and public. It establishes an international space both deglobalized and autonomous, a source of responsive, ethical, and humane encounter. No longer entranced by the distracting dynamic stasis of image-after-image on the screen, the student can face what is his or her emplacement in the physical and natural world, as well as the technological world. The student can become present as a person, here and now, simultaneously historical and timeless.

Conclusions

Slow down and linger should be our motto now. A slogan yes, but it also represents a political, as well as a psychological resistance to the acceleration of time (Berg and Seeber 2016 )—an acceleration that the pandemic has intensified. Covid-19 has moved curriculum online, forcing children physically apart from each other and from their teachers and especially from the in-person dialogical encounters that classrooms can provide. The public space disappears into the pre-designed screen space that software allows, and the machine now becomes the material basis for a curriculum of things, not persons. Like the virus, the pandemic curriculum becomes embedded in devices that technologize our children.

Although one hundred years old, the images created in Modern Times by Charlie Chaplin return, less humorous this time than emblematic of our intensifying subjection to technological necessity. It “would seem to leave us as cogs in the machine, ourselves like moving parts, we keep functioning efficiently, increasing productivity calculating the creative destruction of what is, the human now materialized (de)vices ensnaring us in convenience, connectivity, calculation” (Pinar 2019 , p. 9). Post-human, as many would say.

Technology supports standardized testing and enforces software-designed conformity and never-ending self-evaluation, while all the time erasing lived, embodied experience and intellectual independence. Ignoring the evidence, others are sure that technology can function differently: “Given the potential of information and communication technologies, the teacher should now be a guide who enables learners, from early childhood throughout their learning trajectories, to develop and advance through the constantly expanding maze of knowledge” (UNESCO 2015a , p. 51). Would that it were so.

The canonical question—What knowledge is of most worth?—is open-ended and contentious. In a technologized world, providing for the well-being of children is not obvious, as well-being is embedded in ancient, non-neoliberal visions of the world. “Education is everybody’s business”, Pinar ( 2019 , p. 2) points out, as it fosters “responsible citizenship and solidarity in a global world” (UNESCO 2015a , p. 66), resisting inequality and the exclusion, for example, of migrant groups, refugees, and even those who live below or on the edge of poverty.

In this fast-moving digital world, education needs to be inclusive but not conformist. As the United Nations ( 2015 ) declares, education should ensure inclusive and equitable quality education and promote lifelong learning opportunities for all. “The coming years will be a vital period to save the planet and to achieve sustainable, inclusive human development” (United Nations 2019 , p. 64). Is such sustainable, inclusive human development achievable through technologization? Can technology succeed where religion has failed?

Despite its contradictions and economic emphases, public education has one clear obligation—to create embodied encounters of learning through curriculum conceived as a complicated conversation. Such a conception acknowledges the worldliness of a cosmopolitan curriculum as it affirms the personification of the individual (Pinar 2011 ). As noted by Grumet ( 2017 , p. 89), “as a form of ethics, there is a responsibility to participate in conversation”. Certainly, it is necessary to ask over and over again the canonical curriculum question: What knowledge is of most worth?

If time, technology and teaching are moving images of eternity, curriculum and pedagogy are also, both ‘moving’ and ‘images’ but not an explicit, empirical, or exact representation of eternity…if reality is an endless series of ‘moving images’, the canonical curriculum question—What knowledge is of most worth?—cannot be settled for all time by declaring one set of subjects eternally important” (Pinar 2019 , p. 12).

In a complicated conversation, the curriculum is not a fixed image sliding into a passive technologization. As a “moving image”, the curriculum constitutes a politics of presence, an ongoing expression of subjectivity (Grumet 2017 ) that affirms the infinity of reality: “Shifting one’s attitude from ‘reducing’ complexity to ‘embracing’ what is always already present in relations and interactions may lead to thinking complexly, abiding happily with mystery” (Doll 2012 , p. 172). Describing the dialogical encounter characterizing conceived curriculum, as a complicated conversation, Pinar explains that this moment of dialogue “is not only place-sensitive (perhaps classroom centered) but also within oneself”, because “the educational significance of subject matter is that it enables the student to learn from actual embodied experience, an outcome that cannot always be engineered” (Pinar 2019 , pp. 12–13). Lived experience is not technological. So, “the curriculum of the future is not just a matter of defining content and official knowledge. It is about creating, sculpting, and finessing minds, mentalities, and identities, promoting style of thought about humans, or ‘mashing up’ and ‘making up’ the future of people” (Williamson 2013 , p. 113).

Yes, we need to linger and take time to contemplate the curriculum question. Only in this way will we share what is common and distinctive in our experience of the current pandemic by changing our time and our learning to foreclose on our future. Curriculum conceived as a complicated conversation restarts historical not screen time; it enacts the private and public as distinguishable, not fused in a computer screen. That is the “new normal”.

is full professor in the Department of Curriculum Studies and Educational Technology (Institute of Education, University of Minho, Portugal). His research focuses on curriculum theory, curriculum politics, and teacher training and evaluation. Presently, he is director of the PhD Science Education Program of the University of Minho, member of the Advisory Board of the Organization of Ibero-American Studies, director of the European Journal of Curriculum Studies, and director of the European Association on Curriculum Studies.

My thanks to William F. Pinar. Friendship is another moving image of eternity. I am grateful to the anonymous reviewer. This work is financed by national funds through the FCT - Foundation for Science and Technology, under the project PTDC / CED-EDG / 30410/2017, Centre for Research in Education, Institute of Education, University of Minho.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

• Adorno, T. W. (2011). Educação e emancipação [Education and emancipation]. São Paulo: Paz e Terra.
• Aoki, T. T. (2011). Sonare and videre: A story, three echoes and a lingering note. In W. F. W. Pinar & R. L. Irwin (Eds.), Curriculum in a new key. The collected works of Ted T. Aoki (pp. 368–376). New York, NY: Routledge.
• Badiou A. Theory of the subject. London: Continuum; 2009. [ Google Scholar ]
• Berg M, Seeber B. The slow professor: Challenging the culture of speed in the academy. Toronto: University of Toronto Press; 2016. [ Google Scholar ]
• Couldry N, Mejias U. The costs of connection: How data is colonizing human life and appropriating it for capitalism. Stanford: Stanford University Press; 2019. [ Google Scholar ]
• Daniel SJ. Education and the Covid-19 pandemic. Prospects. 2020 doi: 10.1007/s11125-020-09464-3. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Davies D, Beauchamp G, Davies J, Price R. The potential of the ‘Internet of Things’ to enhance inquiry in Singapore schools. Research in Science & Technological Education. 2019 doi: 10.1080/02635143.2019.1629896. [ CrossRef ] [ Google Scholar ]
• Delors J. Learning: The treasure within. Paris: UNESCO; 1996. [ Google Scholar ]
• Doll, W. E. (2012). Thinking complexly. In D. Trueit (Ed.), Pragmatism, post-modernism, and complexity theory: The “fascinating imaginative realm” of William E. Doll, Jr. (pp. 172–187). New York, NY: Routledge.
• Doll WE. Curriculum and concepts of control. In: Pinar WF, editor. Curriculum: Toward new identities. New York, NY: Routledge; 2013. pp. 295–324. [ Google Scholar ]
• Eley G. Conclusion. In: Thomas JA, Eley G, editors. Visualizing fascism: The twentieth-century rise of the global Right. Durham, NC: Duke University Press; 2020. pp. 284–292. [ Google Scholar ]
• Gil, J. (2020). A pandemia e o capitalismo numérico [The pandemic and numerical capitalism]. Público . https://www.publico.pt/2020/04/12/sociedade/ensaio/pandemia-capitalismo-numerico-1911986 .
• Grumet, M.G. (2017). The politics of presence. In M. A. Doll (Ed.), The reconceptualization of curriculum studies. A Festschrift in honor of William F. Pinar (pp. 76–83). New York, NY: Routledge.
• Heidegger M. What is a thing? South Bend, IN: Gateway Editions; 1967. [ Google Scholar ]
• Heidegger M. Poetry, language, thought. New York, NY: Harper and Row; 1971. [ Google Scholar ]
• Heidegger M. The question concerning technology and other essays. New York, NY: Harper and Row; 1977. [ Google Scholar ]
• Koepnick L. On slowness: Toward an aesthetic of the contemporary. New York, NY: Columbia University Press; 2014. [ Google Scholar ]
• Koopman C. How we became our data: A genealogy of the informational person. Chicago, IL: University of Chicago Press; 2019. [ Google Scholar ]
• Lahtinen M. Politics and curriculum. Leiden: Brill; 2009. [ Google Scholar ]
• Laist R. A curriculum of things: Exploring an object-oriented pedagogy. The National Teaching & Learning. 2016; 25 (3):1–4. doi: 10.1002/ntlf.30062. [ CrossRef ] [ Google Scholar ]
• Latour, B. (2020). Is this a dress rehearsal? Critical Inquiry . https://critinq.wordpress.com/2020/03/26/is-this-a-dress-rehearsal
• Lyotard J. The postmodern condition: A report on knowledge. Manchester: Manchester University Press; 1984. [ Google Scholar ]
• Macdonald BJ. Theory as a prayerful act. New York, NY: Peter Lang; 1995. [ Google Scholar ]
• Marope PTM. Reconceptualizing and repositioning curriculum in the 21st century: A global paradigm shift. Geneva: UNESCO IBE; 2017. [ Google Scholar ]
• Marope PTM. Preventing violent extremism through universal values in curriculum. Prospects. 2020; 48 (1):1–5. doi: 10.1007/s11125-019-09453-1. [ CrossRef ] [ Google Scholar ]
• Means B. Technology’s role in curriculum and instruction. In: Connelly FM, editor. The Sage handbook of curriculum and instruction. Los Angeles, CA: Sage; 2008. pp. 123–144. [ Google Scholar ]
• OECD . OECD learning compass 2030. Paris: OECD; 2019. [ Google Scholar ]
• OECD . Trends shaping education 2019. Paris: OECD; 2019. [ Google Scholar ]
• Pacheco, J. A. (2009). Whole, bright, deep with understanding: Life story and politics of curriculum studies. In-between William Pinar and Ivor Goodson . Roterdam/Taipei: Sense Publishers.
• Pacheco, J. A. (2017). Pinar’s influence on the consolidation of Portuguese curriculum studies. In M. A. Doll (Ed.), The reconceptualization of curriculum studies. A Festschrift in honor of William F. Pinar (pp. 130–136). New York, NY: Routledge.
• Pestre, D. (2013). Science, technologie et société. La politique des savoirs aujourd’hui [Science, technology, and society: Politics of knowledge today]. Paris: Foundation Calouste Gulbenkian.
• Pesssoa F. The book of disquietude. Manchester: Carcanet Press; 1991. [ Google Scholar ]
• Pinar WF. What is curriculum theory? Mahwah, NJ: Lawrence Erlbaum Associates; 2004. [ Google Scholar ]
• Pinar WF. The worldliness of a cosmopolitan education: Passionate lives in public service. New York, NY: Routledge; 2009. [ Google Scholar ]
• Pinar, W. F. (2011). “A lingering note”: An introduction to the collected work of Ted T. Aoki. In W. F. Pinar & R. L. Irwin (Eds.), Curriculum in a new key. The collected works of Ted T. Aoki (pp. 1–85). New York, NY: Routledge.
• Pinar WF. Moving images of eternity: George Grant’s critique of time, teaching, and technology. Ottawa: The University of Ottawa Press; 2019. [ Google Scholar ]
• Shew M. The Kairos philosophy. The Journal of Speculative Philosophy. 2013; 27 (1):47–66. doi: 10.5325/jspecphil.27.1.0047. [ CrossRef ] [ Google Scholar ]
• Spiller, P. (2017). Could subjects soon be a thing of the past in Finland? BBC News . https://www.bbc.com/news/world-europe-39889523 .
• UNESCO (2015a). Rethinking education. Towards a global common global? Paris: UNESCO.
• UNESCO (2015b). Education 2030. Framework for action . Paris: UNESCO. https://www.sdg4education2030.org/sdg-education-2030-steering-committee-resources .
• UNESCO (2017). Global citizenship education . Paris: UNESCO. https://en.unesco.org/themes/gced .
• United Nations . The sustainable development goals. New York, NY: United Nations; 2015. [ Google Scholar ]
• United Nations . The sustainable development goals report. New York, NY: United Nations; 2019. [ Google Scholar ]
• Wells W. Permanent revolution: Reflections on capitalism. Stanford, CA: Stanford University Press; 2020. [ Google Scholar ]
• Westbury, I. (2008). Making curricula. Why do states make curricula, and how? In F. M. Connelly (Ed.), The Sage handbook of curriculum and instruction (pp. 45–65). Los Angeles, CA: Sage.
• Williamson B. The future of the curriculum. School knowledge in the digital age. Cambridge, MA: MIT Press; 2013. [ Google Scholar ]
• Williamson, B. (2017). Big data in education. The digital future of learning, policy and practice . London: Sage.
• Žižek S. PANDEMIC! Covid-19 shakes the world. New York, NY: Or Books; 2020. [ Google Scholar ]

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Open access
• Published: 31 August 2024

Knowledge mapping and evolution of research on older adults’ technology acceptance: a bibliometric study from 2013 to 2023

• Xianru Shang   ORCID: orcid.org/0009-0000-8906-3216 1 ,
• Zijian Liu 1 ,
• Chen Gong 1 ,
• Zhigang Hu 1 ,
• Yuexuan Wu 1 &
• Chengliang Wang   ORCID: orcid.org/0000-0003-2208-3508 2  

Humanities and Social Sciences Communications volume  11 , Article number:  1115 ( 2024 ) Cite this article

Metrics details

• Science, technology and society

The rapid expansion of information technology and the intensification of population aging are two prominent features of contemporary societal development. Investigating older adults’ acceptance and use of technology is key to facilitating their integration into an information-driven society. Given this context, the technology acceptance of older adults has emerged as a prioritized research topic, attracting widespread attention in the academic community. However, existing research remains fragmented and lacks a systematic framework. To address this gap, we employed bibliometric methods, utilizing the Web of Science Core Collection to conduct a comprehensive review of literature on older adults’ technology acceptance from 2013 to 2023. Utilizing VOSviewer and CiteSpace for data assessment and visualization, we created knowledge mappings of research on older adults’ technology acceptance. Our study employed multidimensional methods such as co-occurrence analysis, clustering, and burst analysis to: (1) reveal research dynamics, key journals, and domains in this field; (2) identify leading countries, their collaborative networks, and core research institutions and authors; (3) recognize the foundational knowledge system centered on theoretical model deepening, emerging technology applications, and research methods and evaluation, uncovering seminal literature and observing a shift from early theoretical and influential factor analyses to empirical studies focusing on individual factors and emerging technologies; (4) moreover, current research hotspots are primarily in the areas of factors influencing technology adoption, human-robot interaction experiences, mobile health management, and aging-in-place technology, highlighting the evolutionary context and quality distribution of research themes. Finally, we recommend that future research should deeply explore improvements in theoretical models, long-term usage, and user experience evaluation. Overall, this study presents a clear framework of existing research in the field of older adults’ technology acceptance, providing an important reference for future theoretical exploration and innovative applications.

Similar content being viewed by others

Research progress and intellectual structure of design for digital equity (DDE): A bibliometric analysis based on citespace

Exploring the role of interaction in older-adult service innovation: insights from the testing stage

Smart device interest, perceived usefulness, and preferences in rural Alabama seniors

Introduction.

In contemporary society, the rapid development of information technology has been intricately intertwined with the intensifying trend of population aging. According to the latest United Nations forecast, by 2050, the global population aged 65 and above is expected to reach 1.6 billion, representing about 16% of the total global population (UN 2023 ). Given the significant challenges of global aging, there is increasing evidence that emerging technologies have significant potential to maintain health and independence for older adults in their home and healthcare environments (Barnard et al. 2013 ; Soar 2010 ; Vancea and Solé-Casals 2016 ). This includes, but is not limited to, enhancing residential safety with smart home technologies (Touqeer et al. 2021 ; Wang et al. 2022 ), improving living independence through wearable technologies (Perez et al. 2023 ), and increasing medical accessibility via telehealth services (Kruse et al. 2020 ). Technological innovations are redefining the lifestyles of older adults, encouraging a shift from passive to active participation (González et al. 2012 ; Mostaghel 2016 ). Nevertheless, the effective application and dissemination of technology still depends on user acceptance and usage intentions (Naseri et al. 2023 ; Wang et al. 2023a ; Xia et al. 2024 ; Yu et al. 2023 ). Particularly, older adults face numerous challenges in accepting and using new technologies. These challenges include not only physical and cognitive limitations but also a lack of technological experience, along with the influences of social and economic factors (Valk et al. 2018 ; Wilson et al. 2021 ).

User acceptance of technology is a significant focus within information systems (IS) research (Dai et al. 2024 ), with several models developed to explain and predict user behavior towards technology usage, including the Technology Acceptance Model (TAM) (Davis 1989 ), TAM2, TAM3, and the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al. 2003 ). Older adults, as a group with unique needs, exhibit different behavioral patterns during technology acceptance than other user groups, and these uniquenesses include changes in cognitive abilities, as well as motivations, attitudes, and perceptions of the use of new technologies (Chen and Chan 2011 ). The continual expansion of technology introduces considerable challenges for older adults, rendering the understanding of their technology acceptance a research priority. Thus, conducting in-depth research into older adults’ acceptance of technology is critically important for enhancing their integration into the information society and improving their quality of life through technological advancements.

Reviewing relevant literature to identify research gaps helps further solidify the theoretical foundation of the research topic. However, many existing literature reviews primarily focus on the factors influencing older adults’ acceptance or intentions to use technology. For instance, Ma et al. ( 2021 ) conducted a comprehensive analysis of the determinants of older adults’ behavioral intentions to use technology; Liu et al. ( 2022 ) categorized key variables in studies of older adults’ technology acceptance, noting a shift in focus towards social and emotional factors; Yap et al. ( 2022 ) identified seven categories of antecedents affecting older adults’ use of technology from an analysis of 26 articles, including technological, psychological, social, personal, cost, behavioral, and environmental factors; Schroeder et al. ( 2023 ) extracted 119 influencing factors from 59 articles and further categorized these into six themes covering demographics, health status, and emotional awareness. Additionally, some studies focus on the application of specific technologies, such as Ferguson et al. ( 2021 ), who explored barriers and facilitators to older adults using wearable devices for heart monitoring, and He et al. ( 2022 ) and Baer et al. ( 2022 ), who each conducted in-depth investigations into the acceptance of social assistive robots and mobile nutrition and fitness apps, respectively. In summary, current literature reviews on older adults’ technology acceptance exhibit certain limitations. Due to the interdisciplinary nature and complex knowledge structure of this field, traditional literature reviews often rely on qualitative analysis, based on literature analysis and periodic summaries, which lack sufficient objectivity and comprehensiveness. Additionally, systematic research is relatively limited, lacking a macroscopic description of the research trajectory from a holistic perspective. Over the past decade, research on older adults’ technology acceptance has experienced rapid growth, with a significant increase in literature, necessitating the adoption of new methods to review and examine the developmental trends in this field (Chen 2006 ; Van Eck and Waltman 2010 ). Bibliometric analysis, as an effective quantitative research method, analyzes published literature through visualization, offering a viable approach to extracting patterns and insights from a large volume of papers, and has been widely applied in numerous scientific research fields (Achuthan et al. 2023 ; Liu and Duffy 2023 ). Therefore, this study will employ bibliometric methods to systematically analyze research articles related to older adults’ technology acceptance published in the Web of Science Core Collection from 2013 to 2023, aiming to understand the core issues and evolutionary trends in the field, and to provide valuable references for future related research. Specifically, this study aims to explore and answer the following questions:

RQ1: What are the research dynamics in the field of older adults’ technology acceptance over the past decade? What are the main academic journals and fields that publish studies related to older adults’ technology acceptance?

RQ2: How is the productivity in older adults’ technology acceptance research distributed among countries, institutions, and authors?

RQ3: What are the knowledge base and seminal literature in older adults’ technology acceptance research? How has the research theme progressed?

RQ4: What are the current hot topics and their evolutionary trajectories in older adults’ technology acceptance research? How is the quality of research distributed?

Methodology and materials

Research method.

In recent years, bibliometrics has become one of the crucial methods for analyzing literature reviews and is widely used in disciplinary and industrial intelligence analysis (Jing et al. 2023 ; Lin and Yu 2024a ; Wang et al. 2024a ; Xu et al. 2021 ). Bibliometric software facilitates the visualization analysis of extensive literature data, intuitively displaying the network relationships and evolutionary processes between knowledge units, and revealing the underlying knowledge structure and potential information (Chen et al. 2024 ; López-Robles et al. 2018 ; Wang et al. 2024c ). This method provides new insights into the current status and trends of specific research areas, along with quantitative evidence, thereby enhancing the objectivity and scientific validity of the research conclusions (Chen et al. 2023 ; Geng et al. 2024 ). VOSviewer and CiteSpace are two widely used bibliometric software tools in academia (Pan et al. 2018 ), recognized for their robust functionalities based on the JAVA platform. Although each has its unique features, combining these two software tools effectively constructs mapping relationships between literature knowledge units and clearly displays the macrostructure of the knowledge domains. Particularly, VOSviewer, with its excellent graphical representation capabilities, serves as an ideal tool for handling large datasets and precisely identifying the focal points and hotspots of research topics. Therefore, this study utilizes VOSviewer (version 1.6.19) and CiteSpace (version 6.1.R6), combined with in-depth literature analysis, to comprehensively examine and interpret the research theme of older adults’ technology acceptance through an integrated application of quantitative and qualitative methods.

Data source

Web of Science is a comprehensively recognized database in academia, featuring literature that has undergone rigorous peer review and editorial scrutiny (Lin and Yu 2024b ; Mongeon and Paul-Hus 2016 ; Pranckutė 2021 ). This study utilizes the Web of Science Core Collection as its data source, specifically including three major citation indices: Science Citation Index Expanded (SCIE), Social Sciences Citation Index (SSCI), and Arts & Humanities Citation Index (A&HCI). These indices encompass high-quality research literature in the fields of science, social sciences, and arts and humanities, ensuring the comprehensiveness and reliability of the data. We combined “older adults” with “technology acceptance” through thematic search, with the specific search strategy being: TS = (elder OR elderly OR aging OR ageing OR senile OR senior OR old people OR “older adult*”) AND TS = (“technology acceptance” OR “user acceptance” OR “consumer acceptance”). The time span of literature search is from 2013 to 2023, with the types limited to “Article” and “Review” and the language to “English”. Additionally, the search was completed by October 27, 2023, to avoid data discrepancies caused by database updates. The initial search yielded 764 journal articles. Given that searches often retrieve articles that are superficially relevant but actually non-compliant, manual screening post-search was essential to ensure the relevance of the literature (Chen et al. 2024 ). Through manual screening, articles significantly deviating from the research theme were eliminated and rigorously reviewed. Ultimately, this study obtained 500 valid sample articles from the Web of Science Core Collection. The complete PRISMA screening process is illustrated in Fig. 1 .

Presentation of the data culling process in detail.

Data standardization

Raw data exported from databases often contain multiple expressions of the same terminology (Nguyen and Hallinger 2020 ). To ensure the accuracy and consistency of data, it is necessary to standardize the raw data (Strotmann and Zhao 2012 ). This study follows the data standardization process proposed by Taskin and Al ( 2019 ), mainly executing the following operations:

(1) Standardization of author and institution names is conducted to address different name expressions for the same author. For instance, “Chan, Alan Hoi Shou” and “Chan, Alan H. S.” are considered the same author, and distinct authors with the same name are differentiated by adding identifiers. Diverse forms of institutional names are unified to address variations caused by name changes or abbreviations, such as standardizing “FRANKFURT UNIV APPL SCI” and “Frankfurt University of Applied Sciences,” as well as “Chinese University of Hong Kong” and “University of Hong Kong” to consistent names.

(2) Different expressions of journal names are unified. For example, “International Journal of Human-Computer Interaction” and “Int J Hum Comput Interact” are standardized to a single name. This ensures consistency in journal names and prevents misclassification of literature due to differing journal names. Additionally, it involves checking if the journals have undergone name changes in the past decade to prevent any impact on the analysis due to such changes.

(3) Keywords data are cleansed by removing words that do not directly pertain to specific research content (e.g., people, review), merging synonyms (e.g., “UX” and “User Experience,” “aging-in-place” and “aging in place”), and standardizing plural forms of keywords (e.g., “assistive technologies” and “assistive technology,” “social robots” and “social robot”). This reduces redundant information in knowledge mapping.

Bibliometric results and analysis

Distribution power (rq1), literature descriptive statistical analysis.

Table 1 presents a detailed descriptive statistical overview of the literature in the field of older adults’ technology acceptance. After deduplication using the CiteSpace software, this study confirmed a valid sample size of 500 articles. Authored by 1839 researchers, the documents encompass 792 research institutions across 54 countries and are published in 217 different academic journals. As of the search cutoff date, these articles have accumulated 13,829 citations, with an annual average of 1156 citations, and an average of 27.66 citations per article. The h-index, a composite metric of quantity and quality of scientific output (Kamrani et al. 2021 ), reached 60 in this study.

Trends in publications and disciplinary distribution

The number of publications and citations are significant indicators of the research field’s development, reflecting its continuity, attention, and impact (Ale Ebrahim et al. 2014 ). The ranking of annual publications and citations in the field of older adults’ technology acceptance studies is presented chronologically in Fig. 2A . The figure shows a clear upward trend in the amount of literature in this field. Between 2013 and 2017, the number of publications increased slowly and decreased in 2018. However, in 2019, the number of publications increased rapidly to 52 and reached a peak of 108 in 2022, which is 6.75 times higher than in 2013. In 2022, the frequency of document citations reached its highest point with 3466 citations, reflecting the widespread recognition and citation of research in this field. Moreover, the curve of the annual number of publications fits a quadratic function, with a goodness-of-fit R 2 of 0.9661, indicating that the number of future publications is expected to increase even more rapidly.

A Trends in trends in annual publications and citations (2013–2023). B Overlay analysis of the distribution of discipline fields.

Figure 2B shows that research on older adults’ technology acceptance involves the integration of multidisciplinary knowledge. According to Web of Science Categories, these 500 articles are distributed across 85 different disciplines. We have tabulated the top ten disciplines by publication volume (Table 2 ), which include Medical Informatics (75 articles, 15.00%), Health Care Sciences & Services (71 articles, 14.20%), Gerontology (61 articles, 12.20%), Public Environmental & Occupational Health (57 articles, 11.40%), and Geriatrics & Gerontology (52 articles, 10.40%), among others. The high output in these disciplines reflects the concentrated global academic interest in this comprehensive research topic. Additionally, interdisciplinary research approaches provide diverse perspectives and a solid theoretical foundation for studies on older adults’ technology acceptance, also paving the way for new research directions.

Knowledge flow analysis

A dual-map overlay is a CiteSpace map superimposed on top of a base map, which shows the interrelationships between journals in different domains, representing the publication and citation activities in each domain (Chen and Leydesdorff 2014 ). The overlay map reveals the link between the citing domain (on the left side) and the cited domain (on the right side), reflecting the knowledge flow of the discipline at the journal level (Leydesdorff and Rafols 2012 ). We utilize the in-built Z-score algorithm of the software to cluster the graph, as shown in Fig. 3 .

The left side shows the citing journal, and the right side shows the cited journal.

Figure 3 shows the distribution of citing journals clusters for older adults’ technology acceptance on the left side, while the right side refers to the main cited journals clusters. Two knowledge flow citation trajectories were obtained; they are presented by the color of the cited regions, and the thickness of these trajectories is proportional to the Z-score scaled frequency of citations (Chen et al. 2014 ). Within the cited regions, the most popular fields with the most records covered are “HEALTH, NURSING, MEDICINE” and “PSYCHOLOGY, EDUCATION, SOCIAL”, and the elliptical aspect ratio of these two fields stands out. Fields have prominent elliptical aspect ratios, highlighting their significant influence on older adults’ technology acceptance research. Additionally, the major citation trajectories originate in these two areas and progress to the frontier research area of “PSYCHOLOGY, EDUCATION, HEALTH”. It is worth noting that the citation trajectory from “PSYCHOLOGY, EDUCATION, SOCIAL” has a significant Z-value (z = 6.81), emphasizing the significance and impact of this development path. In the future, “MATHEMATICS, SYSTEMS, MATHEMATICAL”, “MOLECULAR, BIOLOGY, IMMUNOLOGY”, and “NEUROLOGY, SPORTS, OPHTHALMOLOGY” may become emerging fields. The fields of “MEDICINE, MEDICAL, CLINICAL” may be emerging areas of cutting-edge research.

Main research journals analysis

Table 3 provides statistics for the top ten journals by publication volume in the field of older adults’ technology acceptance. Together, these journals have published 137 articles, accounting for 27.40% of the total publications, indicating that there is no highly concentrated core group of journals in this field, with publications being relatively dispersed. Notably, Computers in Human Behavior , Journal of Medical Internet Research , and International Journal of Human-Computer Interaction each lead with 15 publications. In terms of citation metrics, International Journal of Medical Informatics and Computers in Human Behavior stand out significantly, with the former accumulating a total of 1,904 citations, averaging 211.56 citations per article, and the latter totaling 1,449 citations, with an average of 96.60 citations per article. These figures emphasize the academic authority and widespread impact of these journals within the research field.

Research power (RQ2)

Countries and collaborations analysis.

The analysis revealed the global research pattern for country distribution and collaboration (Chen et al. 2019 ). Figure 4A shows the network of national collaborations on older adults’ technology acceptance research. The size of the bubbles represents the amount of publications in each country, while the thickness of the connecting lines expresses the closeness of the collaboration among countries. Generally, this research subject has received extensive international attention, with China and the USA publishing far more than any other countries. China has established notable research collaborations with the USA, UK and Malaysia in this field, while other countries have collaborations, but the closeness is relatively low and scattered. Figure 4B shows the annual publication volume dynamics of the top ten countries in terms of total publications. Since 2017, China has consistently increased its annual publications, while the USA has remained relatively stable. In 2019, the volume of publications in each country increased significantly, this was largely due to the global outbreak of the COVID-19 pandemic, which has led to increased reliance on information technology among the elderly for medical consultations, online socialization, and health management (Sinha et al. 2021 ). This phenomenon has led to research advances in technology acceptance among older adults in various countries. Table 4 shows that the top ten countries account for 93.20% of the total cumulative number of publications, with each country having published more than 20 papers. Among these ten countries, all of them except China are developed countries, indicating that the research field of older adults’ technology acceptance has received general attention from developed countries. Currently, China and the USA were the leading countries in terms of publications with 111 and 104 respectively, accounting for 22.20% and 20.80%. The UK, Germany, Italy, and the Netherlands also made significant contributions. The USA and China ranked first and second in terms of the number of citations, while the Netherlands had the highest average citations, indicating the high impact and quality of its research. The UK has shown outstanding performance in international cooperation, while the USA highlights its significant academic influence in this field with the highest h-index value.

A National collaboration network. B Annual volume of publications in the top 10 countries.

Institutions and authors analysis

Analyzing the number of publications and citations can reveal an institution’s or author’s research strength and influence in a particular research area (Kwiek 2021 ). Tables 5 and 6 show the statistics of the institutions and authors whose publication counts are in the top ten, respectively. As shown in Table 5 , higher education institutions hold the main position in this research field. Among the top ten institutions, City University of Hong Kong and The University of Hong Kong from China lead with 14 and 9 publications, respectively. City University of Hong Kong has the highest h-index, highlighting its significant influence in the field. It is worth noting that Tilburg University in the Netherlands is not among the top five in terms of publications, but the high average citation count (130.14) of its literature demonstrates the high quality of its research.

After analyzing the authors’ output using Price’s Law (Redner 1998 ), the highest number of publications among the authors counted ( n  = 10) defines a publication threshold of 3 for core authors in this research area. As a result of quantitative screening, a total of 63 core authors were identified. Table 6 shows that Chen from Zhejiang University, China, Ziefle from RWTH Aachen University, Germany, and Rogers from Macquarie University, Australia, were the top three authors in terms of the number of publications, with 10, 9, and 8 articles, respectively. In terms of average citation rate, Peek and Wouters, both scholars from the Netherlands, have significantly higher rates than other scholars, with 183.2 and 152.67 respectively. This suggests that their research is of high quality and widely recognized. Additionally, Chen and Rogers have high h-indices in this field.

Knowledge base and theme progress (RQ3)

Research knowledge base.

Co-citation relationships occur when two documents are cited together (Zhang and Zhu 2022 ). Co-citation mapping uses references as nodes to represent the knowledge base of a subject area (Min et al. 2021). Figure 5A illustrates co-occurrence mapping in older adults’ technology acceptance research, where larger nodes signify higher co-citation frequencies. Co-citation cluster analysis can be used to explore knowledge structure and research boundaries (Hota et al. 2020 ; Shiau et al. 2023 ). The co-citation clustering mapping of older adults’ technology acceptance research literature (Fig. 5B ) shows that the Q value of the clustering result is 0.8129 (>0.3), and the average value of the weight S is 0.9391 (>0.7), indicating that the clusters are uniformly distributed with a significant and credible structure. This further proves that the boundaries of the research field are clear and there is significant differentiation in the field. The figure features 18 cluster labels, each associated with thematic color blocks corresponding to different time slices. Highlighted emerging research themes include #2 Smart Home Technology, #7 Social Live, and #10 Customer Service. Furthermore, the clustering labels extracted are primarily classified into three categories: theoretical model deepening, emerging technology applications, research methods and evaluation, as detailed in Table 7 .

A Co-citation analysis of references. B Clustering network analysis of references.

Seminal literature analysis

The top ten nodes in terms of co-citation frequency were selected for further analysis. Table 8 displays the corresponding node information. Studies were categorized into four main groups based on content analysis. (1) Research focusing on specific technology usage by older adults includes studies by Peek et al. ( 2014 ), Ma et al. ( 2016 ), Hoque and Sorwar ( 2017 ), and Li et al. ( 2019 ), who investigated the factors influencing the use of e-technology, smartphones, mHealth, and smart wearables, respectively. (2) Concerning the development of theoretical models of technology acceptance, Chen and Chan ( 2014 ) introduced the Senior Technology Acceptance Model (STAM), and Macedo ( 2017 ) analyzed the predictive power of UTAUT2 in explaining older adults’ intentional behaviors and information technology usage. (3) In exploring older adults’ information technology adoption and behavior, Lee and Coughlin ( 2015 ) emphasized that the adoption of technology by older adults is a multifactorial process that includes performance, price, value, usability, affordability, accessibility, technical support, social support, emotion, independence, experience, and confidence. Yusif et al. ( 2016 ) conducted a literature review examining the key barriers affecting older adults’ adoption of assistive technology, including factors such as privacy, trust, functionality/added value, cost, and stigma. (4) From the perspective of research into older adults’ technology acceptance, Mitzner et al. ( 2019 ) assessed the long-term usage of computer systems designed for the elderly, whereas Guner and Acarturk ( 2020 ) compared information technology usage and acceptance between older and younger adults. The breadth and prevalence of this literature make it a vital reference for researchers in the field, also providing new perspectives and inspiration for future research directions.

Research thematic progress

Burst citation is a node of literature that guides the sudden change in dosage, which usually represents a prominent development or major change in a particular field, with innovative and forward-looking qualities. By analyzing the emergent literature, it is often easy to understand the dynamics of the subject area, mapping the emerging thematic change (Chen et al. 2022 ). Figure 6 shows the burst citation mapping in the field of older adults’ technology acceptance research, with burst citations represented by red nodes (Fig. 6A ). For the ten papers with the highest burst intensity (Fig. 6B ), this study will conduct further analysis in conjunction with literature review.

A Burst detection of co-citation. B The top 10 references with the strongest citation bursts.

As shown in Fig. 6 , Mitzner et al. ( 2010 ) broke the stereotype that older adults are fearful of technology, found that they actually have positive attitudes toward technology, and emphasized the centrality of ease of use and usefulness in the process of technology acceptance. This finding provides an important foundation for subsequent research. During the same period, Wagner et al. ( 2010 ) conducted theory-deepening and applied research on technology acceptance among older adults. The research focused on older adults’ interactions with computers from the perspective of Social Cognitive Theory (SCT). This expanded the understanding of technology acceptance, particularly regarding the relationship between behavior, environment, and other SCT elements. In addition, Pan and Jordan-Marsh ( 2010 ) extended the TAM to examine the interactions among predictors of perceived usefulness, perceived ease of use, subjective norm, and convenience conditions when older adults use the Internet, taking into account the moderating roles of gender and age. Heerink et al. ( 2010 ) adapted and extended the UTAUT, constructed a technology acceptance model specifically designed for older users’ acceptance of assistive social agents, and validated it using controlled experiments and longitudinal data, explaining intention to use by combining functional assessment and social interaction variables.

Then the research theme shifted to an in-depth analysis of the factors influencing technology acceptance among older adults. Two papers with high burst strengths emerged during this period: Peek et al. ( 2014 ) (Strength = 12.04), Chen and Chan ( 2014 ) (Strength = 9.81). Through a systematic literature review and empirical study, Peek STM and Chen K, among others, identified multidimensional factors that influence older adults’ technology acceptance. Peek et al. ( 2014 ) analyzed literature on the acceptance of in-home care technology among older adults and identified six factors that influence their acceptance: concerns about technology, expected benefits, technology needs, technology alternatives, social influences, and older adult characteristics, with a focus on differences between pre- and post-implementation factors. Chen and Chan ( 2014 ) constructed the STAM by administering a questionnaire to 1012 older adults and adding eight important factors, including technology anxiety, self-efficacy, cognitive ability, and physical function, based on the TAM. This enriches the theoretical foundation of the field. In addition, Braun ( 2013 ) highlighted the role of perceived usefulness, trust in social networks, and frequency of Internet use in older adults’ use of social networks, while ease of use and social pressure were not significant influences. These findings contribute to the study of older adults’ technology acceptance within specific technology application domains.

Recent research has focused on empirical studies of personal factors and emerging technologies. Ma et al. ( 2016 ) identified key personal factors affecting smartphone acceptance among older adults through structured questionnaires and face-to-face interviews with 120 participants. The study found that cost, self-satisfaction, and convenience were important factors influencing perceived usefulness and ease of use. This study offers empirical evidence to comprehend the main factors that drive smartphone acceptance among Chinese older adults. Additionally, Yusif et al. ( 2016 ) presented an overview of the obstacles that hinder older adults’ acceptance of assistive technologies, focusing on privacy, trust, and functionality.

In summary, research on older adults’ technology acceptance has shifted from early theoretical deepening and analysis of influencing factors to empirical studies in the areas of personal factors and emerging technologies, which have greatly enriched the theoretical basis of older adults’ technology acceptance and provided practical guidance for the design of emerging technology products.

Research hotspots, evolutionary trends, and quality distribution (RQ4)

Core keywords analysis.

Keywords concise the main idea and core of the literature, and are a refined summary of the research content (Huang et al. 2021 ). In CiteSpace, nodes with a centrality value greater than 0.1 are considered to be critical nodes. Analyzing keywords with high frequency and centrality helps to visualize the hot topics in the research field (Park et al. 2018 ). The merged keywords were imported into CiteSpace, and the top 10 keywords were counted and sorted by frequency and centrality respectively, as shown in Table 9 . The results show that the keyword “TAM” has the highest frequency (92), followed by “UTAUT” (24), which reflects that the in-depth study of the existing technology acceptance model and its theoretical expansion occupy a central position in research related to older adults’ technology acceptance. Furthermore, the terms ‘assistive technology’ and ‘virtual reality’ are both high-frequency and high-centrality terms (frequency = 17, centrality = 0.10), indicating that the research on assistive technology and virtual reality for older adults is the focus of current academic attention.

Research hotspots analysis

Using VOSviewer for keyword co-occurrence analysis organizes keywords into groups or clusters based on their intrinsic connections and frequencies, clearly highlighting the research field’s hot topics. The connectivity among keywords reveals correlations between different topics. To ensure accuracy, the analysis only considered the authors’ keywords. Subsequently, the keywords were filtered by setting the keyword frequency to 5 to obtain the keyword clustering map of the research on older adults’ technology acceptance research keyword clustering mapping (Fig. 7 ), combined with the keyword co-occurrence clustering network (Fig. 7A ) and the corresponding density situation (Fig. 7B ) to make a detailed analysis of the following four groups of clustered themes.

A Co-occurrence clustering network. B Keyword density.

Cluster #1—Research on the factors influencing technology adoption among older adults is a prominent topic, covering age, gender, self-efficacy, attitude, and and intention to use (Berkowsky et al. 2017 ; Wang et al. 2017 ). It also examined older adults’ attitudes towards and acceptance of digital health technologies (Ahmad and Mozelius, 2022 ). Moreover, the COVID-19 pandemic, significantly impacting older adults’ technology attitudes and usage, has underscored the study’s importance and urgency. Therefore, it is crucial to conduct in-depth studies on how older adults accept, adopt, and effectively use new technologies, to address their needs and help them overcome the digital divide within digital inclusion. This will improve their quality of life and healthcare experiences.

Cluster #2—Research focuses on how older adults interact with assistive technologies, especially assistive robots and health monitoring devices, emphasizing trust, usability, and user experience as crucial factors (Halim et al. 2022 ). Moreover, health monitoring technologies effectively track and manage health issues common in older adults, like dementia and mild cognitive impairment (Lussier et al. 2018 ; Piau et al. 2019 ). Interactive exercise games and virtual reality have been deployed to encourage more physical and cognitive engagement among older adults (Campo-Prieto et al. 2021 ). Personalized and innovative technology significantly enhances older adults’ participation, improving their health and well-being.

Cluster #3—Optimizing health management for older adults using mobile technology. With the development of mobile health (mHealth) and health information technology, mobile applications, smartphones, and smart wearable devices have become effective tools to help older users better manage chronic conditions, conduct real-time health monitoring, and even receive telehealth services (Dupuis and Tsotsos 2018 ; Olmedo-Aguirre et al. 2022 ; Kim et al. 2014 ). Additionally, these technologies can mitigate the problem of healthcare resource inequality, especially in developing countries. Older adults’ acceptance and use of these technologies are significantly influenced by their behavioral intentions, motivational factors, and self-management skills. These internal motivational factors, along with external factors, jointly affect older adults’ performance in health management and quality of life.

Cluster #4—Research on technology-assisted home care for older adults is gaining popularity. Environmentally assisted living enhances older adults’ independence and comfort at home, offering essential support and security. This has a crucial impact on promoting healthy aging (Friesen et al. 2016 ; Wahlroos et al. 2023 ). The smart home is a core application in this field, providing a range of solutions that facilitate independent living for the elderly in a highly integrated and user-friendly manner. This fulfills different dimensions of living and health needs (Majumder et al. 2017 ). Moreover, eHealth offers accurate and personalized health management and healthcare services for older adults (Delmastro et al. 2018 ), ensuring their needs are met at home. Research in this field often employs qualitative methods and structural equation modeling to fully understand older adults’ needs and experiences at home and analyze factors influencing technology adoption.

Evolutionary trends analysis

To gain a deeper understanding of the evolutionary trends in research hotspots within the field of older adults’ technology acceptance, we conducted a statistical analysis of the average appearance times of keywords, using CiteSpace to generate the time-zone evolution mapping (Fig. 8 ) and burst keywords. The time-zone mapping visually displays the evolution of keywords over time, intuitively reflecting the frequency and initial appearance of keywords in research, commonly used to identify trends in research topics (Jing et al. 2024a ; Kumar et al. 2021 ). Table 10 lists the top 15 keywords by burst strength, with the red sections indicating high-frequency citations and their burst strength in specific years. These burst keywords reveal the focus and trends of research themes over different periods (Kleinberg 2002 ). Combining insights from the time-zone mapping and burst keywords provides more objective and accurate research insights (Wang et al. 2023b ).

Reflecting the frequency and time of first appearance of keywords in the study.

An integrated analysis of Fig. 8 and Table 10 shows that early research on older adults’ technology acceptance primarily focused on factors such as perceived usefulness, ease of use, and attitudes towards information technology, including their use of computers and the internet (Pan and Jordan-Marsh 2010 ), as well as differences in technology use between older adults and other age groups (Guner and Acarturk 2020 ). Subsequently, the research focus expanded to improving the quality of life for older adults, exploring how technology can optimize health management and enhance the possibility of independent living, emphasizing the significant role of technology in improving the quality of life for the elderly. With ongoing technological advancements, recent research has shifted towards areas such as “virtual reality,” “telehealth,” and “human-robot interaction,” with a focus on the user experience of older adults (Halim et al. 2022 ). The appearance of keywords such as “physical activity” and “exercise” highlights the value of technology in promoting physical activity and health among older adults. This phase of research tends to make cutting-edge technology genuinely serve the practical needs of older adults, achieving its widespread application in daily life. Additionally, research has focused on expanding and quantifying theoretical models of older adults’ technology acceptance, involving keywords such as “perceived risk”, “validation” and “UTAUT”.

In summary, from 2013 to 2023, the field of older adults’ technology acceptance has evolved from initial explorations of influencing factors, to comprehensive enhancements in quality of life and health management, and further to the application and deepening of theoretical models and cutting-edge technologies. This research not only reflects the diversity and complexity of the field but also demonstrates a comprehensive and in-depth understanding of older adults’ interactions with technology across various life scenarios and needs.

Research quality distribution

To reveal the distribution of research quality in the field of older adults’ technology acceptance, a strategic diagram analysis is employed to calculate and illustrate the internal development and interrelationships among various research themes (Xie et al. 2020 ). The strategic diagram uses Centrality as the X-axis and Density as the Y-axis to divide into four quadrants, where the X-axis represents the strength of the connection between thematic clusters and other themes, with higher values indicating a central position in the research field; the Y-axis indicates the level of development within the thematic clusters, with higher values denoting a more mature and widely recognized field (Li and Zhou 2020 ).

Through cluster analysis and manual verification, this study categorized 61 core keywords (Frequency ≥5) into 11 thematic clusters. Subsequently, based on the keywords covered by each thematic cluster, the research themes and their directions for each cluster were summarized (Table 11 ), and the centrality and density coordinates for each cluster were precisely calculated (Table 12 ). Finally, a strategic diagram of the older adults’ technology acceptance research field was constructed (Fig. 9 ). Based on the distribution of thematic clusters across the quadrants in the strategic diagram, the structure and developmental trends of the field were interpreted.

Classification and visualization of theme clusters based on density and centrality.

As illustrated in Fig. 9 , (1) the theme clusters of #3 Usage Experience and #4 Assisted Living Technology are in the first quadrant, characterized by high centrality and density. Their internal cohesion and close links with other themes indicate their mature development, systematic research content or directions have been formed, and they have a significant influence on other themes. These themes play a central role in the field of older adults’ technology acceptance and have promising prospects. (2) The theme clusters of #6 Smart Devices, #9 Theoretical Models, and #10 Mobile Health Applications are in the second quadrant, with higher density but lower centrality. These themes have strong internal connections but weaker external links, indicating that these three themes have received widespread attention from researchers and have been the subject of related research, but more as self-contained systems and exhibit independence. Therefore, future research should further explore in-depth cooperation and cross-application with other themes. (3) The theme clusters of #7 Human-Robot Interaction, #8 Characteristics of the Elderly, and #11 Research Methods are in the third quadrant, with lower centrality and density. These themes are loosely connected internally and have weak links with others, indicating their developmental immaturity. Compared to other topics, they belong to the lower attention edge and niche themes, and there is a need for further investigation. (4) The theme clusters of #1 Digital Healthcare Technology, #2 Psychological Factors, and #5 Socio-Cultural Factors are located in the fourth quadrant, with high centrality but low density. Although closely associated with other research themes, the internal cohesion within these clusters is relatively weak. This suggests that while these themes are closely linked to other research areas, their own development remains underdeveloped, indicating a core immaturity. Nevertheless, these themes are crucial within the research domain of elderly technology acceptance and possess significant potential for future exploration.

Discussion on distribution power (RQ1)

Over the past decade, academic interest and influence in the area of older adults’ technology acceptance have significantly increased. This trend is evidenced by a quantitative analysis of publication and citation volumes, particularly noticeable in 2019 and 2022, where there was a substantial rise in both metrics. The rise is closely linked to the widespread adoption of emerging technologies such as smart homes, wearable devices, and telemedicine among older adults. While these technologies have enhanced their quality of life, they also pose numerous challenges, sparking extensive research into their acceptance, usage behaviors, and influencing factors among the older adults (Pirzada et al. 2022 ; Garcia Reyes et al. 2023 ). Furthermore, the COVID-19 pandemic led to a surge in technology demand among older adults, especially in areas like medical consultation, online socialization, and health management, further highlighting the importance and challenges of technology. Health risks and social isolation have compelled older adults to rely on technology for daily activities, accelerating its adoption and application within this demographic. This phenomenon has made technology acceptance a critical issue, driving societal and academic focus on the study of technology acceptance among older adults.

The flow of knowledge at the level of high-output disciplines and journals, along with the primary publishing outlets, indicates the highly interdisciplinary nature of research into older adults’ technology acceptance. This reflects the complexity and breadth of issues related to older adults’ technology acceptance, necessitating the integration of multidisciplinary knowledge and approaches. Currently, research is primarily focused on medical health and human-computer interaction, demonstrating academic interest in improving health and quality of life for older adults and addressing the urgent needs related to their interactions with technology. In the field of medical health, research aims to provide advanced and innovative healthcare technologies and services to meet the challenges of an aging population while improving the quality of life for older adults (Abdi et al. 2020 ; Wilson et al. 2021 ). In the field of human-computer interaction, research is focused on developing smarter and more user-friendly interaction models to meet the needs of older adults in the digital age, enabling them to actively participate in social activities and enjoy a higher quality of life (Sayago, 2019 ). These studies are crucial for addressing the challenges faced by aging societies, providing increased support and opportunities for the health, welfare, and social participation of older adults.

Discussion on research power (RQ2)

This study analyzes leading countries and collaboration networks, core institutions and authors, revealing the global research landscape and distribution of research strength in the field of older adults’ technology acceptance, and presents quantitative data on global research trends. From the analysis of country distribution and collaborations, China and the USA hold dominant positions in this field, with developed countries like the UK, Germany, Italy, and the Netherlands also excelling in international cooperation and research influence. The significant investment in technological research and the focus on the technological needs of older adults by many developed countries reflect their rapidly aging societies, policy support, and resource allocation.

China is the only developing country that has become a major contributor in this field, indicating its growing research capabilities and high priority given to aging societies and technological innovation. Additionally, China has close collaborations with countries such as USA, the UK, and Malaysia, driven not only by technological research needs but also by shared challenges and complementarities in aging issues among these nations. For instance, the UK has extensive experience in social welfare and aging research, providing valuable theoretical guidance and practical experience. International collaborations, aimed at addressing the challenges of aging, integrate the strengths of various countries, advancing in-depth and widespread development in the research of technology acceptance among older adults.

At the institutional and author level, City University of Hong Kong leads in publication volume, with research teams led by Chan and Chen demonstrating significant academic activity and contributions. Their research primarily focuses on older adults’ acceptance and usage behaviors of various technologies, including smartphones, smart wearables, and social robots (Chen et al. 2015 ; Li et al. 2019 ; Ma et al. 2016 ). These studies, targeting specific needs and product characteristics of older adults, have developed new models of technology acceptance based on existing frameworks, enhancing the integration of these technologies into their daily lives and laying a foundation for further advancements in the field. Although Tilburg University has a smaller publication output, it holds significant influence in the field of older adults’ technology acceptance. Particularly, the high citation rate of Peek’s studies highlights their excellence in research. Peek extensively explored older adults’ acceptance and usage of home care technologies, revealing the complexity and dynamics of their technology use behaviors. His research spans from identifying systemic influencing factors (Peek et al. 2014 ; Peek et al. 2016 ), emphasizing familial impacts (Luijkx et al. 2015 ), to constructing comprehensive models (Peek et al. 2017 ), and examining the dynamics of long-term usage (Peek et al. 2019 ), fully reflecting the evolving technology landscape and the changing needs of older adults. Additionally, the ongoing contributions of researchers like Ziefle, Rogers, and Wouters in the field of older adults’ technology acceptance demonstrate their research influence and leadership. These researchers have significantly enriched the knowledge base in this area with their diverse perspectives. For instance, Ziefle has uncovered the complex attitudes of older adults towards technology usage, especially the trade-offs between privacy and security, and how different types of activities affect their privacy needs (Maidhof et al. 2023 ; Mujirishvili et al. 2023 ; Schomakers and Ziefle 2023 ; Wilkowska et al. 2022 ), reflecting a deep exploration and ongoing innovation in the field of older adults’ technology acceptance.

Discussion on knowledge base and thematic progress (RQ3)

Through co-citation analysis and systematic review of seminal literature, this study reveals the knowledge foundation and thematic progress in the field of older adults’ technology acceptance. Co-citation networks and cluster analyses illustrate the structural themes of the research, delineating the differentiation and boundaries within this field. Additionally, burst detection analysis offers a valuable perspective for understanding the thematic evolution in the field of technology acceptance among older adults. The development and innovation of theoretical models are foundational to this research. Researchers enhance the explanatory power of constructed models by deepening and expanding existing technology acceptance theories to address theoretical limitations. For instance, Heerink et al. ( 2010 ) modified and expanded the UTAUT model by integrating functional assessment and social interaction variables to create the almere model. This model significantly enhances the ability to explain the intentions of older users in utilizing assistive social agents and improves the explanation of actual usage behaviors. Additionally, Chen and Chan ( 2014 ) extended the TAM to include age-related health and capability features of older adults, creating the STAM, which substantially improves predictions of older adults’ technology usage behaviors. Personal attributes, health and capability features, and facilitating conditions have a direct impact on technology acceptance. These factors more effectively predict older adults’ technology usage behaviors than traditional attitudinal factors.

With the advancement of technology and the application of emerging technologies, new research topics have emerged, increasingly focusing on older adults’ acceptance and use of these technologies. Prior to this, the study by Mitzner et al. ( 2010 ) challenged the stereotype of older adults’ conservative attitudes towards technology, highlighting the central roles of usability and usefulness in the technology acceptance process. This discovery laid an important foundation for subsequent research. Research fields such as “smart home technology,” “social life,” and “customer service” are emerging, indicating a shift in focus towards the practical and social applications of technology in older adults’ lives. Research not only focuses on the technology itself but also on how these technologies integrate into older adults’ daily lives and how they can improve the quality of life through technology. For instance, studies such as those by Ma et al. ( 2016 ), Hoque and Sorwar ( 2017 ), and Li et al. ( 2019 ) have explored factors influencing older adults’ use of smartphones, mHealth, and smart wearable devices.

Furthermore, the diversification of research methodologies and innovation in evaluation techniques, such as the use of mixed methods, structural equation modeling (SEM), and neural network (NN) approaches, have enhanced the rigor and reliability of the findings, enabling more precise identification of the factors and mechanisms influencing technology acceptance. Talukder et al. ( 2020 ) employed an effective multimethodological strategy by integrating SEM and NN to leverage the complementary strengths of both approaches, thus overcoming their individual limitations and more accurately analyzing and predicting older adults’ acceptance of wearable health technologies (WHT). SEM is utilized to assess the determinants’ impact on the adoption of WHT, while neural network models validate SEM outcomes and predict the significance of key determinants. This combined approach not only boosts the models’ reliability and explanatory power but also provides a nuanced understanding of the motivations and barriers behind older adults’ acceptance of WHT, offering deep research insights.

Overall, co-citation analysis of the literature in the field of older adults’ technology acceptance has uncovered deeper theoretical modeling and empirical studies on emerging technologies, while emphasizing the importance of research methodological and evaluation innovations in understanding complex social science issues. These findings are crucial for guiding the design and marketing strategies of future technology products, especially in the rapidly growing market of older adults.

Discussion on research hotspots and evolutionary trends (RQ4)

By analyzing core keywords, we can gain deep insights into the hot topics, evolutionary trends, and quality distribution of research in the field of older adults’ technology acceptance. The frequent occurrence of the keywords “TAM” and “UTAUT” indicates that the applicability and theoretical extension of existing technology acceptance models among older adults remain a focal point in academia. This phenomenon underscores the enduring influence of the studies by Davis ( 1989 ) and Venkatesh et al. ( 2003 ), whose models provide a robust theoretical framework for explaining and predicting older adults’ acceptance and usage of emerging technologies. With the widespread application of artificial intelligence (AI) and big data technologies, these theoretical models have incorporated new variables such as perceived risk, trust, and privacy issues (Amin et al. 2024 ; Chen et al. 2024 ; Jing et al. 2024b ; Seibert et al. 2021 ; Wang et al. 2024b ), advancing the theoretical depth and empirical research in this field.

Keyword co-occurrence cluster analysis has revealed multiple research hotspots in the field, including factors influencing technology adoption, interactive experiences between older adults and assistive technologies, the application of mobile health technology in health management, and technology-assisted home care. These studies primarily focus on enhancing the quality of life and health management of older adults through emerging technologies, particularly in the areas of ambient assisted living, smart health monitoring, and intelligent medical care. In these domains, the role of AI technology is increasingly significant (Qian et al. 2021 ; Ho 2020 ). With the evolution of next-generation information technologies, AI is increasingly integrated into elder care systems, offering intelligent, efficient, and personalized service solutions by analyzing the lifestyles and health conditions of older adults. This integration aims to enhance older adults’ quality of life in aspects such as health monitoring and alerts, rehabilitation assistance, daily health management, and emotional support (Lee et al. 2023 ). A survey indicates that 83% of older adults prefer AI-driven solutions when selecting smart products, demonstrating the increasing acceptance of AI in elder care (Zhao and Li 2024 ). Integrating AI into elder care presents both opportunities and challenges, particularly in terms of user acceptance, trust, and long-term usage effects, which warrant further exploration (Mhlanga 2023 ). These studies will help better understand the profound impact of AI technology on the lifestyles of older adults and provide critical references for optimizing AI-driven elder care services.

The Time-zone evolution mapping and burst keyword analysis further reveal the evolutionary trends of research hotspots. Early studies focused on basic technology acceptance models and user perceptions, later expanding to include quality of life and health management. In recent years, research has increasingly focused on cutting-edge technologies such as virtual reality, telehealth, and human-robot interaction, with a concurrent emphasis on the user experience of older adults. This evolutionary process demonstrates a deepening shift from theoretical models to practical applications, underscoring the significant role of technology in enhancing the quality of life for older adults. Furthermore, the strategic coordinate mapping analysis clearly demonstrates the development and mutual influence of different research themes. High centrality and density in the themes of Usage Experience and Assisted Living Technology indicate their mature research status and significant impact on other themes. The themes of Smart Devices, Theoretical Models, and Mobile Health Applications demonstrate self-contained research trends. The themes of Human-Robot Interaction, Characteristics of the Elderly, and Research Methods are not yet mature, but they hold potential for development. Themes of Digital Healthcare Technology, Psychological Factors, and Socio-Cultural Factors are closely related to other themes, displaying core immaturity but significant potential.

In summary, the research hotspots in the field of older adults’ technology acceptance are diverse and dynamic, demonstrating the academic community’s profound understanding of how older adults interact with technology across various life contexts and needs. Under the influence of AI and big data, research should continue to focus on the application of emerging technologies among older adults, exploring in depth how they adapt to and effectively use these technologies. This not only enhances the quality of life and healthcare experiences for older adults but also drives ongoing innovation and development in this field.

Research agenda

Based on the above research findings, to further understand and promote technology acceptance and usage among older adults, we recommend future studies focus on refining theoretical models, exploring long-term usage, and assessing user experience in the following detailed aspects:

Refinement and validation of specific technology acceptance models for older adults: Future research should focus on developing and validating technology acceptance models based on individual characteristics, particularly considering variations in technology acceptance among older adults across different educational levels and cultural backgrounds. This includes factors such as age, gender, educational background, and cultural differences. Additionally, research should examine how well specific technologies, such as wearable devices and mobile health applications, meet the needs of older adults. Building on existing theoretical models, this research should integrate insights from multiple disciplines such as psychology, sociology, design, and engineering through interdisciplinary collaboration to create more accurate and comprehensive models, which should then be validated in relevant contexts.

Deepening the exploration of the relationship between long-term technology use and quality of life among older adults: The acceptance and use of technology by users is a complex and dynamic process (Seuwou et al. 2016 ). Existing research predominantly focuses on older adults’ initial acceptance or short-term use of new technologies; however, the impact of long-term use on their quality of life and health is more significant. Future research should focus on the evolution of older adults’ experiences and needs during long-term technology usage, and the enduring effects of technology on their social interactions, mental health, and life satisfaction. Through longitudinal studies and qualitative analysis, this research reveals the specific needs and challenges of older adults in long-term technology use, providing a basis for developing technologies and strategies that better meet their requirements. This understanding aids in comprehensively assessing the impact of technology on older adults’ quality of life and guiding the optimization and improvement of technological products.

Evaluating the Importance of User Experience in Research on Older Adults’ Technology Acceptance: Understanding the mechanisms of information technology acceptance and use is central to human-computer interaction research. Although technology acceptance models and user experience models differ in objectives, they share many potential intersections. Technology acceptance research focuses on structured prediction and assessment, while user experience research concentrates on interpreting design impacts and new frameworks. Integrating user experience to assess older adults’ acceptance of technology products and systems is crucial (Codfrey et al. 2022 ; Wang et al. 2019 ), particularly for older users, where specific product designs should emphasize practicality and usability (Fisk et al. 2020 ). Researchers need to explore innovative age-appropriate design methods to enhance older adults’ usage experience. This includes studying older users’ actual usage preferences and behaviors, optimizing user interfaces, and interaction designs. Integrating feedback from older adults to tailor products to their needs can further promote their acceptance and continued use of technology products.

Conclusions

This study conducted a systematic review of the literature on older adults’ technology acceptance over the past decade through bibliometric analysis, focusing on the distribution power, research power, knowledge base and theme progress, research hotspots, evolutionary trends, and quality distribution. Using a combination of quantitative and qualitative methods, this study has reached the following conclusions:

Technology acceptance among older adults has become a hot topic in the international academic community, involving the integration of knowledge across multiple disciplines, including Medical Informatics, Health Care Sciences Services, and Ergonomics. In terms of journals, “PSYCHOLOGY, EDUCATION, HEALTH” represents a leading field, with key publications including Computers in Human Behavior , Journal of Medical Internet Research , and International Journal of Human-Computer Interaction . These journals possess significant academic authority and extensive influence in the field.

Research on technology acceptance among older adults is particularly active in developed countries, with China and USA publishing significantly more than other nations. The Netherlands leads in high average citation rates, indicating the depth and impact of its research. Meanwhile, the UK stands out in terms of international collaboration. At the institutional level, City University of Hong Kong and The University of Hong Kong in China are in leading positions. Tilburg University in the Netherlands demonstrates exceptional research quality through its high average citation count. At the author level, Chen from China has the highest number of publications, while Peek from the Netherlands has the highest average citation count.

Co-citation analysis of references indicates that the knowledge base in this field is divided into three main categories: theoretical model deepening, emerging technology applications, and research methods and evaluation. Seminal literature focuses on four areas: specific technology use by older adults, expansion of theoretical models of technology acceptance, information technology adoption behavior, and research perspectives. Research themes have evolved from initial theoretical deepening and analysis of influencing factors to empirical studies on individual factors and emerging technologies.

Keyword analysis indicates that TAM and UTAUT are the most frequently occurring terms, while “assistive technology” and “virtual reality” are focal points with high frequency and centrality. Keyword clustering analysis reveals that research hotspots are concentrated on the influencing factors of technology adoption, human-robot interaction experiences, mobile health management, and technology for aging in place. Time-zone evolution mapping and burst keyword analysis have revealed the research evolution from preliminary exploration of influencing factors, to enhancements in quality of life and health management, and onto advanced technology applications and deepening of theoretical models. Furthermore, analysis of research quality distribution indicates that Usage Experience and Assisted Living Technology have become core topics, while Smart Devices, Theoretical Models, and Mobile Health Applications point towards future research directions.

Through this study, we have systematically reviewed the dynamics, core issues, and evolutionary trends in the field of older adults’ technology acceptance, constructing a comprehensive Knowledge Mapping of the domain and presenting a clear framework of existing research. This not only lays the foundation for subsequent theoretical discussions and innovative applications in the field but also provides an important reference for relevant scholars.

Limitations

To our knowledge, this is the first bibliometric analysis concerning technology acceptance among older adults, and we adhered strictly to bibliometric standards throughout our research. However, this study relies on the Web of Science Core Collection, and while its authority and breadth are widely recognized, this choice may have missed relevant literature published in other significant databases such as PubMed, Scopus, and Google Scholar, potentially overlooking some critical academic contributions. Moreover, given that our analysis was confined to literature in English, it may not reflect studies published in other languages, somewhat limiting the global representativeness of our data sample.

It is noteworthy that with the rapid development of AI technology, its increasingly widespread application in elderly care services is significantly transforming traditional care models. AI is profoundly altering the lifestyles of the elderly, from health monitoring and smart diagnostics to intelligent home systems and personalized care, significantly enhancing their quality of life and health care standards. The potential for AI technology within the elderly population is immense, and research in this area is rapidly expanding. However, due to the restrictive nature of the search terms used in this study, it did not fully cover research in this critical area, particularly in addressing key issues such as trust, privacy, and ethics.

Consequently, future research should not only expand data sources, incorporating multilingual and multidatabase literature, but also particularly focus on exploring older adults’ acceptance of AI technology and its applications, in order to construct a more comprehensive academic landscape of older adults’ technology acceptance, thereby enriching and extending the knowledge system and academic trends in this field.

Data availability

The datasets analyzed during the current study are available in the Dataverse repository: https://doi.org/10.7910/DVN/6K0GJH .

Abdi S, de Witte L, Hawley M (2020) Emerging technologies with potential care and support applications for older people: review of gray literature. JMIR Aging 3(2):e17286. https://doi.org/10.2196/17286

Article   PubMed   PubMed Central   Google Scholar  

Achuthan K, Nair VK, Kowalski R, Ramanathan S, Raman R (2023) Cyberbullying research—Alignment to sustainable development and impact of COVID-19: Bibliometrics and science mapping analysis. Comput Human Behav 140:107566. https://doi.org/10.1016/j.chb.2022.107566

Article   Google Scholar  

Ahmad A, Mozelius P (2022) Human-Computer Interaction for Older Adults: a Literature Review on Technology Acceptance of eHealth Systems. J Eng Res Sci 1(4):119–126. https://doi.org/10.55708/js0104014

Ale Ebrahim N, Salehi H, Embi MA, Habibi F, Gholizadeh H, Motahar SM (2014) Visibility and citation impact. Int Educ Stud 7(4):120–125. https://doi.org/10.5539/ies.v7n4p120

Amin MS, Johnson VL, Prybutok V, Koh CE (2024) An investigation into factors affecting the willingness to disclose personal health information when using AI-enabled caregiver robots. Ind Manag Data Syst 124(4):1677–1699. https://doi.org/10.1108/IMDS-09-2023-0608

Baer NR, Vietzke J, Schenk L (2022) Middle-aged and older adults’ acceptance of mobile nutrition and fitness apps: a systematic mixed studies review. PLoS One 17(12):e0278879. https://doi.org/10.1371/journal.pone.0278879

Barnard Y, Bradley MD, Hodgson F, Lloyd AD (2013) Learning to use new technologies by older adults: Perceived difficulties, experimentation behaviour and usability. Comput Human Behav 29(4):1715–1724. https://doi.org/10.1016/j.chb.2013.02.006

Berkowsky RW, Sharit J, Czaja SJ (2017) Factors predicting decisions about technology adoption among older adults. Innov Aging 3(1):igy002. https://doi.org/10.1093/geroni/igy002

Braun MT (2013) Obstacles to social networking website use among older adults. Comput Human Behav 29(3):673–680. https://doi.org/10.1016/j.chb.2012.12.004

Article   MathSciNet   Google Scholar  

Campo-Prieto P, Rodríguez-Fuentes G, Cancela-Carral JM (2021) Immersive virtual reality exergame promotes the practice of physical activity in older people: An opportunity during COVID-19. Multimodal Technol Interact 5(9):52. https://doi.org/10.3390/mti5090052

Chen C (2006) CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. J Am Soc Inf Sci Technol 57(3):359–377. https://doi.org/10.1002/asi.20317

Chen C, Dubin R, Kim MC (2014) Emerging trends and new developments in regenerative medicine: a scientometric update (2000–2014). Expert Opin Biol Ther 14(9):1295–1317. https://doi.org/10.1517/14712598.2014.920813

Article   PubMed   Google Scholar  

Chen C, Leydesdorff L (2014) Patterns of connections and movements in dual‐map overlays: A new method of publication portfolio analysis. J Assoc Inf Sci Technol 65(2):334–351. https://doi.org/10.1002/asi.22968

Chen J, Wang C, Tang Y (2022) Knowledge mapping of volunteer motivation: A bibliometric analysis and cross-cultural comparative study. Front Psychol 13:883150. https://doi.org/10.3389/fpsyg.2022.883150

Chen JY, Liu YD, Dai J, Wang CL (2023) Development and status of moral education research: Visual analysis based on knowledge graph. Front Psychol 13:1079955. https://doi.org/10.3389/fpsyg.2022.1079955

Chen K, Chan AH (2011) A review of technology acceptance by older adults. Gerontechnology 10(1):1–12. https://doi.org/10.4017/gt.2011.10.01.006.00

Chen K, Chan AH (2014) Gerontechnology acceptance by elderly Hong Kong Chinese: a senior technology acceptance model (STAM). Ergonomics 57(5):635–652. https://doi.org/10.1080/00140139.2014.895855

Chen K, Zhang Y, Fu X (2019) International research collaboration: An emerging domain of innovation studies? Res Policy 48(1):149–168. https://doi.org/10.1016/j.respol.2018.08.005

Chen X, Hu Z, Wang C (2024) Empowering education development through AIGC: A systematic literature review. Educ Inf Technol 1–53. https://doi.org/10.1007/s10639-024-12549-7

Chen Y, Chen CM, Liu ZY, Hu ZG, Wang XW (2015) The methodology function of CiteSpace mapping knowledge domains. Stud Sci Sci 33(2):242–253. https://doi.org/10.16192/j.cnki.1003-2053.2015.02.009

Codfrey GS, Baharum A, Zain NHM, Omar M, Deris FD (2022) User Experience in Product Design and Development: Perspectives and Strategies. Math Stat Eng Appl 71(2):257–262. https://doi.org/10.17762/msea.v71i2.83

Dai J, Zhang X, Wang CL (2024) A meta-analysis of learners’ continuance intention toward online education platforms. Educ Inf Technol 1–36. https://doi.org/10.1007/s10639-024-12654-7

Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q 13(3):319–340. https://doi.org/10.2307/249008

Delmastro F, Dolciotti C, Palumbo F, Magrini M, Di Martino F, La Rosa D, Barcaro U (2018) Long-term care: how to improve the quality of life with mobile and e-health services. In 2018 14th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), pp. 12–19. IEEE. https://doi.org/10.1109/WiMOB.2018.8589157

Dupuis K, Tsotsos LE (2018) Technology for remote health monitoring in an older population: a role for mobile devices. Multimodal Technol Interact 2(3):43. https://doi.org/10.3390/mti2030043

Ferguson C, Hickman LD, Turkmani S, Breen P, Gargiulo G, Inglis SC (2021) Wearables only work on patients that wear them”: Barriers and facilitators to the adoption of wearable cardiac monitoring technologies. Cardiovasc Digit Health J 2(2):137–147. https://doi.org/10.1016/j.cvdhj.2021.02.001

Fisk AD, Czaja SJ, Rogers WA, Charness N, Sharit J (2020) Designing for older adults: Principles and creative human factors approaches. CRC Press. https://doi.org/10.1201/9781420080681

Friesen S, Brémault-Phillips S, Rudrum L, Rogers LG (2016) Environmental design that supports healthy aging: Evaluating a new supportive living facility. J Hous Elderly 30(1):18–34. https://doi.org/10.1080/02763893.2015.1129380

Garcia Reyes EP, Kelly R, Buchanan G, Waycott J (2023) Understanding Older Adults’ Experiences With Technologies for Health Self-management: Interview Study. JMIR Aging 6:e43197. https://doi.org/10.2196/43197

Geng Z, Wang J, Liu J, Miao J (2024) Bibliometric analysis of the development, current status, and trends in adult degenerative scoliosis research: A systematic review from 1998 to 2023. J Pain Res 17:153–169. https://doi.org/10.2147/JPR.S437575

González A, Ramírez MP, Viadel V (2012) Attitudes of the elderly toward information and communications technologies. Educ Gerontol 38(9):585–594. https://doi.org/10.1080/03601277.2011.595314

Guner H, Acarturk C (2020) The use and acceptance of ICT by senior citizens: a comparison of technology acceptance model (TAM) for elderly and young adults. Univ Access Inf Soc 19(2):311–330. https://doi.org/10.1007/s10209-018-0642-4

Halim I, Saptari A, Perumal PA, Abdullah Z, Abdullah S, Muhammad MN (2022) A Review on Usability and User Experience of Assistive Social Robots for Older Persons. Int J Integr Eng 14(6):102–124. https://penerbit.uthm.edu.my/ojs/index.php/ijie/article/view/8566

He Y, He Q, Liu Q (2022) Technology acceptance in socially assistive robots: Scoping review of models, measurement, and influencing factors. J Healthc Eng 2022(1):6334732. https://doi.org/10.1155/2022/6334732

Heerink M, Kröse B, Evers V, Wielinga B (2010) Assessing acceptance of assistive social agent technology by older adults: the almere model. Int J Soc Robot 2:361–375. https://doi.org/10.1007/s12369-010-0068-5

Ho A (2020) Are we ready for artificial intelligence health monitoring in elder care? BMC Geriatr 20(1):358. https://doi.org/10.1186/s12877-020-01764-9

Hoque R, Sorwar G (2017) Understanding factors influencing the adoption of mHealth by the elderly: An extension of the UTAUT model. Int J Med Inform 101:75–84. https://doi.org/10.1016/j.ijmedinf.2017.02.002

Hota PK, Subramanian B, Narayanamurthy G (2020) Mapping the intellectual structure of social entrepreneurship research: A citation/co-citation analysis. J Bus Ethics 166(1):89–114. https://doi.org/10.1007/s10551-019-04129-4

Huang R, Yan P, Yang X (2021) Knowledge map visualization of technology hotspots and development trends in China’s textile manufacturing industry. IET Collab Intell Manuf 3(3):243–251. https://doi.org/10.1049/cim2.12024

Article   ADS   Google Scholar  

Jing Y, Wang C, Chen Y, Wang H, Yu T, Shadiev R (2023) Bibliometric mapping techniques in educational technology research: A systematic literature review. Educ Inf Technol 1–29. https://doi.org/10.1007/s10639-023-12178-6

Jing YH, Wang CL, Chen ZY, Shen SS, Shadiev R (2024a) A Bibliometric Analysis of Studies on Technology-Supported Learning Environments: Hotopics and Frontier Evolution. J Comput Assist Learn 1–16. https://doi.org/10.1111/jcal.12934

Jing YH, Wang HM, Chen XJ, Wang CL (2024b) What factors will affect the effectiveness of using ChatGPT to solve programming problems? A quasi-experimental study. Humanit Soc Sci Commun 11:319. https://doi.org/10.1057/s41599-024-02751-w

Kamrani P, Dorsch I, Stock WG (2021) Do researchers know what the h-index is? And how do they estimate its importance? Scientometrics 126(7):5489–5508. https://doi.org/10.1007/s11192-021-03968-1

Kim HS, Lee KH, Kim H, Kim JH (2014) Using mobile phones in healthcare management for the elderly. Maturitas 79(4):381–388. https://doi.org/10.1016/j.maturitas.2014.08.013

Article   MathSciNet   PubMed   Google Scholar  

Kleinberg J (2002) Bursty and hierarchical structure in streams. In Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 91–101. https://doi.org/10.1145/775047.775061

Kruse C, Fohn J, Wilson N, Patlan EN, Zipp S, Mileski M (2020) Utilization barriers and medical outcomes commensurate with the use of telehealth among older adults: systematic review. JMIR Med Inform 8(8):e20359. https://doi.org/10.2196/20359

Kumar S, Lim WM, Pandey N, Christopher Westland J (2021) 20 years of electronic commerce research. Electron Commer Res 21:1–40. https://doi.org/10.1007/s10660-021-09464-1

Kwiek M (2021) What large-scale publication and citation data tell us about international research collaboration in Europe: Changing national patterns in global contexts. Stud High Educ 46(12):2629–2649. https://doi.org/10.1080/03075079.2020.1749254

Lee C, Coughlin JF (2015) PERSPECTIVE: Older adults’ adoption of technology: an integrated approach to identifying determinants and barriers. J Prod Innov Manag 32(5):747–759. https://doi.org/10.1111/jpim.12176

Lee CH, Wang C, Fan X, Li F, Chen CH (2023) Artificial intelligence-enabled digital transformation in elderly healthcare field: scoping review. Adv Eng Inform 55:101874. https://doi.org/10.1016/j.aei.2023.101874

Leydesdorff L, Rafols I (2012) Interactive overlays: A new method for generating global journal maps from Web-of-Science data. J Informetr 6(2):318–332. https://doi.org/10.1016/j.joi.2011.11.003

Li J, Ma Q, Chan AH, Man S (2019) Health monitoring through wearable technologies for older adults: Smart wearables acceptance model. Appl Ergon 75:162–169. https://doi.org/10.1016/j.apergo.2018.10.006

Article   ADS   PubMed   Google Scholar  

Li X, Zhou D (2020) Product design requirement information visualization approach for intelligent manufacturing services. China Mech Eng 31(07):871, http://www.cmemo.org.cn/EN/Y2020/V31/I07/871

Google Scholar  

Lin Y, Yu Z (2024a) An integrated bibliometric analysis and systematic review modelling students’ technostress in higher education. Behav Inf Technol 1–25. https://doi.org/10.1080/0144929X.2024.2332458

Lin Y, Yu Z (2024b) A bibliometric analysis of artificial intelligence chatbots in educational contexts. Interact Technol Smart Educ 21(2):189–213. https://doi.org/10.1108/ITSE-12-2022-0165

Liu L, Duffy VG (2023) Exploring the future development of Artificial Intelligence (AI) applications in chatbots: a bibliometric analysis. Int J Soc Robot 15(5):703–716. https://doi.org/10.1007/s12369-022-00956-0

Liu R, Li X, Chu J (2022) Evolution of applied variables in the research on technology acceptance of the elderly. In: International Conference on Human-Computer Interaction, Cham: Springer International Publishing, pp 500–520. https://doi.org/10.1007/978-3-031-05581-23_5

Luijkx K, Peek S, Wouters E (2015) “Grandma, you should do it—It’s cool” Older Adults and the Role of Family Members in Their Acceptance of Technology. Int J Environ Res Public Health 12(12):15470–15485. https://doi.org/10.3390/ijerph121214999

Lussier M, Lavoie M, Giroux S, Consel C, Guay M, Macoir J, Bier N (2018) Early detection of mild cognitive impairment with in-home monitoring sensor technologies using functional measures: a systematic review. IEEE J Biomed Health Inform 23(2):838–847. https://doi.org/10.1109/JBHI.2018.2834317

López-Robles JR, Otegi-Olaso JR, Porto Gomez I, Gamboa-Rosales NK, Gamboa-Rosales H, Robles-Berumen H (2018) Bibliometric network analysis to identify the intellectual structure and evolution of the big data research field. In: International Conference on Intelligent Data Engineering and Automated Learning, Cham: Springer International Publishing, pp 113–120. https://doi.org/10.1007/978-3-030-03496-2_13

Ma Q, Chan AH, Chen K (2016) Personal and other factors affecting acceptance of smartphone technology by older Chinese adults. Appl Ergon 54:62–71. https://doi.org/10.1016/j.apergo.2015.11.015

Ma Q, Chan AHS, Teh PL (2021) Insights into Older Adults’ Technology Acceptance through Meta-Analysis. Int J Hum-Comput Interact 37(11):1049–1062. https://doi.org/10.1080/10447318.2020.1865005

Macedo IM (2017) Predicting the acceptance and use of information and communication technology by older adults: An empirical examination of the revised UTAUT2. Comput Human Behav 75:935–948. https://doi.org/10.1016/j.chb.2017.06.013

Maidhof C, Offermann J, Ziefle M (2023) Eyes on privacy: acceptance of video-based AAL impacted by activities being filmed. Front Public Health 11:1186944. https://doi.org/10.3389/fpubh.2023.1186944

Majumder S, Aghayi E, Noferesti M, Memarzadeh-Tehran H, Mondal T, Pang Z, Deen MJ (2017) Smart homes for elderly healthcare—Recent advances and research challenges. Sensors 17(11):2496. https://doi.org/10.3390/s17112496

Article   ADS   PubMed   PubMed Central   Google Scholar  

Mhlanga D (2023) Artificial Intelligence in elderly care: Navigating ethical and responsible AI adoption for seniors. Available at SSRN 4675564. 4675564 min) Identifying citation patterns of scientific breakthroughs: A perspective of dynamic citation process. Inf Process Manag 58(1):102428. https://doi.org/10.1016/j.ipm.2020.102428

Mitzner TL, Boron JB, Fausset CB, Adams AE, Charness N, Czaja SJ, Sharit J (2010) Older adults talk technology: Technology usage and attitudes. Comput Human Behav 26(6):1710–1721. https://doi.org/10.1016/j.chb.2010.06.020

Mitzner TL, Savla J, Boot WR, Sharit J, Charness N, Czaja SJ, Rogers WA (2019) Technology adoption by older adults: Findings from the PRISM trial. Gerontologist 59(1):34–44. https://doi.org/10.1093/geront/gny113

Mongeon P, Paul-Hus A (2016) The journal coverage of Web of Science and Scopus: a comparative analysis. Scientometrics 106:213–228. https://doi.org/10.1007/s11192-015-1765-5

Mostaghel R (2016) Innovation and technology for the elderly: Systematic literature review. J Bus Res 69(11):4896–4900. https://doi.org/10.1016/j.jbusres.2016.04.049

Mujirishvili T, Maidhof C, Florez-Revuelta F, Ziefle M, Richart-Martinez M, Cabrero-García J (2023) Acceptance and privacy perceptions toward video-based active and assisted living technologies: Scoping review. J Med Internet Res 25:e45297. https://doi.org/10.2196/45297

Naseri RNN, Azis SN, Abas N (2023) A Review of Technology Acceptance and Adoption Models in Consumer Study. FIRM J Manage Stud 8(2):188–199. https://doi.org/10.33021/firm.v8i2.4536

Nguyen UP, Hallinger P (2020) Assessing the distinctive contributions of Simulation & Gaming to the literature, 1970–2019: A bibliometric review. Simul Gaming 51(6):744–769. https://doi.org/10.1177/1046878120941569

Olmedo-Aguirre JO, Reyes-Campos J, Alor-Hernández G, Machorro-Cano I, Rodríguez-Mazahua L, Sánchez-Cervantes JL (2022) Remote healthcare for elderly people using wearables: A review. Biosensors 12(2):73. https://doi.org/10.3390/bios12020073

Pan S, Jordan-Marsh M (2010) Internet use intention and adoption among Chinese older adults: From the expanded technology acceptance model perspective. Comput Human Behav 26(5):1111–1119. https://doi.org/10.1016/j.chb.2010.03.015

Pan X, Yan E, Cui M, Hua W (2018) Examining the usage, citation, and diffusion patterns of bibliometric map software: A comparative study of three tools. J Informetr 12(2):481–493. https://doi.org/10.1016/j.joi.2018.03.005

Park JS, Kim NR, Han EJ (2018) Analysis of trends in science and technology using keyword network analysis. J Korea Ind Inf Syst Res 23(2):63–73. https://doi.org/10.9723/jksiis.2018.23.2.063

Peek ST, Luijkx KG, Rijnaard MD, Nieboer ME, Van Der Voort CS, Aarts S, Wouters EJ (2016) Older adults’ reasons for using technology while aging in place. Gerontology 62(2):226–237. https://doi.org/10.1159/000430949

Peek ST, Luijkx KG, Vrijhoef HJ, Nieboer ME, Aarts S, van der Voort CS, Wouters EJ (2017) Origins and consequences of technology acquirement by independent-living seniors: Towards an integrative model. BMC Geriatr 17:1–18. https://doi.org/10.1186/s12877-017-0582-5

Peek ST, Wouters EJ, Van Hoof J, Luijkx KG, Boeije HR, Vrijhoef HJ (2014) Factors influencing acceptance of technology for aging in place: a systematic review. Int J Med Inform 83(4):235–248. https://doi.org/10.1016/j.ijmedinf.2014.01.004

Peek STM, Luijkx KG, Vrijhoef HJM, Nieboer ME, Aarts S, Van Der Voort CS, Wouters EJM (2019) Understanding changes and stability in the long-term use of technologies by seniors who are aging in place: a dynamical framework. BMC Geriatr 19:1–13. https://doi.org/10.1186/s12877-019-1241-9

Perez AJ, Siddiqui F, Zeadally S, Lane D (2023) A review of IoT systems to enable independence for the elderly and disabled individuals. Internet Things 21:100653. https://doi.org/10.1016/j.iot.2022.100653

Piau A, Wild K, Mattek N, Kaye J (2019) Current state of digital biomarker technologies for real-life, home-based monitoring of cognitive function for mild cognitive impairment to mild Alzheimer disease and implications for clinical care: systematic review. J Med Internet Res 21(8):e12785. https://doi.org/10.2196/12785

Pirzada P, Wilde A, Doherty GH, Harris-Birtill D (2022) Ethics and acceptance of smart homes for older adults. Inform Health Soc Care 47(1):10–37. https://doi.org/10.1080/17538157.2021.1923500

Pranckutė R (2021) Web of Science (WoS) and Scopus: The titans of bibliographic information in today’s academic world. Publications 9(1):12. https://doi.org/10.3390/publications9010012

Qian K, Zhang Z, Yamamoto Y, Schuller BW (2021) Artificial intelligence internet of things for the elderly: From assisted living to health-care monitoring. IEEE Signal Process Mag 38(4):78–88. https://doi.org/10.1109/MSP.2021.3057298

Redner S (1998) How popular is your paper? An empirical study of the citation distribution. Eur Phys J B-Condens Matter Complex Syst 4(2):131–134. https://doi.org/10.1007/s100510050359

Sayago S (ed.) (2019) Perspectives on human-computer interaction research with older people. Switzerland: Springer International Publishing. https://doi.org/10.1007/978-3-030-06076-3

Schomakers EM, Ziefle M (2023) Privacy vs. security: trade-offs in the acceptance of smart technologies for aging-in-place. Int J Hum Comput Interact 39(5):1043–1058. https://doi.org/10.1080/10447318.2022.2078463

Schroeder T, Dodds L, Georgiou A, Gewald H, Siette J (2023) Older adults and new technology: Mapping review of the factors associated with older adults’ intention to adopt digital technologies. JMIR Aging 6(1):e44564. https://doi.org/10.2196/44564

Seibert K, Domhoff D, Bruch D, Schulte-Althoff M, Fürstenau D, Biessmann F, Wolf-Ostermann K (2021) Application scenarios for artificial intelligence in nursing care: rapid review. J Med Internet Res 23(11):e26522. https://doi.org/10.2196/26522

Seuwou P, Banissi E, Ubakanma G (2016) User acceptance of information technology: A critical review of technology acceptance models and the decision to invest in Information Security. In: Global Security, Safety and Sustainability-The Security Challenges of the Connected World: 11th International Conference, ICGS3 2017, London, UK, January 18-20, 2017, Proceedings 11:230-251. Springer International Publishing. https://doi.org/10.1007/978-3-319-51064-4_19

Shiau WL, Wang X, Zheng F (2023) What are the trend and core knowledge of information security? A citation and co-citation analysis. Inf Manag 60(3):103774. https://doi.org/10.1016/j.im.2023.103774

Sinha S, Verma A, Tiwari P (2021) Technology: Saving and enriching life during COVID-19. Front Psychol 12:647681. https://doi.org/10.3389/fpsyg.2021.647681

Soar J (2010) The potential of information and communication technologies to support ageing and independent living. Ann Telecommun 65:479–483. https://doi.org/10.1007/s12243-010-0167-1

Strotmann A, Zhao D (2012) Author name disambiguation: What difference does it make in author‐based citation analysis? J Am Soc Inf Sci Technol 63(9):1820–1833. https://doi.org/10.1002/asi.22695

Talukder MS, Sorwar G, Bao Y, Ahmed JU, Palash MAS (2020) Predicting antecedents of wearable healthcare technology acceptance by elderly: A combined SEM-Neural Network approach. Technol Forecast Soc Change 150:119793. https://doi.org/10.1016/j.techfore.2019.119793

Taskin Z, Al U (2019) Natural language processing applications in library and information science. Online Inf Rev 43(4):676–690. https://doi.org/10.1108/oir-07-2018-0217

Touqeer H, Zaman S, Amin R, Hussain M, Al-Turjman F, Bilal M (2021) Smart home security: challenges, issues and solutions at different IoT layers. J Supercomput 77(12):14053–14089. https://doi.org/10.1007/s11227-021-03825-1

United Nations Department of Economic and Social Affairs (2023) World population ageing 2023: Highlights. https://www.un.org/zh/193220

Valk CAL, Lu Y, Randriambelonoro M, Jessen J (2018) Designing for technology acceptance of wearable and mobile technologies for senior citizen users. In: 21st DMI: Academic Design Management Conference (ADMC 2018), Design Management Institute, pp 1361–1373. https://www.dmi.org/page/ADMC2018

Van Eck N, Waltman L (2010) Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 84(2):523–538. https://doi.org/10.1007/s11192-009-0146-3

Vancea M, Solé-Casals J (2016) Population aging in the European Information Societies: towards a comprehensive research agenda in eHealth innovations for elderly. Aging Dis 7(4):526. https://doi.org/10.14336/AD.2015.1214

Venkatesh V, Morris MG, Davis GB, Davis FD (2003) User acceptance of information technology: Toward a unified view. MIS Q 27(3):425–478. https://doi.org/10.2307/30036540

Wagner N, Hassanein K, Head M (2010) Computer use by older adults: A multi-disciplinary review. Comput Human Behav 26(5):870–882. https://doi.org/10.1016/j.chb.2010.03.029

Wahlroos N, Narsakka N, Stolt M, Suhonen R (2023) Physical environment maintaining independence and self-management of older people in long-term care settings—An integrative literature review. J Aging Environ 37(3):295–313. https://doi.org/10.1080/26892618.2022.2092927

Wang CL, Chen XJ, Yu T, Liu YD, Jing YH (2024a) Education reform and change driven by digital technology: a bibliometric study from a global perspective. Humanit Soc Sci Commun 11(1):1–17. https://doi.org/10.1057/s41599-024-02717-y

Wang CL, Dai J, Zhu KK, Yu T, Gu XQ (2023a) Understanding the Continuance Intention of College Students Toward New E-learning Spaces Based on an Integrated Model of the TAM and TTF. Int J Hum-comput Int 1–14. https://doi.org/10.1080/10447318.2023.2291609

Wang CL, Wang HM, Li YY, Dai J, Gu XQ, Yu T (2024b) Factors Influencing University Students’ Behavioral Intention to Use Generative Artificial Intelligence: Integrating the Theory of Planned Behavior and AI Literacy. Int J Hum-comput Int 1–23. https://doi.org/10.1080/10447318.2024.2383033

Wang J, Zhao W, Zhang Z, Liu X, Xie T, Wang L, Zhang Y (2024c) A journey of challenges and victories: a bibliometric worldview of nanomedicine since the 21st century. Adv Mater 36(15):2308915. https://doi.org/10.1002/adma.202308915

Wang J, Chen Y, Huo S, Mai L, Jia F (2023b) Research hotspots and trends of social robot interaction design: A bibliometric analysis. Sensors 23(23):9369. https://doi.org/10.3390/s23239369

Wang KH, Chen G, Chen HG (2017) A model of technology adoption by older adults. Soc Behav Personal 45(4):563–572. https://doi.org/10.2224/sbp.5778

Wang S, Bolling K, Mao W, Reichstadt J, Jeste D, Kim HC, Nebeker C (2019) Technology to Support Aging in Place: Older Adults’ Perspectives. Healthcare 7(2):60. https://doi.org/10.3390/healthcare7020060

Wang Z, Liu D, Sun Y, Pang X, Sun P, Lin F, Ren K (2022) A survey on IoT-enabled home automation systems: Attacks and defenses. IEEE Commun Surv Tutor 24(4):2292–2328. https://doi.org/10.1109/COMST.2022.3201557

Wilkowska W, Offermann J, Spinsante S, Poli A, Ziefle M (2022) Analyzing technology acceptance and perception of privacy in ambient assisted living for using sensor-based technologies. PloS One 17(7):e0269642. https://doi.org/10.1371/journal.pone.0269642

Wilson J, Heinsch M, Betts D, Booth D, Kay-Lambkin F (2021) Barriers and facilitators to the use of e-health by older adults: a scoping review. BMC Public Health 21:1–12. https://doi.org/10.1186/s12889-021-11623-w

Xia YQ, Deng YL, Tao XY, Zhang SN, Wang CL (2024) Digital art exhibitions and psychological well-being in Chinese Generation Z: An analysis based on the S-O-R framework. Humanit Soc Sci Commun 11:266. https://doi.org/10.1057/s41599-024-02718-x

Xie H, Zhang Y, Duan K (2020) Evolutionary overview of urban expansion based on bibliometric analysis in Web of Science from 1990 to 2019. Habitat Int 95:102100. https://doi.org/10.1016/j.habitatint.2019.10210

Xu Z, Ge Z, Wang X, Skare M (2021) Bibliometric analysis of technology adoption literature published from 1997 to 2020. Technol Forecast Soc Change 170:120896. https://doi.org/10.1016/j.techfore.2021.120896

Yap YY, Tan SH, Choon SW (2022) Elderly’s intention to use technologies: a systematic literature review. Heliyon 8(1). https://doi.org/10.1016/j.heliyon.2022.e08765

Yu T, Dai J, Wang CL (2023) Adoption of blended learning: Chinese university students’ perspectives. Humanit Soc Sci Commun 10:390. https://doi.org/10.1057/s41599-023-01904-7

Yusif S, Soar J, Hafeez-Baig A (2016) Older people, assistive technologies, and the barriers to adoption: A systematic review. Int J Med Inform 94:112–116. https://doi.org/10.1016/j.ijmedinf.2016.07.004

Zhang J, Zhu L (2022) Citation recommendation using semantic representation of cited papers’ relations and content. Expert Syst Appl 187:115826. https://doi.org/10.1016/j.eswa.2021.115826

Zhao Y, Li J (2024) Opportunities and challenges of integrating artificial intelligence in China’s elderly care services. Sci Rep 14(1):9254. https://doi.org/10.1038/s41598-024-60067-w

Article   ADS   MathSciNet   PubMed   PubMed Central   Google Scholar  

Download references

Acknowledgements

This research was supported by the Social Science Foundation of Shaanxi Province in China (Grant No. 2023J014).

Author information

Authors and affiliations.

School of Art and Design, Shaanxi University of Science and Technology, Xi’an, China

Xianru Shang, Zijian Liu, Chen Gong, Zhigang Hu & Yuexuan Wu

Department of Education Information Technology, Faculty of Education, East China Normal University, Shanghai, China

Chengliang Wang

You can also search for this author in PubMed   Google Scholar

Contributions

Conceptualization, XS, YW, CW; methodology, XS, ZL, CG, CW; software, XS, CG, YW; writing-original draft preparation, XS, CW; writing-review and editing, XS, CG, ZH, CW; supervision, ZL, ZH, CW; project administration, ZL, ZH, CW; funding acquisition, XS, CG. All authors read and approved the final manuscript. All authors have read and approved the re-submission of the manuscript.

Corresponding author

Correspondence to Chengliang Wang .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Ethical approval

Ethical approval was not required as the study did not involve human participants.

Informed consent

Informed consent was not required as the study did not involve human participants.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ .

Reprints and permissions

About this article

Cite this article.

Shang, X., Liu, Z., Gong, C. et al. Knowledge mapping and evolution of research on older adults’ technology acceptance: a bibliometric study from 2013 to 2023. Humanit Soc Sci Commun 11 , 1115 (2024). https://doi.org/10.1057/s41599-024-03658-2

Download citation

Received : 20 June 2024

Accepted : 21 August 2024

Published : 31 August 2024

DOI : https://doi.org/10.1057/s41599-024-03658-2

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies