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On Thinking and STEM Education

• Published: 27 February 2019
• Volume 2 , pages 1–13, ( 2019 )

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• Yeping Li 1 ,
• Alan H. Schoenfeld 2 ,
• Andrea A. diSessa 2 ,
• Arthur C. Graesser 3 ,
• Lisa C. Benson 4 ,
• Lyn D. English 5 &
• Richard A. Duschl 6  

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The rapidly evolving and global field of STEM education has placed ever-increasing calls for interdisciplinary research and the development of new and deeper scholarship in and for STEM education. In this editorial, we focus on the topic of thinking, first with a brief overview of related studies and conceptions in the past. We then problematize a traditional conception of thinking in the context of STEM education, and propose possible alternative perspectives about thinking areas for future research.

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Introduction

Mathematics (M) and science (S) have long been important in K-16 education internationally. For example, the International Association for the Evaluation of Educational Achievement (IEA) identified mathematics and science as important school subjects when investigating the outcomes of various school systems around the world. IEA conducted the First International Mathematics Study in 12 participating countries in 1964 (Husén 1967 ) and the First International Science Study, focusing on biology, chemistry, and physics, in 19 participating countries in 1970–1971 (Comber and Keeves 1973 ). While efforts to add or change a school subject or course are not new in the history of K-16 education, it is fascinating for us to witness and wonder: What makes the adding of technology (T) and engineering (E) in education so special nowadays, while still maintaining the importance of M and S? What can and should we expect students to learn differently with the adding of T and E? What makes the combination of T and E with M and S something special for students’ learning of knowledge and thinking development? Clearly, we have many more questions than answers in science, technology, engineering, and mathematics (STEM) education.

Coining the acronym of STEM itself is not enough to justify why STEM education has drawn so much attention internationally over the past decade. The importance of STEM education has been recognized for preparing diverse students for growing job opportunities in STEM in the future, and to a nation as a whole for technological innovations and national prosperity and security (e.g., Committee on STEM Education 2018 ; National Academies of Sciences, Engineering, and Medicine 2007 ; National Science Foundation 2010 ; U.S. Department of Education 2016 ). At the same time, however, there are on-going doubts and critiques of the obsession with STEM education as being delusive and unrelated to human concerns, and which will not bring changes desired in school education (e.g., Hacker 2016 ; Zakaria 2015 ). In spite of such doubts and critiques, to many educators and policy makers internationally, STEM education brings hope for changes in education that will benefit all students, now and in the future, and they also look for new and robust scholarship to support such changes (Li 2018a ).

Developing scholarship in STEM education is not a small task, as it requires team and community work, cross-disciplinary collaboration, and long-term dedication. With such understanding, members of this journal’s editorial board are invited to collaborate to raise questions and perspectives that can reflect and promote the rapid development of integrated STEM education around the globe. In particular, we use the journal’s editorial form of contribution, occasional guest editorials, as a platform to initiate, develop, and encourage interdisciplinary discussion and research in and for STEM education. By doing so, we do not wish to limit discussions and research to only those issues or topics raised in the editorials. While there are many important topics and issues related to STEM education, especially integrated STEM education, that remain to be explored, these editorials can help illustrate which themes, topics, or issues might be relevant to this journal.

In this editorial, we start with the topic of “thinking,” in general, not simply because it is a common focus in education, but because, we argue, it becomes especially valuable for students to develop in and through STEM education. In the following sections, we provide a brief overview of conceptions and studies about thinking and share our questions and alternative perspectives about how thinking can be conceptualized. In particular, we propose that thinking needs to be reconceptualized in and for STEM education, rather than to be viewed only as a single individual-based cognitive process, as in traditional studies in psychology. We develop one possible alternative perspective about thinking as plural, in which thinking can be differentiated into multiple models with levels. With this perspective, we further argue that integrated STEM education is uniquely positioned to offer our students ample opportunities to develop multiple models of thinking productively.

Reviewing Conceptions and Studies of Thinking

Thinking is what we do every day, with various forms and functions. Over a century, scholars have been fascinating about the topic of thinking, and developed many innovative approaches and theoretical perspectives to conceptualize and study thinking. The scholarship about thinking, predominantly as situated in individual’s mind, has shown its development from philosophical discussion to psychological studies in and across disciplinary domains. Here we briefly review and summarize some of them that bear close connections with STEM.

Thinking Viewed from a Philosophical Perspective

One of America’s foremost philosophers and educators, John Dewey, tackled the topic of thought from a philosophical perspective in his classic book How We Think (Dewey 1910 ). Viewing thought and thinking as interchangeable, he shared his views on questions such as, What is thought? Can thought be trained? and What natural resources can be used in the training of thought? He offered philosophical guidance for teachers through analyses of topics such as rational thought, scientific inquiry, the processes of inductive and deductive reasoning, and the teacher-student relationship. His detailed analyses of inductive and deductive thought as the double movement of reflection show important features of logical reasoning that are applicable to various settings such as, doing scientific experiments and a physician making his diagnosis. Although his philosophical discussion is still as inspirational to educators today as in the past, his conceptualization of thinking as what occurred in individual’s mind that can’t be directly observed or perceived limited him to discuss thinking in general terms rather than as an empirical and systematic study.

Thinking Viewed as Cognitive Processes and Strategies in Individual Problem Solving Activities

Conceptualizing thinking as individual’s cognitive processes and strategies has long been important in cognitive psychology. Revolutionary changes in studying problem solving occurred when the information processing approach was introduced in the 1950s and 1960s (e.g., Hovland 1952 ; Hunt 1962 ; as cited in Simon 1979 ). Benefitting from the development of computer technology, psychologists were able to use computers to simulate human’s problem solving performance (Newell and Simon 1972 ). Supported by empirical evidence from both human problem solving performance and computer simulation, the information processing process in computers was used to conceptualize information processing process in human’s mind, with structural components of short-term memory, long-term memory and associated mechanisms similar to what are constructed in computers. Although Newell and Simon’s Human Problem Solving ( 1972 ) framed a general theory of human cognition beyond problem solving, thinking was mainly taken and studied as problem solving in their seminal book.

Simon expanded the information processing model of “problem solving man” from Newell and Simon ( 1972 ) to the notion of “thinking man” in the book Models of Thought (Simon 1979 ), a collection of journal articles with many of them that Simon collaboratively wrote with others including psychologists and computer scientists; a second volume was published 10 years later (Simon 1989 ). With the notion of “thinking man”, Simon was able to compile various studies associated with thinking to include a wide range of task domains such as learning and remembering, problem solving, inducing rules, attaining concepts, and understanding natural language, that can be viewed as models of thought for the thinking man in each of these domains. Simon conceptualized and modeled the thinking man’s information processing as containing different components that can and should be merged into a coherent whole (Simon 1979 ). Thus, human’s thinking is fundamentally conceptualized and modeled as a general and coherent cognitive process with different components in individual’s mind.

Although rooted in the computer simulation of human cognition many years ago, the notion of quantifying information for processing in human mind, as happens in computers, is indeed powerful and still has its great influence nowadays. Jeannette M. Wing at Carnegie Mellon University, where the information processing theory of human cognition was mainly developed, published a succinct article in arguing that computational thinking “represents a universally applicable attitude and skill set everyone, not just computer scientists, would be eager to learn and use” (Wing 2006 , p. 33). The article has drawn widespread interest and prompted discussions about computational thinking as critical to all modern STEM disciplines (e.g., Henderson et al. 2007 ) and its status in K-12 education (e.g., Grover and Pea 2013 ). Questions are also raised to further clarify computational thinking (e.g., diSessa 2018 ; Grover and Pea 2013 ) and a possible important alternative, computational literacy, is also proposed to enrich the meaning of computational thinking (e.g., diSessa 2018 ). In a nutshell, computational literacy avoids Wing’s claim that the importance of computation lies in powerful, general skills that can be developed by using computers. Rather, computation can change the very intellectual landscape of particular domains, in the same way that Arabic notation completely changed the doing of “arithmetic,” and who could do it, and algebra and calculus transformed the study of physics from a philosophical inquiry to a rigorous, precise empirical pursuit (diSessa, 2000 ). More broadly, such scholarly developments and reports suggest the importance of paying close attention to computational thinking and related notions in STEM education and developing further research in the future.

It is important to point out that research on individual students’ thinking goes beyond the conceptualization of thinking to designing and empirical testing, as illustrated in the research work using the information processing approach discussed above. In addition, researchers also used other methods such as instructional experiments to study individual students’ attainment and development of thinking skills (e.g., Chipman et al. 1985 ; Segal et al. 1985 ). Conceptualizing and studying thinking as supported with experimental studies and empirical analyses mark the scholarship development on thinking from the past, both theoretically and methodologically.

The above conceptions and modeling of thinking have been influential, while focusing on individual’s mind as an independent entity. However, thinking and learning often take place in a group setting, both in the context of K-16 STEM education and the workplace (Autor et al. 2003 ; Fiore et al. 2018 ). What important differences in thinking and skill requirement and development emerge when we consider that students do not sit alone but work and discuss with others in situations such as collaborative problem solving (e.g., Graesser et al. 2018 ), and in classroom discourse and argumentation (e.g., Duschl and Osborne 2002 ). As an example, Graesser and his colleagues argue that collaborative problem solving (CPS) requires a set of cognitive and social skills that are different from traditional studies on an individual’s problem solving (Graesser et al. 2018 ). This unique set of cognitive and social skills can include:

Shared understanding: Group members share common goals when solving a new problem.

Accountability: The contributions that each member makes are visible to the rest of the group.

Differentiated roles: Group members draw on their specific expertise to complete different tasks.

Interdependency: Group members depend on the contributions of others to solve the problem.

Graesser and his colleagues further indicate that current school curricula and instruction typically focus on task- and discipline-specific knowledge, placing little emphasis on promoting students’ ability to communicate and collaborate effectively (Fiore et al. 2018 ; Graesser et al. 2018 ). This point is consistent with the potential opportunities that STEM education provides for students to participate in group activities with meaningful instruction, modeling, and feedback on collaborations. Graesser et al.’s work that identifies the essential cognitive and social components of CPS goes beyond traditional conceptualizations and models of thinking as individual-based cognitive processes.

Thinking Viewed as Discipline-Based Individual Cognitive Endeavor

There are many scholars outside of psychology who have also studied thinking from their unique vantage points such as mathematicians, scientists, and educators. George Pólya, a mathematician at Stanford University, published How to Solve It ( 1945 ) that provides general heuristics for solving a wide range of problems, both mathematical and non-mathematical. In this book, thinking is conceptualized as problem solving with heuristics (or strategies) as techniques. Different from psychological studies of problem solving that provide a theoretical understanding of cognitive processes, Pólya tends to provide practical suggestions to teachers of mathematics. His book presents a mathematical approach to study problem solving.

Problem solving was highly emphasized in mathematics education in the 1980s, when it was proposed as the core of school mathematics in the United States (National Council of Teachers of Mathematics 1980 ). Research efforts were also focused on the study of mathematical problem solving. For example, Schoenfeld built upon Pólya’s work in his book Mathematical Problem Solving ( 1985 ), developing a framework that includes four categories of problem solving skills: knowledge base, heuristics, monitoring and self-regulation, and beliefs. His framework for analyzing problem solving indicates that knowing heuristics alone is not enough to guarantee problem solving success. Schoenfeld supported his framework with experiments and detailed data analyses that illustrate how Pólya’s heuristics can become practically useful for different students. While discipline-based (or disciplinary domain-specific) knowledge is essential in mathematical problem solving, the thinking skills highlighted in Schoenfeld’s framework actually include both disciplinary domain-specific and domain-general components. The inclusion of both domain-specific and domain-general components is consistent with what the national and international assessments of problem solving, such as the Programme for International Student Assessment (PISA), have used and revealed (Greiff et al. 2014 ).

Building on his work on mathematical problem solving, Schoenfeld studied teaching mathematics with a focus on how teachers make decisions during classroom interactions (Schoenfeld 2011 ). He developed a theory of decision making that describes how teachers, and individuals more generally, navigate their way through in-the-moment decision-making in their familiar domains. Instead of viewing thinking as individual’s internal cognitive process, Schoenfeld’s work, consistent with his work on mathematical problem solving, highlights how resources (especially their prior knowledge and the tools at their disposal), orientations (a generalization of beliefs, including values and preferences), and goals (often being chosen on the basis of their orientations and available resources) function together, beyond an individual’s cognitive processes, in virtually all knowledge-rich domains (Schoenfeld 2014 ). Such an expanded notion of what research reveals about thinking and its contributing factors may further include one’s history, available external resources, non-cognitive characteristics, and environmental and cultural factors, as what research has revealed about learning nowadays (National Research Council 2018 ).

Studies on thinking in discipline-based education are needed to provide theoretical perspectives and guidance for teaching and learning in different disciplines. Many types of thinking have been identified and studied as pertinent to certain disciplines, but less so to other disciplines. For example, a broadened perspective on mathematics and mathematical reasoning views reasoning as “embodied” and “imaginative”, rather than only in the traditional sense as “abstract” and “disembodied” (e.g., English 1997 ; Lakoff and Núñez 2000 ). In the book edited by English ( 1997 ), Mathematical Reasoning , this perspective allows the book’s contributors to discuss how students’ physical experiences with concrete and visual materials can be transformed into models for abstract thought, along with the role of “thinking tools,” such as analogy, metaphor, and image, in mathematical reasoning. At the same time, multiple approaches are often developed and used in studying discipline-based thinking such as, mathematical thinking. Sternberg and Ben-Zeev ( 1996 ) demonstrated in their edited book, Nature of Mathematical Thinking , that studies about mathematical thinking can take a range of different approaches including, psychometric approach, cognitive information-processing approach, cognitive-cultural approach, cognitive-educational approach, and mathematical approach. From a practice perspective, although mathematical thinking, especially inductive and deductive reasoning, is often taken as commonly needed in different STEM disciplines, improving students’ mathematical thinking is traditionally left for educators and teachers in mathematics. It is thus not surprising if discipline-based educators and teachers are hardly communicated to each other about developing students’ thinking. One possible factor is that discipline-based thinking has traditionally emphasized the importance of a specific discipline (e.g., mathematics) but made other cognitive components almost invisible, which does not follow what Schoenfeld’s problem solving framework tends to reveal.

Discipline-based approaches can be found with research on thinking in other STEM disciplines. For example, design thinking is often associated with innovation (e.g., Leavy 2010 ), and engineering is viewed as the driving force behind design thinking (Simon 1996 ). Although design thinking is important for students in the twenty-first century (Razzouk and Shute 2012 ), it is not a type of thinking skills that traditional mathematics and science educators would address, leaving a void in school education in terms of preparing students to be innovative and successful in today’s highly competitive world. At the same time, the emphasis on the disciplinary aspect of design thinking tends to place engineering as the only discipline responsible for developing students’ design thinking. Although engineering design has received substantial attention in recent years as an essential component in STEM education (e.g., McFadden and Roehrig 2018 ; Park et al. 2018 ; Strimel et al. 2018 ), much more research is needed to explore possible ways of integrating design thinking in school education, especially through STEM education.

As further examples, critical thinking and creativity are another two types of cognitive competences that are discussed broadly in literature and education (e.g., Lai 2011 ; Loveless 2002 ; Sternberg 1999 ; Tiwari et al. 2006 ), and to a certain degree in school science and mathematics education (e.g., Bailin 2002 ; Kind and Kind 2007 ; Silver 1997 ). Similar to design thinking, both critical thinking and creativity are highly valued in education and identified as important cognitive competences for students in the twenty-first century (Pellegrino and Hilton 2012 ). Different from design thinking, they are perceived as more of domain-general cognitive competences. Specifically, background knowledge is perceived as a necessary but not a sufficient condition for enabling critical thinking within a given discipline. At the same time, it is debatable about the extent to which critical thinking is domain-specific (Lai 2011 ). The importance of creativity is commonly acknowledged and highly valued in STEM disciplines. But creativity is associated much more closely with the arts, including visual and literary arts, rather than viewing and examining what STEM may possibly do to foster students’ creativity in school education. There are many questions that remain to be explored about critical thinking and creativity in STEM education. For example, how are critical thing and creativity different from, and/or connected to, each other? How are they different from, and/or overlap with, design thinking? How does a person integrate critical thinking and creativity in school education for students’ thinking development, especially through STEM education? What differences would it bring to develop students’ critical thinking and creativity through individual’s activity vs. group’s collaborative work? Further research is needed.

Problematizing Thinking in and for STEM Education

The above brief overview of conceptions and studies about thinking outlines related scholarship development in broad strokes. Clearly, scholarship over the past 100 years has developed diverse perspectives and approaches about thinking, even within the same discipline, such as in mathematical thinking. However, most of previous studies on thinking have been on individual’s cognitive process in a lab setting, or based on specific disciplines. Scholarship in this area prompts two main questions. First, while disciplinary domain-specific thinking has its own unique value pertinent to a specific discipline, how do we conceptualize thinking in and for STEM education more broadly? Second, when students do not work alone but often collaborate and interact with others in STEM education, how to conceptualize thinking?

Prior work points to the need of reconceptualizing thinking in and for STEM education. Specifically, discipline-based thinking in previous studies tends to specify and highlight content-based approaches but not relationships with thinking in other disciplines. Different from traditional discipline-specific education acting in silos, STEM education is multi-disciplinary or even further interdisciplinary. Previous conceptions of domain-specific thinking can and should be problematized.

Moreover, the lack of attention to students’ collaborative interactions makes the traditional conceptions about thinking questionable for STEM education. The emphasis on students’ group collaborative work is to help them develop those skills important in the twenty-first century. Problems have become substantially more complex nowadays, so complex that a single person cannot provide a deep solution to each problem. Instead, there needs to be a team with different expertise and perspectives to organize and communicate so that sophisticated solutions evolve. Possible examples include medical treatment of a heart problem, and the improvement of water quality in a community. Therefore, researchers argue that students’ group-based collaborative problem solving and discourse present a set of cognitive and social skills different from individual student’s work (e.g., Duschl and Osborne 2002 ; Graesser et al. 2018 ). STEM education is indeed conducive to activities that are student group’s collaboration in nature as situated in a specific socio-cultural environment.

Is there STEM Thinking? If Yes, how Should it Be Defined and Characterized?

Studies on thinking have evolved over the years with a tendency from domain-general to domain-specific, a trend that is also shown in studies about learning from general models to discipline-specific learning trajectories (e.g., Greene et al. 2016 ). At the same time, however, domain-specific thinking and domain-general thinking are not dichotomous, as thinking itself is a complex process involving many different components. Domain-general thinking is often derived from human’s thinking performance across different knowledge-lean (e.g., solving a puzzle) or -rich task domains (e.g., solving algebraic equations). Domain-specific thinking is often characterized in terms of its disciplinary content but also involves more general cognitive components. In other words, domain-specific thinking should contain both domain-specific and -general aspects of cognitive activities. For example, a mathematician’s thinking is scarcely only mathematics (the knowledge component). It can share possible common elements with a biologist’s thinking (e.g., certain aspects of metacognition and meta-representation).

The same reasoning applies to students’ thinking in specific disciplines. For example, as discussed above, Schoenfeld’s problem-solving framework (Schoenfeld 1985 ) illustrates that some aspects of mathematical problem solving are largely discipline-specific (e.g., the knowledge base), some heavily discipline-oriented (e.g., strategies and beliefs), some much like discipline domain-general (e.g., metacognition). In sum, there are many components of thinking that might be shared across STEM disciplines, which prompts the general issues of how much thinking is domain-specific, how much is domain-general, and how much in-between?

STEM is not a single domain, or discipline. However, when STEM education is developed and implemented as specific sets of activities, would it be possible to develop students’ thinking through such activities that can be called STEM thinking? If yes, how should STEM thinking be defined and characterized as different from thinking in specific disciplines? If STEM thinking can be defined in a meaningful way, how much does it overlap with thinking in other individual disciplines, for example, mathematics?

At the same time, current literature shows that STEM education is loosely defined and open to different interpretations (Li 2018b ). STEM education and research can refer to a collection of traditionally separated disciplines, or the integrations of selected disciplines (not necessarily all four disciplines in STEM) in specific ways. The diverse perspectives about STEM and STEM education would pose another challenge for characterizing STEM thinking and whether it can be meaningfully defined, studied, and assessed. Further research and discussion are needed if such a notion of STEM thinking remains as a viable possibility.

How Should Thinking in Integrated STEM Education Be Reconceptualized, when Integration itself Is Also Subject to Variations?

This journal aims to promote the development of interdisciplinary research, especially in integrated STEM education (Li 2018a ). However, currently STEM integration itself is also subject to different perspectives (e.g., English 2016 ). In addition, integration can take place among two, three, or four disciplines in STEM. Nevertheless, one common feature is that integrated STEM education involves more than one discipline. Therefore, would it be better to conceptualize thinking in integrated STEM activities as plural, rather than a singular model (e.g., mathematical reasoning) that is pertinent to a specific discipline?

Viewing thinking as plural differs from viewing thinking as containing different components. Traditional views of thinking are dominated by a single individual-based cognitive process as a whole that contains several components, as illustrated in Simon’s models of thought ( 1979 , 1989 ). Instead, thinking in integrated STEM education can be better reconceptualized and differentiated into multiple models. Individual models can be identified and developed as pertinent to thinking that takes place either in individuals or in groups. Each model can also refer to discipline-general or discipline-based thinking that have been the focus of previous studies such as mathematical reasoning, computational thinking, design thinking, and critical thinking. Individual models can be influenced and characterized further with respect to socio-cultural environments such as the language that students are accustomed to (National Research Council 2018 ). Furthermore, thinking can be differentiated into levels, similar to how diSessa ( 2015 ) defends studying knowledge according to different levels and Graesser and McNamara ( 2011 ) differentiate discourse comprehension into multiple levels. For each model of thinking, however, it is also important to clarify how levels of thinking are differentiated. For example, Simon ( 1979 ) indicates that thinking can be differentiated in terms of levels of information processing. Wing ( 2006 ) suggests that computational thinking can be differentiated at different levels of abstraction.

The perspective of multiple models of thinking will not be apparent when students’ thinking is focused on in a single discipline or when it is studied as individuals in a lab setting. The nature of integrated STEM education clearly differs from traditional discipline-based education, and it calls for the questioning and reconceptualizing of thinking as a process or activity that can be differentiated into multiple models and that can happen in individual’s mind or in interactions among individuals. The perspective of multiple models of thinking suggests that students’ learning can be amplified when specific models of thinking are specified and carefully assembled with a range of meaningful and appropriate materials, methods, and activities. If this perspective is meaningful and can be taken, it is clear that STEM education might be uniquely positioned to offer students opportunities to develop multiple models of thinking. Further discussion and development about this perspective are needed.

Making Connections between Thinking Development through Integrated STEM Education and Twenty-First Century Skills

The call for students to learn and develop twenty-first century skills has been on-going for years and around the world (e.g., Dede 2010 ; Trilling and Fadel 2012 ). Similar to the development of STEM education, the development of twenty-first century skills is driven by a need to prepare the workforce in today’s highly competitive world (Trilling and Fadel 2012 ). For twenty-first century skills, there are also multiple frameworks being proposed such as Partnership for twenty-first Century Skills (P21), EnGauge Framework from Metiri/NCREL, Organization for Economic Cooperation and Development (OECD) twenty-first century skills (Dede 2010 ). However, the specifications of twenty-first century skills vary across these frameworks.

To clarify the meaning of twenty-first century skills and “deep learning,” a committee of the National Research Council of National Academies published a report, Education for Life and Work: Developing Transferable Knowledge and Skills in the twenty-first Century (Pellegrino and Hilton 2012 ). In this report, the committee identified three domains of competence: cognitive, interpersonal, and intrapersonal, while recognizing that these three domains represent distinct facets of human thinking and build on previous efforts to identify and organize dimensions of human behavior. The list of these three domains in the committee’s report is aligned with the perspective of multiple models of thinking discussed above. The shared commonalities suggest that further discussion about these three domains of twenty-first century skills, multiple models of thinking, and STEM education should be on the research agenda in the future.

As STEM education is positioned to bring new perspectives and opportunities to school education, what students can and should learn and do in traditional schooling also need to be problematized and reconceptualized. With a focus on thinking, we hope that this editorial can stimulate more discussion and research about this topic in STEM education. What makes thinking especially important in education is that we not only want to understand how people think, but also try to find ways to develop students’ thinking in new ways, respecting new conditions of the twenty-first century. Having uncovered many new questions, we would certainly like to continue our discussion about thinking. Stay tuned.

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Teaching Approaches for STEM Integration in Pre- and Primary School: a Systematic Qualitative Literature Review

Kevin larkin.

1 School of Education and Professional Studies, Griffith University, 1 Parklands Drive, Southport, Gold Coast, Queensland 4222 Australia

Thomas Lowrie

2 SERC, University of Canberra, Canberra, Australia

In the last 5 years, there have been several literature reviews or meta-analyses investigating various aspects of STEM education; however, they have investigated a specific aspect of STEM, e.g. robotics, or digital games, or Early childhood, or Teacher perspectives. In addition, a broad-reaching review on STEM integration has not been conducted in the past 10 years. This article reports findings from a Systematic Qualitative Literature Review concerning STEM education for children aged 4–12 in formal education contexts. To provide context, the article initially presents descriptive findings (date and country of research, age of participants, research setting, and research methodologies used) in the 60 research articles that are included for analysis. The article then answers three research questions regarding the: (1) level of integration evident in the studies; (2) role of engineering in any such integration; and (3) teaching approaches used in the studies. Findings from this research suggest that there is still much work to be done to move from scenarios where STEM integration is claimed but is not evident in practice. To do so we encourage educators and researchers to (a) focus on authentic interdisciplinary approaches rather than the siloed approaches evident in the existing research; and (b) use a teaching approach such as problem-based or project-based learning that provide opportunities for authentic integration.

Introduction

The purpose of this Systematic Qualitative Literature Review is to examine available research, in peer-reviewed journal articles (2000–present), regarding science, technology, engineering, or mathematics (STEM) integration in preschool and primary school contexts (children 4–12 years of age). Much of the current discussion regarding STEM revolves around an.economic rather than educational agenda. For example, in the Australian context, STEM education is part of a suite of measures that seek to make Australia a “science nation… in which science is woven, not only into our classrooms, but also into our boardrooms, our workplaces and our living rooms, as one of the building blocks of our prosperity” (Commonwealth of Australia, 2015 , p. iii). Likewise, policy discourses in Europe and the USA increasingly position the importance of STEM in the educational context as the basis for future economic well-being (Marginson et al., 2013 ).

Whilst not ignoring the political and economic imperatives for STEM in current discourses, as educational researchers, we suggest it is of much greater importance to understand the educational implications of attempted STEM integration in educational contexts. We chose to focus on STEM education in pre-and elementary school (children 4–12 years of age) as (a) this is our area of research interest and expertise; and (b) research suggests that children’s attitudes to STEM disciplines is formed early in primary school (e.g., Larkin & Jorgensen,  2016 ) found that negative attitudes towards mathematics were already present in children 6–7 years old). A review into STEM integration is particularly timely, as although we are not the first to do so, a similar literature review regarding STEM integration is over ten years old (see Becker & Park, 2011 ). In addition, STEM integration is required if we are to avoid the siloed approaches to STEM education that are present in many of the articles discussed in this review.

To provide a background context for the reader, and to frame our three research questions (see “ Method ”), we briefly summarise some of the key literature in relation to the following three areas; STEM integration, engineering in STEM education, and approaches to teaching STEM.

Theme One—STEM Integration

Although other methods for discussing STEM are present in the literature, for example, via teaching frameworks (see Greca Dufranc et al., 2020 ) or in terms of STEM content, pedagogy, or context (Cheng & So, 2020 ), the dominant approach used in the literature is one that frames STEM solely in terms of integration. For example, Dugger ( 2010 ) categorises STEM Integration into four categories: (a) four separate disciplines; (b) two of the four disciplines emphasised (e.g., SteM); (c) one discipline is integrated into the other three (e.g., E; STM), and (d) all four disciplines have equal emphasis and are approached in an interdisciplinary way. In a similar vein, Laksmiwati et al. ( 2020 ) present seven STEM perspectives including STEM as a very loose connection of the four separate disciplines; STEM as primarily Science, or Science and Mathematics, incorporating the other three or two disciplines respectively; through to full integration of the four disciplines. This full integration is seen by Nadelson and Seifert ( 2017 ) as a “seamless amalgamation of content and concepts” so that “knowledge and process of the specific STEM disciplines are considered simultaneously without regard for the discipline, but rather in the context of a problem, project or task” (p. 221).

Despite being implicit in the definitions of integration noted above, Vasquez et al. ( 2013 ) were explicit in expressing their view on the relative worth of the different forms of integration. They did so via the creation of a continuum of integration where less integrated forms of STEM are placed at the lower level of the continuum and fully integrated forms of STEM are placed at the highest level on the continuum. This continuum has frequently been used by researchers to assess the level of integration occurs when teaching STEM (see Anderson et al., 2019 ; Lowrie & Larkin, 2022 ). The continuum spans four forms of integration commencing with Disciplinary (concepts and skills are learned within each discipline); then Multidisciplinary (concepts and skills are still learned within each discipline but use a common theme); then Interdisciplinary (where concepts and skills from two or more disciplines are learned together); to the final Transdisciplinary form (where concepts and skills are learned across two or more disciplines but with a focus on real-world problems). Given that the Vasquez et al. ( 2013 ) continuum is used in many of the articles we reviewed, we decided to base our initial analysis of integration in the articles in this study using this continuum.

Theme Two—STEM or Just STM

Although the acronym STEM has been evident in educational contexts for the last two decades (see Lowrie & Larkin, 2022 ), its enactment in schools has not been as pronounced, and this is particularly true in the case of the E in STEM. Research on engineering education, as part of the broader STEM education agenda, is limited and perhaps reflects, at least in school contexts, the rather problematic nature of engineering as one of the STEM disciplines. This problematic nature can be accounted for from at least three perspectives; namely curriculum, pedagogy, and gender.

As a curriculum example, in the Australian educational context, while there are clearly defined science, mathematics and technology curriculums, there is no specified engineering curriculum. Instead, the Australian Curriculum, Assessment and Reporting Agency (ACARA), argues that “engineering is addressed across the curriculum through Science, Technologies and Mathematics and in a dedicated content description focusing on engineering principles and systems at each band in Design and Technologies” (Australian Curriculum Assessment and Reporting Authority [ACARA], 2017 ). Whilst this may appear to be a good outcome in terms of integrating engineering into other STEM disciplines, from our experience, when a curriculum area is intended to be integrated across a range of areas it often means, in practice, it is not integrated into any of them. As Lowrie and Larkin ( 2020 ) illustrate, this approach is problematic as the individual disciplines are often written independently of each other, with little attempt at developing authentic connections between them. Given this observation, the lack of a dedicated engineering curriculum within a curriculum suite, places engineering in primary schools in a precarious position.

In terms of pedagogical issues related to the teaching of engineering, Dubosarsky et al. ( 2018 ) indicate that “one of the reasons for the lack of STEM and engineering instruction is educators’ low self-efficacy regarding the teaching of STEM, due in part to a lack of preparation and shortage of early childhood STEM and engineering curricula” (p. 252). This lack of confidence in teaching engineering occurs, in large part, because engineering is as new for most early childhood educators as it is for children (Cunningham et al., 2018 ).

An urgent requirement for the better teaching of engineering in the early and primary years is, therefore, the professional development of educators. Lippard et al. ( 2018 ) advance the argument that professional development in mathematics and English has encouraged early years educators to recognise early literacy and maths skills and to value these “pre” skills. Likewise, they claim “teachers will, similarly, need training and support to recognize and appreciate pre-engineering skills” (p. 32). English ( 2018 ) also identifies concerns and calls for professional development that can “assist teachers in better understanding the nature and role of engineering learning, together with effective planning and the enactment of integrated STEM lessons” (p. 282). In a somewhat novel solution, Estapa and Tank ( 2017 ) promote a triadic method of professional development with the triads consisting of a classroom educator, a pre-service educator, and an engineering fellow, where the focus is on enhancing knowledge of STEM concepts using an engineering design approach. These authors argue that any real changes in practice call for “sustained, coherent, collaborative, reflective teacher programs” (p. 2).

Finally, in terms of gender, as a logical consequence of the limited research overall, there is only a limited body of research on the role that gender plays in engineering education in the early and primary years. Sullivan and Bers ( 2016 ) indicate that, even though the gender disparity has decreased over the past decade or so, this disparity remains at its largest in terms of engineering opportunities. Research by Pattison et al. ( 2016 ) highlights the “critical need to understand how engineering interests develop and can be supported before children enter school; and the effectiveness of supporting, through early childhood interventions, long-term engineering-related interest development” (p. 1). In some brighter news, Metz ( 1997 ), and Greca Dufranc et al. ( 2020 ), found that robotics and computer programming, particularly in the early years, can provide girls with positive experiences of engineering before negative gender stereotypes begin to set in during the upper primary school years.

Given the rather glum picture we have painted in relation to the place of engineering in STEM, in terms of curriculum, pedagogy, and gender, we were interested to test our research question that E would be underrepresented in the STEM articles that form the dataset for this article.

Theme Three—STEM Teaching Approaches

We have identified, in previous work in this domain, (see Larkin & Lowrie, 2022 ; Lowrie, et al., 2017 ) that three teaching approaches are typically associated with STEM education: Inquiry-based, Project-based, and Problem-based, learning. In examining the articles in this review, we discovered that in some of the articles, the related term, Design-based learning, was used (see Bagiati & Evangelou, 2015 ; Sariçam & Yildirim, 2021 ). In instances where this occurred, we looked to see whether the projects related to real-world issues generated by the children or whether they were issues proposed by the teacher, and then categorised them as Problem-based or Project-based respectively. Regardless of the terminology used, this group of learning approaches has been identified as being beneficial for students in terms of a) cognitive aspects, e.g. improved connectivity between discipline areas (Estapa & Tank, 2017 ) and increases in higher-order thinking skills and creativity (Fan & Yu, 2017 ); and b) affective aspects— (for example, positive changes in perceptions of STEM-related careers and disciplines (Knezek et al., 2013 ). We briefly outline the features of each of the three approaches below.

Inquiry-based learning

According to Bybee ( 2010 ), descriptions vary in terms of what Inquiry-based learning means, and these differences are often represented using a continuum from educator-directed to child-centred approaches (Anderson et al., 2019 ; Calder et al., 2020 ). At the educator-directed end of the continuum, there is minimal inquiry (e.g., where an educator provides explicit instructions regarding how children are to carry out an experiment or investigation). At the child-centred end is an open-ended inquiry where children initiate both their own questions and their own processes to answer those questions. Albion ( 2015 ) notes that, whilst sharing many features of Project-based and Problem-based learning, a distinguishing feature of Inquiry-based learning is that it follows a cyclical scientific method that is often expressed in terms of the 5Es —Engage, Explore, Explain, Elaborate , and Evaluate (Bybee, 2010 ). Thus, Inquiry-based learning can take place over a shorter period, with greater scaffolding by educators, than is likely in either of the other two learning approaches.

Project-Based Learning

Lowrie et al. ( 2017 ) indicate that Project-based learning involves children investigating a particular problem, question, or challenge for a sustained period. Several key features characterise this approach and these include educators:

• Identifying authentic problems that are likely to be of interest to children (Estapa & Tank, 2017 )
• Assisting children to establish connections between these problems and their real-life experiences
• Supporting children to solve these problems using the concepts they have been learning (Dierdorp et al., 2014 )
• Encouraging the creation of a meaningful product (Albion, 2015 )

Problem-Based Learning

Problem-based learning is similar in many respects to Project-based learning as both involve children working to solve open-ended problems. The distinguishing feature of Problem-based approaches are that they relate to the children’s real-life experiences, are posed by the children, and aim to challenging them to think differently in finding solutions (English & Mousoulides, 2015 ). To facilitate an understanding by children, regarding how STEM-based knowledge and skills work outside the classroom, a necessary component of Problem-based approaches is that they offer multiple solutions and pathways to success (English & Mousoulides, 2015 ) and normally occur over a period of at least several weeks (Albion, 2015 ).

Research Questions

Based on our work in STEM in the before school, early years, and primary years of schooling (see Larkin & Lowrie, 2022 ; Lowrie et al., 2017 , 2019 ) we approached this review with three research questions in mind:

• RQ 1#. Do most articles included in the dataset involve only the lower levels of integration (i.e. Disciplinary or Multidisciplinary as opposed to Interdisciplinary or Transdisciplinary)?

RQ 2. Is engineering the least integrated of the four individual STEM disciplines?

• RQ 3. Are most teaching approaches either Inquiry-based, Problem-based, or Project-based?

We will return to these research questions later in the article. Initially, we explain the methodology we followed to find relevant research according to our selection criteria, and then we explore some of the descriptive findings from the Systematic Qualitative Literature Review.

Search Strategy Used

In finding STEM published research, we followed the established Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) search protocols (Page et al., 2021 ). For consistency with previous Systematic Qualitative Literature Reviews, we used databases that have been used in previous research by Becker and Park (2016), Sullivan and Heffernan ( 2016 ), and Margot and Kettler ( 2019 ). The databases searched were ERIC; Informit + ; Proquest; Sage Journals; and Taylor and Francis Online. The following two searches were conducted in each of the five databases:

• ti((child* OR preschool OR Kindergarten OR early childhood OR School)) AND ti(STEM) AND all(STEM) stype.exact(“Scholarly Journals”) AND PEER(yes) since 2000
• (ti((child* OR preschool OR Kindergarten OR early childhood OR School)) AND ti(Science AND Technology AND Engineering AND Mathematics) AND stype.exact(“Scholarly Journals”) AND PEER(yes)) AND stype.exact(“Scholarly Journals”) AND PEER(yes).

The search was limited the research to peer-reviewed journals articles between 2000 and 2022. The year 2000 was chosen as it was then that STEM became a topic of focus in education. To maximise replicability of our search strategy, we choose to only include peer-reviewed research published in journals. Following this process, we found 1439 articles and, after 160 duplicates were removed, we were left with 1279 articles for further screening (see Fig.  1 ).

Identification of studies via databases (adapted from PRISMA — see Page et al., 2021 )

Details regarding screening process

As recommended in the PRISMA Statement (Page et al., 2021 ), the screening process followed several steps. Initially, we examined the titles, abstracts, and keywords to determine whether the research met our criteria for inclusion (see Table ​ Table1) 1 ) and to exclude those that did not.

Criteria for inclusion and exclusion

Following this initial scan, we were left with 109 articles. The next step of the process involved reading these 109 articles in full. This was necessary to accurately answer our three research questions, and to clarify the suitability of articles where our inclusion criteria were not clear from the title, abstract or keywords. This process resulted in a further 49 articles being excluded, which left us with 60 articles included for descriptive analysis (see “Appendix” for full bibliographic details).

Three observations and clarifications are important at this juncture.

• In Fig.  1 , we have included the list of reasons for non-inclusion in the study. The list indicates the order that the exclusion criteria were applied and, therefore, only demonstrates one potential pathway in determining the suitability of the articles. If the pathway was modified, the number of articles deleted at each step would change; however, the final number of 60 articles that meet all inclusion criteria (i.e. none of the exclusion criteria) would remain the same. For example, some of the articles excluded on the “Outside Age Group” criteria concerned “Out of School” STEM and thus, if the steps were reversed, there would be a larger n for “Out of School” STEM.
• We stress that we are not suggesting, by their exclusion, that “Out of School” STEM activities are not beneficial; indeed, in Larkin and Lowrie ( 2022 ) we argue for their important role in supporting STEM learning. Likewise, as we have argued elsewhere, professional development for teachers is critical (see Larkin & Lowrie, 2022 ; Resnick et al., 2022 ). However, as the focus of our three questions include levels of integration and types of pedagogical approaches, it was necessary to limit our focus to children’s in-school STEM learning.
• Some of the final 60 papers also include aspects of the exclusion criteria. For example, both Cotabish et al. ( 2013 ) and Dejarnette ( 2018 ) discussed professional development as one element of their research; however, each of these research papers had as their primary focus, elements that met inclusion criteria. In instances like these, these articles were included in the review.

Although the large bulk of articles initially found in the database search were excluded, the number of articles left to address our three questions is, when compared with other STEM related Systematic Qualitative Literature Reviews (see Table ​ Table2), 2 ), quite large.

Related STEM Education Systematic Qualitative Literature Reviews

Compilation of the Data

Once the final 60 articles were determined, we then began a comprehensive data collation process and used an Excel spreadsheet to assist in the compilation and analysis of the data. To situate the research articles in context, we identified several types of descriptive statistics (see Fig.  2 ): namely, year of publication, country where research was conducted, the participants in the study, and the research setting. We also coded data according to our three research questions (see Figs. ​ Figs.3 3 and ​ and4). 4 ). As articles often included several data collection techniques (e.g., interviews, surveys, classroom observations), some articles were counted twice, using two difference codes (e.g., as using interviews and as using pre and post measures). One further point of clarification is required. Rather than determining ourselves whether a STEM activity was, for example, engineering or technology (given the close relationship between the two), we relied on the terminology used by the original researchers in their depictions of whether an activity was engineering or technology. The spreadsheet containing the full coding information is available at this link ( https://www.dropbox.com/s/nwder8jpc4j9ecu/Raw%20Data%20for%20online%20file.xlsx?dl=0 ).

Sample of descriptive information

Sample of levels of integration

Sample of discipline combinations and learning approaches

Descriptive Analysis

To provide an overall view of the research, we now discuss the descriptive statistics we collected that provide a holistic context for the remainder of the article. As we indicated earlier in our search criteria, as STEM as an educational issue largely coincided with the start of the new millennium, we searched for articles in the period of 2000–2022. It was a little surprising to find that the first peer-reviewed article relating to either preschool, early years or primary STEM was only published in 2010, with the bulk of the articles appearing in the last four years (see Fig.  5 ).

Publications per year since 2000

The large increase in the number of publications towards the end of the last decade possibly reflects various national government initiatives to improve national economic and social mobility outcomes via a STEM agenda. For example, in the Australian economic context, “an improvement of 1% in STEM related roles could add $57.4 billion to GDP” (Australian Academy of Science, 2016 , p. 4). Maass et al. ( 2019 ) note that in the European context, “it is also increasingly recognised that Science, Technology, Engineering, and Mathematics (STEM) education is an essential foundation for responsible citizenship and the ethical custodianship of our planet” (p. 870). The larger number of the articles towards the end of the period under investigation could also reflect the findings of Li et al. ( 2020 ) who report that funded STEM research in the USA was unevenly distributed. As the trend for average funding of STEM research reached a peak in 2014, it could be the case that this accounts for a peak in publications in the years following the conclusion of the projects.

We also coded the articles to determine the countries in which the research took place (see Fig.  6 ). All but one of the articles involved research in a single country, with the exception being an article by Greca Dufranc et al. ( 2020 ) involving a case study approach using classes in Spain and Sweden.

Location of Research. a Publications total 61 as one study was conducted in two countries

As STEM originated in the USA, we were not surprised that many studies took place there; however, contrary to the findings of Margot and Kettler ( 2019 ) regarding teacher perspectives of STEM integration, where 20 of the 25 studies in their review were from the USA, the studies in our review were more evenly distributed (see Fig.  6 ). As Australian based researchers, we were aware of various research projects in our educational “backyard”; however, what was surprising to us were the large number of studies conducted in Turkey. We surmise that the 15 articles reporting research in Turkey, each published from 2018 onwards (with 13/15 published in last two years), may have been a consequence of a report regarding STEM Education in Turkey (Bücük, 2016 ) where the Minister of Education called for the development of a dynamic education system that would “raise a generation who will invent scientifically in the future” (n.p.).

One of the inclusion criteria was STEM research involving primary school aged children (4–12 years old). As seen in Table ​ Table3, 3 , the articles reported a mixture of child only (26/60), teacher only (12/60), and both children and teachers, as participants (22/60). Recall that, to be included, the articles with only teachers as participants needed to focus on curriculum or pedagogy and not only professional development. Although none of our research questions delineate between stages of primary school, for transparency (see Table ​ Table4), 4 ), we report the split of studies according to preschool children only (18/48), primary school children only (26/48), or both groups (4/48) Most of the primary school research occurred in the first four years of schooling (i.e. 4–8-year-olds).

Study participants ( n  = 60)

Studies including children ( n  = 48)

As seen in Table ​ Table5, 5 , there was a broad range of research methodologies employed in the articles, ranging from more quantitative empirical studies (pre- and post-tests and/or experimental/control groups), mixed methods (surveys and document analysis), through to the more qualitative approaches of (interviews, focus groups, classroom observation and work samples). Sample sizes of the studies ranged from 12 to 1201 participants, with four large studies each with more than 800 participants, and nine small studies each with less than 20 participants. In terms of average number of participants, the mean was 139, the median 44, and the mode 40.

Approaches to data collection ( n  = 115)

Number is greater than 60 as many studies used more than one approach to data collection

The Three Research Questions

We now examine the data collected from the articles to answer each of the three research questions indicated earlier in the article.

RQ 1#. Do most articles included in the dataset involve only the lower levels of integration (i.e.Disciplinary or Multidisciplinary as opposed to Interdisciplinary or Transdisciplinary)?

Given the widespread use of the Vasquez et al. ( 2013 ) model for categorising STEM integration (see Anderson et al., 2019 ; Larkin & Lowrie, 2022 ), we commenced an examination of the types of STEM integration using this model as a coding device. However, it became apparent early in the coding process that there were claims of integration in the research articles that did not, in our view, correspond to any of the four levels of integration proposed by (Vasquez et al., 2013 ) (see Fig.  7 ), and thus, new categories were required.

Level of Integration of STEM disciplines

Firstly, we found articles that, although they included STEM or STEM integration in the title, did not demonstrate any (or at least only very incidental) integration between disciplines. These examples of research “within” a sole STEM discipline have been coded for this analysis using the term Intradisciplinary . Examples of Intradisciplinary research include the use of a tool (e.g., iPads (Aladé et al., 2016 )), or a STEM discipline methodology (e.g., the 5Es in science (Ültay et al., 2020 )), within the domain of one individual discipline. In instances such as this, the term STEM in the article title might more accurately be replaced with a specific discipline term such as science, engineering, etc.

The second category not included in Vasquez et al. ( 2013 ) is similar to the Intradisciplinary category in that a specific STEM discipline methodology is used; however, in this instance, the methodology is used to (a) teach either content from another specified STEM discipline (e.g. an Engineering Design approach is used to teach mathematics (Firdaus et al., 2020 ; Gold et al., 2021 )); or (b) the methodology is used to teach STEM without identifying any disciplines (e.g. an Engineering Design approach is used to teach STEM (Malcok & Ceylan, 2021 )). This category also includes the use of a non-STEM specific instructional approaches to teach STEM (e.g., play-based learning (Stephenson et al., 2021 ) or blended learning (Seage & Türegün, 2020 )). For cases such as these, the term Quasidisciplinary is used. We have two observations to make regarding these findings, which touch on issues related to either end of the Vasquez et al. ( 2013 ) continuum. The first relates to the lack of studies at the more integrated end of the continuum and the second relates to the need to create two new categories at the lower end of the continuum to accurately reflect the level of, or lack of, integration.

Lack of Interdisciplinary and Transdisciplinary Integration

Of the 60 studies analysed in this study, only 5/60 (or ≈ 8%) involved the higher levels of integration i.e. Interdisciplinary or Transdisciplinary . Koul et al. ( 2018 ) provide evidence of transdisciplinary integration in their project, which involved children completing a selection of design-based problems (e.g., investigating bike wheel friction, an oil spill, or the workings of solar panels). What makes this work transdisciplinary is that, in each of the problems, there was an emphasis on concepts from each of the four disciplines and how these need to work together to generate potential solutions to the problems. The observation that most projects demonstrated low levels of interdisciplinary integration is perhaps unsurprising given the lack of content and pedagogical knowledge regarding STEM for primary and early childhood educators (Fleer, 2009 ); and curriculum design issues where individual STEM disciplines have their own curriculums (Engineering being an exception) with little thought as to how these disciplines might be taught in integrated ways (Lowrie & Larkin, 2020 ). Although we had anticipated difficulties with the higher order integration of STEM, it is a little surprising, given the greater flexibility with timetabling (Honey et al., 2014 ), and the fact that primary school teachers normally teach several subjects (Shernoff et al., 2017 ), that we did not see more studies involving evidence of the higher levels of integration in this analysis.

Intradisciplinary and Quasidisciplinary Integration

An initial finding was that less than 50% of the studies (29/60) reflected any of the four levels of integration as proposed by Vasquez et al. ( 2013 ). To accurately reflect the level of integration in 31 of the studies, which did not even reach the lowest integration level ( Disciplinary )—where students learn concepts and skills separately in each discipline—it was necessary for us to create two even less integrative categories— Intradisciplinary (effectively STEM is claimed, but only one discipline is involved) and Quasidisciplinary (STEM is again claimed, but it is just the use of one discipline methodology—or a non-STEM methodology—to teach a STEM discipline). Possible causes for these findings relate to the issues raised above regarding the difficulties of integration. However, they may also reflect the fact that the STEM agenda has become a powerful source of research and school funding in the last decade or so, and this funding is only attracted by STEM badged research or teaching activities. Thus, the incentive is there to claim STEM integration, even though this integration is only minimal, with the primary thrust of the research appearing to involve only one discipline. This incentive is also evident in the plethora of STEM siblings—STEAM, STEMM, STEMR, STEM C + (see Lowrie et al., 2017 ), where hitching a ride on the STEM train can mean additional financial support for research and teaching endeavours.

Given our experiences in STEM education in Australia, and our knowledge of research in the international STEM context, we anticipated that engineering would be the least integrated STEM discipline. However, as depicted in (Fig.  8 ), this was not the case, with engineering and mathematics almost equal as the second most integrated disciplines after science with technology being the least integrated discipline.

Integration of STEM by discipline

Figure  8 is a raw count of the number of times the individual disciplines were named in the articles reviewed. We were also interested to see the pattern of combinations of the disciplines as, given that some of the articles were not really about integration at all, this might give us more of a sense of which disciplines are more easily, or at least more regularly, integrated than others. These combinations are provided in (Fig.  9 ). For the purposes of this discussion, we are not proposing any evaluation of the relative worth of the disciplines in the order that they are presented and for convenience, we have listed the combinations in the order that the letters appear in the word STEM. For example, a study about engineering and science and a study about science and engineering are both included in the S + E category, with no implication that the discipline listed first was the primary one. Secondly, to be coded as “(all 4*)”, the articles needed to specifically mention the four disciplines. This was used as a quality control measure, as ten of the 60 articles reviewed just referred to STEM throughout, without specific mention of the different disciplines or how they were integrated. This meant it was impossible for use to assess discipline integration in the articles and thus they were coded as “undefined”.

Combinations of STEM disciplines. *Indicates that each of the four disciplines was specifically mentioned and excludes articles that indicated STEM integration but did not name any specific discipline

In terms of the various combinations of disciplines, excluding the instances where all four disciplines were combined, the results show that science was included in 20 combinations, engineering in 16 combinations, mathematics in 11 combinations, and technology in 8 combinations. The science and engineering combination is interesting as they were paired to a much greater degree than any other pairing. The combinations of disciplines found in our review can be compared with the meta-analysis of 28 articles by Becker and Park ( 2011 ), who also investigated integrative approaches to STEM education present in the literature, albeit with a broader age range (students were from elementary through to college age). These authors report that ten of their studies involved integration of (S + M); three combinations had five studies each (S + T + E; S + T + M; and S + T); and three further combinations had one study each (S + T + E + M; E + M; and S + E).

The main differences between the results of Becker and Park ( 2011 ) and our results are in the integration pairs of (S + M) with 10/28 and 3/36 respectively; (S + T + E + M) with 1/28 and 11/36 respectively) and (S + E) with 1/28 and 10/36 respectively. There are several possible explanations for the differences. Firstly, the meta-analysis by Becker and Park ( 2011 ) investigated the impact of STEM on student learning and thus science and mathematics may have figured more prominently, as these are established curriculum subjects, with historical standardised tests that can be used to measure learning. In addition, the stronger emphasis on engineering in our review might relate to the observation that engineering was under researched in early STEM publications. Given it is more than ten years since the Becker and Park ( 2011 ) study, the rebalancing of emphasis on engineering might account for this difference. In our analysis, 21 of the 27 studies that included engineering were published in the last 3.5 years. What is curious to us is that only one study in the research of Becker and Park ( 2011 ) involved all four disciplines. This could again be related to the earlier observation that science and mathematics have a long history as school curriculum subjects, with technology (at least in its digital aspects) a latecomer in a curriculum sense (see Lowrie & Larkin, 2020 ) and engineering already established as being the “difficult child” in the STEM family.

RQ 3. Are most teaching approaches either Inquiry-based, Problem-based, or Project-based

Initially, a point of clarification is required regarding how we made our classifications. In some of the articles the author(s) indicated that they used one of our three approaches; however, if we determined, according to our classification system, that the articles portrayed a different approach, we categorised the article according to our evaluation and not according to the author(s) determination. By way of example, Ergün and Külekci ( 2019 ) indicate in their article that they used a Problem-based approach; however, in our view, it only minimally involved this approach and was primarily a series of science lessons regarding Friction and Force. Consequently, we categorised this article as using a teacher directed approach.

Our initial coding, using the three types of approaches (Problem-based, Inquiry-based, and Project-based), proved inadequate for the task of categorising learning approaches in the studies reported upon here. If we coded the articles using only the original three approaches, 38 out of the 60 studies would have been coded as “Other”. Therefore, we added a further two codes; namely, play-based, and teacher directed, approaches (see Fig.  10 ). As we have already defined Problem-based, Inquiry-based, and Project-based approaches, we will now briefly define Play-based, and Teacher-directed, approaches. By Play-based we mean instances where children are involved in learning about STEM as they engage in play. Although a difficult concept to define, our emphasis in this classification is on STEM learning through play and can be seen, for example, in Stephenson et al. ( 2021 ) and Tippett and Milford ( 2017 ). By Teacher-directed approaches we mean scenarios where teachers plan for STEM learning or STEM integration but do not provide opportunities for children to have any agency in this learning or integration. In our classification this is seen, for example, in Yavuz and Yildiz Duban ( 2021 ) and Türk and Akcanca ( 2021 ).

Pedagogical approach used in research

As was the case with our earlier discussion regarding the reasons for low levels of integration, we suggest that the large number of teacher directed approaches evident in the research (25/60 or 42%) again relate to issues concerning curriculum, where discipline content are developed separately with minimal attempt at integration; and concerns regarding the content and pedagogical knowledge of educators in relation to some or all of the STEM disciplines. These issues then impact on how researchers can investigate STEM in school contexts. The distribution of the three types of STEM approaches we had predicted was relatively equal, with Problem-based learning being the least common of the three approaches. This likely reflects that Problem-based learning is the more difficult of the three for teachers to implement as this type of learning requires teachers to “hand over” a significant amount of learning control to the children, and then having the pedagogical and content knowledge confidence to be able to guide the children in their learning rather than the more teacher directed aspects of Inquiry-based and to a lesser extent Project-based learning (see Anderson et al, 2019 ).

The prevalence of play-based learning is accounted for in two ways; firstly, a number of the articles reported on research with pre-school children and play-based learning is a dominant pedagogy in this age group; secondly, two of the articles involved the research of Fleer concerning Conceptual Play Worlds, which, by definition incorporate play-based methodologies. As we have reported elsewhere (Larkin & Lowrie, 2022 ) we agree with Fleer that play-based learning, when accompanied by an appropriate level of educator intentionality, is a robust way to support children’s STEM learning beyond preschool and into the early years of formal schooling.

Limitations

Whilst the search criteria resulted in an initially large set of research articles, the criteria of only selecting peer reviewed journal articles means that we might have missed important research published in book chapters or government reports, or relevant work presented at conferences. We also only reviewed STEM research that directly focussed on children in formal contexts, so again we may have overlooked important insights from work that focussed on STEM in out of school contexts, the ongoing professional development of teachers, or the training of pre-service teachers.

A second limitation relates to our specific focus on the actual integration of STEM, the role of engineering within any integration, and the various teaching approaches used to deliver such integration. Thus, many of the articles we reviewed provided important insights regarding STEM (e.g. supporting creativity (see Sariçam & Yildirim, 2021 ) or STEM and gender (see Sullivan & Bers, 2016 ))—that were outside the scope of our three research questions. Thus, some of the articles that we have been somewhat critical of, make contributions to the STEM research field, but do so outside of our focus.

This Systematic Qualitative Literature Review was the first in over ten years to investigate peer reviewed research regarding STEM integration, and the first that focused solely on the primary school years of schooling (4–12 years). Our initial search of a large body of articles found over 1200 potentially relevant articles; however, only 60 articles met our STEM integration inclusion criteria. Given the amount of funding for STEM in the last two decades, we had anticipated that more research into STEM integration may have occurred with primary age students. We particularly encourage more research into the integration of STEM in the middle and upper primary school age group, as research with this subset of primary-aged students was underrepresented in the 60 studies evaluated in this article. A second recommendation, based on our analysis, would be for researchers to utilise existing STEM performance measures (see Lin et al., 2021 ; Malcok & Ceylan, 2021 ) when investigating STEM integration. In much of the research, this is not the case. In Acar et al.( 2018 ) and He et al. ( 2021 ), for example, existing measures of science, mathematics, or technology achievement are used as a means of measuring STEM achievement. In our view, this is approach counterproductive, as measures of the independent disciplines, are likely to reinforce the siloed positions of the four disciplines and thus hinder more authentic STEM integration.

In examining the articles, we also viewed them through the lens of several research questions that we generated based on our experiences as STEM researchers and educators. These research questions focussed our attention on whether: claims of STEM integration, in the titles and abstracts, were supported by evidence in the body of the articles; the articles were STEM or merely STM; and there were established STEM teaching methodologies evident in the research studies. In terms of STEM or STM, we found that there has been an increased emphasis on research regarding the E in STEM, with 27 studies including engineering. In addition, many of these studies used what was described as an engineering design process. Using this design approach could bear fruit in classrooms, as it is one that can easily support integration with other disciplines (see Bagiati & Evangelou, 2015 ), as well as provide opportunities for greater student agency in their own learning (see Dubosarsky et al., 2018 ).

Whilst the finding regarding an increased role for engineering is a positive for STEM education, what we discovered in relation to the remaining two research questions suggests that much work remains to be done if the rhetoric of STEM integration is to be matched in practice. In our view, two main agenda items remain to be addressed. Firstly, how can teachers, based on more highly integrated research into STEM, be supported in providing children with STEM experiences that are either Interdisciplinary or Transdisciplinary (as STEM is envisaged and promoted) rather than what is currently occurring where STEM is, at best, taught in only Disciplinary or minimally Multidisciplinary ways. Secondly, how can teachers be supported in moving beyond Teacher-directed types of STEM learning (that likely hamper attempts at authentic integration) towards Inquiry-based, Problem-based, Project-based, or Play-based approaches, which are better placed to support the integrative intent of STEM.

Appendix. List of articles used in this SQLR

Acar, D., Tertemiz, N., & Tasdemir, A. (2018). The effects of STEM training on the academic achievement of 4th graders in science and mathematics and their views on STEM training teachers. International Electronic Journal of Elementary Education, 10 (4), 505–513. https://www.iejee.com/index.php/IEJEE/article/view/465

Alade, F., Lauricella, A., Beaudoin-Ryan, L., & Wartella, E. (2016). Measuring with Murray: Touchscreen technology and preschoolers’ STEM learning. Computers in Human Behavior, 62 , 433–441. 10.1016/j.chb.2016.03.080

Amran, M., Bakar, K., Surat, S., Mahmud, S., & Shafie, A. (2021). Assessing preschool teachers’ challenges and needs for creativity in STEM education. Asian Journal of University Education, 17 (3), 99–108. 10.24191/ajue.v17i3.14517

Anderson, J., Wilson, K., Tully, D., & Way, J. (2019). “Can We Build the Wind Powered Car Again?” Students’ and teachers’ responses to a new integrated STEM curriculum. Journal of Research in STEM Education, 5 (1), 20–39. 10.51355/jstem.2019.61

Awang, Z., Yakob, N., Hamzah, A., & Talling, M. (2020). Exploring STEAM teaching in preschool using Fred Rogers approach. International Journal of Evaluation and Research in Education, 9 (4), 1071–1078. 10.11591/ijere.v9i4.20674

Bagiati, A., Yoon, S., Evangelou, D., & Ngambeki, I. (2010). Engineering curricula in early education: Describing the landscape of open resources. European Early Childhood Education Research Journal, 23 (1), 112–128. 10.1080/1350293X.2014.991099

Blackley, S., & Howell, J. (2019). The next chapter in the STEM education narrative: Using robotics to support programming and coding. Australian Journal of Teacher Education (Online), 44 (4), 51–64. 10.14221/ajte.2018v44n4.4

Campbell, C., Speldewinde, C., Howitt, C., & MacDonald, A. (2018). STEM practice in the early years. Creative Education, 99 , 11–25. 10.4236/ce.2018.91002

Çetin, A. (2020). Examining project-based STEM training in a primary school. International Online Journal of Education and Teaching, 7 (3), 811–825. https://iojet.org/index.php/IOJET/article/view/761

Chaldi, D., & Mantzanidou, G. (2021). Educational robotics and STEAM in early childhood education. Advances in Mobile Learning Educational Research, 1 (2), 72–81. 10.25082/AMLER.2021.02.003

Ching, Y., Yang, D., Wang, S., Baek, Y., Swanson, S., & Chitoori, B. (2019). Elementary school student development of STEM attitudes and perceived learning in a STEM integrated robotics curriculum. TechTrends, 63 (5), 590–601. 10.1007/s11528-019-00388-0

Cotabish, A., Dailey, D., Robinson, A., & Hughes, G. (2013). The effects of a STEM intervention on elementary students’ science knowledge and skills. School Science & Mathematics, 113 (5), 215–226. 10.1111/ssm.12023

Counsell, S., & Geiken, R. (2019). Improving STEM teaching practices with R&P: increasing the full range of young children’s STEM outcomes. Journal of Early Childhood Teacher Education, 40 (4), 352–381. 10.1080/10901027.2019.1603173

Dedetürk, A., Kırmızıgül, A. S., & Kaya, H. (2021). The effects of stem activities on 6th grade students’ conceptual development of sound. Journal of Baltic Science Education, 20 (1), 21–37. 10.33225/jbse/21.20.21

DeJarnette, N. (2018). Implementing STEAM in the early childhood classroom. European Journal of STEM Education, 3 (3), 18. 10.20897/ejsteme/3878

Dejonckheere, P., de Wit, N., van de Keere, K., & Vervaet, S. (2016). Exploring the classroom: Teaching science in early childhood. European Journal of Educational Research, 5 (3), 149–164. 10.12973/eu-jer.5.3.149

Dilek, H., Tasdemir, A., Konca, A., & Baltaci, S. (2020). Preschool children’s science motivation and process skills during inquiry-based STEM activities . Journal of Education in Science, Environment and Health, 6 (2), 92–104. 10.21891/jeseh.673901

Ergün, A., & Külekci, E. (2019). The effect of problem based STEM education on the perception of 5th grade students of engineering, engineers and technology. Pedagogical Research, 4 (3), 1-15.

Firdaus, A. R., Wardani, D. S., Altaftazani, D. H., Kelana, J. B., & Rahayu, G. D. S. (2020). Mathematics learning in elementary school through engineering design process method with STEM approach. Journal of Physics: Conference Series, 1657 (1). 10.1088/1742-6596/1657/1/012044

Fleer, M. (2021). Re-imagining play spaces in early childhood education: Supporting girls’ motive orientation to STEM in times of COVID-19. Journal of Early Childhood Research, 19 (1), 3–20. 10.1177/1476718X20969848

Fridberg, M., & Redfors, A. (2021). Teachers’ and children’s use of words during early childhood STEM teaching supported by robotics. International Journal of Early Years Education . 10.1080/09669760.2021.1892599

• Gold, Z., Elicker, J., Kellerman, A., Christ, S., Mishra, A., & Howe, N. (2021). Engineering play, mathematics, and spatial skills in children with and without disabilities. Early Education and Development, 32 (1), 49–65. 10.1080/10409289.2019.1709382

Graves, L., Hughes, H., & Balgopal, M. (2016). Teaching STEM through horticulture: Implementing an edible plant curriculum at a STEM-centric elementary school. Journal of Agricultural Education, 57 (3), 192–207.

Greca Dufranc, I. M., García Terceño, E. M., Fridberg, M., Cronquist, B., & Redfors, A. (2020). Robotics and early-years STEM education: The botSTEM framework and activities. European Journal of STEM Education, 5 (1), 1–13. 10.20897/ejsteme/7948

He, X., Li, T., Turel, O., Kuang, Y., Zhao, H., & He, Q. (2021). The impact of STEM education on mathematical development in children aged 5-6 years. International Journal of Educational Research, 109 , 101795. 10.1016/j.ijer.2021.101795

Hong, J.-C., Ye, J.-H., Ho, Y.-J., & Ho, H.-Y. (2020). Developing an inquiry and hands-on teaching model to guide STEAM lesson planning for kindergarten children. Journal of Baltic Science Education, 19 (6), 908–922.

Hudson, P., English, L., Dawes, L., King, D., & Baker, S. (2015). Exploring links between pedagogical knowledge practices and student outcomes in STEM education for primary schools. Australian Journal of Teacher Education, 40 (6), 1–19.

John, M., Sibuma, B., Wunnava, S., Anggoro, F., & Dubosarsky, M. (2018). An iterative participatory approach to developing an early childhood problem-based STEM curriculum. European Journal of STEM Education, 3 (3), 1–12.

Koul, R., Fraser, B., & Nastiti, H. (2018). Transdisciplinary instruction: Implementing and evaluating a primary-school STEM teaching model. International Journal of Innovation in Science and Mathematics Education, 26 (8), n/a.

Kuo-Ting, H., Ball, C., Cotten, S., & LaToya, O. (2020). Effective experiences: A social cognitive analysis of young students’ technology self-efficacy and STEM attitudes. Social Inclusion, 8 (2), 213–221. 10.17645/si.v8i2.2612

Laksmiwati, P. A., Padmi, R. S., & Salmah, U. (2020, July). Elementary school teachers’ perceptions of STEM: What do teachers perceive? Journal of Physics: Conference Series, 1581 (1).

Le Thi Xinh; Bui Van Hong (2021). STEM teaching skills of primary school teachers: The current situation in Ho Chi Minh City, Vietnam. Journal of Education and e-Learning Research, 8 (2): 149–157.

Lin, X., Yang, W., Wu, L., Zhu, L., Wu, D., & Li, H. (2021). Using an inquiry-based science and engineering program to promote science knowledge, problem-solving skills and approaches to learning in preschool children. Early Education and Development, 32 (5), 695–713. 10.1080/10409289.2020.1795333

Malcok, B., & Ceylan, R. (2021). The effects of STEM activities on the problem-solving skills of 6-year-old preschool children. European Early Childhood Education Research Journal . 10.1080/1350293X.2021.1965639

Malone, K., Tiarani, V., Irving, K., Kajfez, R., Lin, H., Giasi, T., & Edmiston, B. (2018). Engineering Design Challenges in Early Childhood Education: Effects on Student Cognition and Interest, 3 (3).

Master, A., Cheryan, S., & Meltzoff, A. N. (2017). Social group membership increases STEM engagement among preschoolers. Developmental Psychology, 53 (2), 201–209. 10.1037/dev0000195

Miller, J. (2019). STEM education in the primary years to support mathematical thinking: Using coding to identify mathematical structures and patterns . ZDM Mathematics Education, 51 , 915–927. 10.1007/s11858-019-01096-y

Ndijuye, L., & Pambas, B. (2020). STEM starts early: Views and beliefs of early childhood education stakeholders in Tanzania. Journal of Childhood, Education & Society, 1 (1), 29–42. 10.37291/2717638X.20201128

Onal, N., & Kirmizigul, A. (2022). A Makey-Makey based STEM activity for children. Science Activities, 58 (4), 166–182.

Orak, S., Çilek, A., & Yilmaz, F. (2020). Adaptation of traditional children’s games to social studies course: STEM course design for teachers. Cypriot Journal of Educational Sciences, 15 (6), 1422–1438. 10.18844/cjes.v15i6.4318

Parlakay, E. S., & Koç, Y. (2020). An investigation the effect of STEM practices on fifth grade students’ academic achievement and motivations at the unit “Exploring and Knowing the World of Living Creatures”. International Journal of Progressive Education, 16 (1), 125–137.

Pila, S., Piper, A., Lauricella, A., & Wartella, E. (2020). Preschoolers’ STEM learning on a haptic enabled tablet. Multimodal Technologies and Interaction, 4 (4), 87. 10.3390/mti4040087

Qiao, X. & Zhou, X. (2020). Research on the integration of STEM education into the rural elementary school science curriculum: An example from rural elementary schools in Western China. Best Evidence in Chinese Education, 5 (1), 581–590. https://doi.org/10.2139/ssrn.3607636

Rochman, C., Nasudin, D., & Rokayah, R. (2019, October). Science literacy on science technology engineering and math (STEM) learning in elementary schools. Journal of Physics: Conference Series, 1318 (1).

Rokayah, R., & Rochman, C. (2019, October). Challenges in science technology engineering and math (STEM) learning in elementary schools based on literacy of social science. Journal of Physics: Conference Series, 1318 (1).

Saddhono, K., Sueca, I. N., Sentana, G. D. D., Santosa, W. H., & Rachman, R. S. (2020, July). The application of STEAM (science, technology, engineering, arts, and mathematics)-based learning in elementary school Surakarta district. Journal of Physics: Conference Series, 1573 (1).

Sangngam, S. (2021). The development of early childhood students’ creative thinking problem solving abilities through STEM Education learning activities. Journal of Physics: Conference Series, 1835 (1).

Sariçam, U., & Yildirim, M. (2021). The effects of digital game-based STEM activities on students’ interests in STEM fields and scientific creativity: Minecraft case. International Journal of Technology in Education and Science, 5 (2), 166–192.

Schroeder, E., & Kirkorian, H. (2016). When seeing is better than doing: Preschoolers’ transfer of STEM skills using touchscreen games. Frontiers in Psychology, 7 (1377). 10.3389/fpsyg.2016.01377

Seage, S., & Türegün, M. (2020). The effects of blended learning on STEM achievement of elementary school students. International Journal of Research in Education and Science, 6 (1), 133–140.

Shimwell, J., DeWitt, J., Davenport, C., Padwick, A., Sanderson, J., & Strachan, R. (2021). Scientist of the week: Evaluating effects of a teacher-led STEM intervention to reduce stereotypical views of scientists in young children. Research in Science & Technological Education . 10.1080/02635143.2021.1941840

Stephenson, T., Fleer, M., Fragkiadaki, G., & Rai, P. (2021). Teaching STEM through play: Conditions created by the conceptual playWorld model for early childhood teachers. Early Years . 10.1080/09575146.2021.2019198

• Tippett, C., & Milford, T. M. (2017). Findings from a pre-kindergarten classroom: Making the case for STEM in early childhood education. International Journal of Science and Mathematics Education, 15 (1), 67–86. 10.1007/s10763-017-9812-8

Türk, A., & Akcanca, N. (2021). Implementation of STEM in preschool education. Journal of Educational Leadership and Policy Studies .

Ugur-Erdogmus, F. (2021). How do elementary childhood education teachers perceive robotic education in kindergarten? A qualitative study. Participatory Educational Research, 8 (2), 421–434. 10.17275/per.21.47.8.2

Ültay, N., Zivali, A., Yilmaz, H., Bak, H., Yilmaz, K., Topatan, M., & Kara, P. (2020). STEM-focused activities to support student learning in primary school science. Journal of Science Learning, 3 (3), 156–164.

Üret, A., & Ceylan, R. (2021). Exploring the effectiveness of STEM education on the creativity of 5-year-old kindergarten children. European Early Childhood Education Research Journal, 29 , 842–855. 10.1080/1350293X.2021.1913204

Wong, K., & Maat, S. M. (2020). The attitude of primary school teachers towards STEM education. STEM Journal, 9 (3), 1243-1251.

Yavuz, Ü., & Yildiz Duban, N. (2021). Primary school students’ interests on professions and opinions on STEM implementations. International Technology and Education Journal, 5 (1), 21–31.

Zhou, S. N., Zeng, H., Xu, S. R., Chen, L. C., & Xiao, H. (2019). Exploring changes in primary students’ attitudes towards science, technology, engineering and mathematics (Stem) across genders and grade levels. Journal of Baltic Science Education, 18 (3), 466–480. 10.33225/jbse/19.18.466

Open Access funding enabled and organized by CAUL and its Member Institutions

Declarations

The authors declare no competing interests.

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STEM Education in Early Years: Challenges and Opportunities in Changing Teachers’ Pedagogical Strategies

• Education Sciences 13(5):490
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Making sense of “STEM education” in K-12 contexts

• Tamara D. Holmlund   ORCID: orcid.org/0000-0001-6132-7873 1 ,
• Kristin Lesseig 1 &
• David Slavit 1  

International Journal of STEM Education volume  5 , Article number:  32 ( 2018 ) Cite this article

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Despite increasing attention to STEM education worldwide, there is considerable uncertainty as to what constitutes STEM education and what it means in terms of curriculum and student outcomes. The purpose of this study was to investigate the commonalities and variations in educators’ conceptualizations of STEM education. Sensemaking theory framed our analysis of ideas that were being selected and retained in relation to professional learning experiences in three contexts: two traditional middle schools, a STEM-focused school, and state-wide STEM professional development. Concept maps and interview transcripts from 34 educators holding different roles were analyzed: STEM and non-STEM teachers, administrators, and STEM professional development providers.

Three themes were included on over 70% of the 34 concept maps: interdisciplinary connections; the need for new, ambitious instructional practices in enacting a STEM approach; and the engagement of students in real-world problem solving. Conceptualizations of STEM education were related to educational contexts, which included the STEM education professional development activities in which educators engaged. We also identified differences across educators in different roles (e.g., non-STEM teacher, administrator). Two important attributes of STEM education addressed in the literature appeared infrequently across all contexts and role groups: students’ use of technology and the potential of STEM-focused education to provide access and opportunities for all students’ successful participation in STEM.

Conclusions

Given the variety of institutionalized practices and school contexts within which STEM education is enacted, we are not convinced that a single worldwide definition of STEM education is critical. What we do see as essential is that those working in the same system explore the common elements that are being attributed to STEM education and co-construct a vision that provides opportunities for all their students to attain STEM-related goals. This is especially important in the current reform contexts related to STEM education. We also see that common conceptions of STEM education appear across roles and contexts, and these could provide starting points for these discussions. Explicitly identifying the ideas educators are and are not selecting and retaining can inform professional learning activities at local and larger scales.

Across the world, STEM receives tremendous attention in education reform efforts and in popular media. The International Council of Associations for Science Educators (ICASE 2013 ) recently urged member countries to work together to improve access to, and the quality of, STEM education in order to prepare all students for global citizenry. In the USA, the National Science Foundation (NSF) has played a significant role in the STEM education movement by calling for research related to science, mathematics, engineering, and technology. While the NSF first used the term “SMET,” this was revised into the more euphonic “STEM” in the early 2000s (Patton 2013 ). Shortly thereafter, the US government issued several studies on the state of STEM learning, and the number of schools designated as STEM-focused increased. Numerous legislative actions also emerged at this time related to computer science, STEM teachers, and STEM as career and technology (CTE) education (Gonzalez and Kuenzi 2012 ; Kuenzi 2008 ).

The NSF continues to use the STEM as an overarching title—for example, in requests for proposals—and activity within any one of the four disciplines can fit into the STEM category. For example, engaging elementary children in engineering and design, developing middle-level mathematics curriculum, or studying high school biology students’ understandings about evolution are all STEM activities. However, in the general public and among K-12 educators, “STEM education” is being increasingly viewed as a new concept, one that somehow brings all four disciplines together. One definition that illustrates an integrated perspective of STEM education comes from work in southwest Pennsylvania:

STEM education is an interdisciplinary approach to learning where rigorous academic concepts are coupled with real world lessons as students apply science, technology, engineering, and mathematics in contexts that make connections between school, community, work, and the global enterprise enabling the development of STEM literacy and with it the ability to compete in the new economy. (Southwest Regional STEM Network 2009 , p. 3)

Despite the increasingly common use of the term “STEM education,” there is still uncertainty as to what constitutes STEM education and what it means in terms of curriculum and student outcomes (Breiner et al. 2012 ; Lamberg and Trzynadlowski 2015 ). STEM education can be considered a single or multi-disciplinary field, and in the case of the latter, no clear consensus exists on the nature of the content and pedagogic interplay among the STEM fields. While science and mathematics education are well-defined (though separate) entities across elementary and secondary schools worldwide, engineering education has largely been a function of higher education in the USA. And technology education has traditionally been delegated to vocational education (now called CTE), when included at all in secondary schooling. Given that policymakers, parents, and business communities are calling for STEM education across grade levels and that STEM literacy is viewed as critical for the economic success and health of individuals and nations worldwide (National Science Board 2015 ; STEM Education Coalition 2014 ), it is important to consider the varied meanings that different groups may have for STEM and STEM education. While it may not be necessary, or even feasible, to coalesce around one common definition of STEM education, we argue that without some shared understandings across a system, it is difficult to design and implement curriculum and instruction to promote successful STEM learning for all students.

In this study, we investigated the conceptualizations of STEM education among educators who work in STEM-focused settings. Our analysis centered on identifying the themes that arise in these educators’ conceptualizations. We also looked for possible relationships between these conceptualizations and (a) their professional work context, including relevant supports for professional learning (referred to as context group ), as well as (b) their professional roles (referred to as role group ).

Conceptualizing STEM education

Consistent with many international recommendations, two National Research Council (NRC) reports on successful K-12 STEM programs in the USA described three major and inclusive goals for STEM education: (a) increase the number of STEM innovators and professionals, (b) strengthen the STEM-related workforce, and (c) improve STEM literacy in all citizens (National Research Council 2011a , 2013 ). But what does it mean, at the classroom level, to implement STEM education? Current research suggests that STEM education is an innovation with various instructional models and emphases that are shaping reform in many educational systems (Bybee 2013 ; National Academy of Engineering and National Research Council 2014 ; Wang et al. 2011 ). Emerging research shows a lack of consensus on the content and instructional practices associated with STEM education, with various models being promoted. These include the incorporation of an engineering design process into the curriculum (Lesseig et al. 2017 ; Ring et al. 2017 ; Roehrig et al. 2012 ), a thematic approach centered around contemporary issues or problems that integrates two or more STEM areas (Bybee 2010 ; Zollman 2012 ), and maker-oriented programs such as robotics, coding, and Maker Faires, which may occur outside of the regular school curriculum (Bevan et al. 2014 )).

However, while various models have emerged, an analysis of STEM education does reveal an emerging consensus on the global attributes associated with this innovation. For example, Peters-Burton et al. ( 2014 ) compiled ten “critical components” of STEM high schools, and LaForce et al. ( 2014 ) identified eight “core elements” of STEM schools. At the classroom level, Kelley and Knowles ( 2016 ) provide a conceptual framework for secondary STEM education efforts. As these and other reports informed the content of the professional development for the participants in this study and our a priori coding categories, we next provide brief descriptions of common elements of STEM education.

One significant attribute of STEM-focused schools is the attention to instructional practices that actively engage and support all students in learning rigorous science and mathematics (Kloser 2014 ; LaForce et al. 2014 ; Lampert and Graziani 2009 ; Newmann and Associates 1996 ). These instructional practices are beginning to be known as a core or ambitious teaching (Kloser 2014 ; Whitcomb et al. 2009 ), and professional development that helps teachers develop these practices along with disciplinary content knowledge is often recommended for STEM-focused learning contexts. Other attributes of STEM-focused schools are student learning experiences that incorporate multiple disciplines (an interdisciplinary, integrated, or trans-disciplinary approach) and often include a project- or problem-based approach tied to authentic or real-world contexts (LaForce et al. 2014 ; Peters-Burton et al. 2014 ). Inherent in problem- and project-based learning are opportunities for student growth in twenty-first century skills such as collaboration, critical thinking, creativity, accountability, persistence, and leadership (Buck Institute 2018 ; Partnership for 21st Century Skills 2013 ). These projects often encompass partnerships with STEM professionals and other community members who can help students make connections between school learning, problem solving, and careers. Another important attribute is students’ use of appropriate and innovative technologies in their inquiries, research, and communication. In this study, we explore the extent to which these characteristics or any others were part of educators’ conceptions of STEM education.

Research questions

Our interest in how educators conceptualize STEM education is grounded in our research on STEM schools and our participation as STEM professional development providers. We framed our study around the following question:

What sense have educators made of STEM education after implementing and/or supporting STEM learning experiences?

We were also interested in possible relationships between participants’ professional work contexts or professional roles and the themes they associated with STEM education. Thus, we addressed the following sub-questions in our analysis:

What themes emerge in the conceptualizations of STEM education among educators in a given professional context? What relationships might exist between an individual’s conceptualization of STEM education and the professional context in which she/he works?

What themes emerge in the conceptualizations of STEM education among educators in a given role group? What relationships might exist between an individual’s conceptualization of STEM education and his/her professional role?

Theoretical framework

Understanding the intentions of reform proposals requires implementers to interpret what is meant and foresee implications on curriculum and instruction (Spillane et al. 2002 ). Because we are interested in the ways in which individuals are navigating the complex and novel ideas inherent in STEM education, we use sensemaking as our theoretical framework. Sensemaking theory attends to both the individual processing and the socially interactive work that occurs when a person encounters a gap in or discontinuity between what exists and a proposed change or innovation (Dervin 1992 ). Grounded in cognitive learning theory, sensemaking is a dynamic process where each person draws upon existing knowledge, beliefs, values, experiences, and identity to accommodate or assimilate new concepts (Weick 1995 ).

Sensemaking begins with a real or perceived disruption to the status quo, which may range from a fairly routine change, such as a schedule revision, to radical innovation in curriculum and instruction. Sensemaking involves a continuous cycle of enacting actions to address the disruption, noticing and categorizing aspects of the enactment, selecting elements that are plausible, and retaining those in future actions (see Fig.  1 ). Feedback from multiple sources shapes all these processes (Weick et al. 2005 ). The creation of a “plausible story” (Weick et al. 2005 , p. 410) provides the implementer a way to reconcile the varied requirements, standards, and other ideas associated with a proposal for change within their current situation.

Sensemaking cycle (adapted from Weick et al. 2005 , p. 414)

Sensemaking is situated within social and contextual components that influence the individual (Coburn 2001 ; Spillane et al. 2002 ). Any one person’s conceptualization can be “talked into existence” (Weick et al. 2005 , p. 413), as it is shaped through dialog with others, by the constraints and affordances of the environment, and sometimes by the influence of leaders. Both individual and collective sensemaking can result in a range of meanings. While multiple perspectives are useful in generating ideas, this can also be problematic in terms of how new ideas are implemented. For example, there are numerous accounts of the challenges inherent in translating educational innovations or policies for reform into mathematics and science classrooms due to contrasting vision (Allen and Penuel 2015 ; Fishman and Krajcik 2003 ; Spillane 2001 ). Therefore, in this study, we are most interested in the current status and result of the participants’ sensemaking process rather than documenting the sensemaking process itself. Understanding how various stakeholders conceptualize new curricular or instructional ideas can inform the conversation needed to support professional learning and alleviate challenges to reform.

Research design

“The assumptions and propositions of sensemaking, taken together, provide methodological guidance for framing research questions, for collecting data, and for charting analyses” (Dervin 1992 , p.62). To understand what sense participants made of the information encountered and experiences they had about STEM education, we elicited each participant’s thinking through concept maps and interviews. Concept maps can show the “structure of knowledge” (Novak 1995 , p. 79) by making explicit one’s ideas within a specific domain. Map creators identify ideas associated with the given domain and arrange these in a way to designate which are most salient and which are related but less significant. These main and subordinate ideas are called “nodes.” Connecting lines, arrows, and words written on these connecting lines can be used to show the interrelationships between the major and less significant nodes (Novak and Cañas 2008 ). As learning is contextual and informed by a learner’s previous knowledge (Bruner 1990 ), any two concept maps typically differ in multiple ways.

Concept maps have been used in K-20 education and in professional development to provide insight into how learners are structuring new ideas with existing understandings (Adesope and Nesbit 2009 ; Besterfield-Sacre et al. 2004 ; Greene et al. 2013 ; Markham et al. 1994 ). The act of map creation requires reflection on events, experiences, and ideas and, thus, is a sensemaking activity: “How can I know what I think until I see what I say?” (Weick et al. 2005 , p. 416). In addition, concept maps allow participants time to make sense of what they think. The maps can then be used in interviews to provide focal points for further sensemaking (Linderman et al. 2011 ), with opportunities for the creator to elaborate and clarify the components and structures of the map.

While sensemaking is ultimately individualistic, the ideas and experiences that contribute to this occur in the context of organizations, conversation, shared activity, and feedback loops (Weick et al. 2005 ).

Sense-making does assume that the individual is situated in cultural/historical moments in time-space and that culture, history, and institutions define much of the world within which the individual lives . . . the individual’s relationship to these moments and the structures that define them is always a matter of self-construction. (Dervin 1992 , p. 67)

In line with this theoretical perspective, the unit of analysis for our study is the individual. We report on this analysis to answer our first research question. We also recognize that each individual has a professional role and is situated within particular institutional structures and cultures and that both the responsibilities of one’s role and the context inform one’s conceptualization of STEM education. As such, we also noted the roles of each participant and developed rich descriptions of the professional contexts in which participants worked. These descriptions, in conjunction with participants’ concept maps and interviews, allowed us to look for relationships among participants’ conceptualizations of STEM education, their professional contexts (sub-question A), and their professional roles and responsibilities (sub-question B).

Participants

Thirty-four people participated in this study. Each was affiliated with STEM education endeavors in one of three context groups . Thirteen participants were teachers and administrators at an inclusive, STEM-focused secondary school (Ridgeview STEM Academy Footnote 1 ). Another 12 were teachers from two traditional middle schools who participated in a 2-year professional development project that supported their implementation of engineering design challenges with their students. Nine were STEM educators and stakeholders participating as faculty in a statewide professional development (PD) institute designed to assist district or school teams with the creation of a STEM education implementation plan. The professional roles of each participant are shown in Table  1 .

Some participants in each context group held dual roles (e.g., Shawn was both a science and an engineering/CTE teacher; Will and Michelle were both non-STEM teachers and administrators). For the purpose of this analysis, the role they most strongly identified with at the time they completed the concept map was used to determine the role groups . The selection of these participants from the larger pool of teachers and administrators at all three schools was based on their participation in two larger research projects. The professional development faculty were included as participants to provide data from a group with very different contexts and, possibly, perspectives. Given the frequent lack of communication and difference in vision among groups associated with reform efforts (Spillane et al. 2002 ), it was important to get a snapshot of the thinking of a group situated outside of classrooms and schools.

Professional work contexts

We describe the professional work contexts of each of our participants. With regard to the participants from Ridgeview STEM Academy and from the two traditional middles schools, we focus on the characteristics of the school and the supports teachers received for their professional learning. In the case of the statewide PD faculty, we focus primarily on their leadership roles in the context of a statewide STEM education leadership institute.

Ridgeview STEM Academy

The participants in this context group were from Ridgeview STEM Academy (RSA), an inclusive STEM-focused school that opened in 2012 with nine teachers and students in grades 6, 7, and 9. The student population was intended to mirror the demographics of the district, and admission was obtained through a lottery by zip code. During the focus year of this study, RSA had approximately 400 students in grades 6–12 and 22 teachers. District-provided professional development associated with learning about the school vision, culture, and practices has been provided since the opening of the school, but teachers have predominantly made sense of STEM education as they implement it. The RSA vision statement described the student learning experience as one that would support the student as a “learner, collaborator, designer, and connector” and the faculty nurtured the growth of a school identity as a place where students had “voice and choice.” STEM learning was viewed as possible for all students, and the curriculum was envisioned as a project- or problem-based (Buck Institute 2018 ) and connected to “the real world of business and research.”

Teachers collaborated across the school year to develop their own interdisciplinary, project-based curricula and used overarching themes to integrate the humanities and STEM disciplines. They accessed a variety of resources as they experimented with the types of instructional practices needed to enact the school vision in the context of the Common Core State Standards (CCSS) (National Governors Association 2010 ) and the Next Generation Science Standards (NGSS) (Achieve 2013 ). Teachers explicitly supported building student skills and attitudes, such as persistence in problem solving, curiosity and a willingness to learn from failure, creative thinking, and the ability to work independently and collaboratively. The technology received attention from the start. Each student was provided a laptop loaded with design, research, and communication tools, and the school offered specific classes dedicated to the use of this technology. Bringing STEM professionals into the school and taking students out to explore STEM careers and work was an explicit focus, with a half-time position created to develop partnerships to support this. The administration assisted teachers in curriculum development by encouraging curricular risk-taking and continuous improvement.

The first and third authors conducted research at this school over a 5-year period (Slavit et al. 2016 ). We invited teachers who participated in our long-term study on STEM schools to participate in this investigation about sensemaking of STEM education. Interviews for this study were conducted with 13 RSA teachers and administrators over an 18-month period.

Traditional Middle Schools (TrMS)

This context group was composed of teachers from two middle schools (Rainier and Hood) in a large suburban school district. Both schools had traditional approaches to education, including a seven-period day and distinct courses for each content area (e.g., physical science, algebra, state history). Limited structures for teacher collaboration existed, and teachers’ interactions typically were by discipline and grade level. Each school had approximately 850 students in grades 6–8; 50% of these students came from low-income households, as determined by their qualification for free or reduced-price lunch.

Thirty-four science, mathematics, special education, and English language teachers from these two schools participated in Teachers Exploring STEM Integration (TESI), a 2-year professional development project that included a 2-week summer institute and ongoing support throughout the school years. Twelve of the 34 teachers participated in this study. TESI focused on the integration of STEM design challenges (DCs) into the existing middle school curriculum (Lesseig et al. 2016 ). An interdisciplinary team composed of scientists, mathematicians, and educators from a local university, community college, and school district developed several DCs that could be incorporated into the district’s existing mathematics and science curricula. The professional learning experiences in TESI were explicitly designed to model integrated STEM curricula aligned with math, science, and ELA standards. Authentic mathematical, scientific, and engineering practices received specific and ongoing attention, especially the identification and clarification of the problem; the importance of research, solution testing, failure, and feedback; and the development of evidence-based explanations. Teachers were provided with the literature about and video examples of core instructional practices (e.g., https://ambitiousscienceteaching.org ) specific to mathematics and science. Teachers were also supported in making sense of an engineering design cycle and reflecting on the attributes of a strong design challenge in relation to the student learning experience. The need for and value of STEM learning was also contextualized in terms of twenty-first century challenges and opportunities for innovation.

During the first week of each summer session, teachers engaged in STEM DCs to support their learning about the relevant disciplinary content and to gain familiarity with the engineering design process. During the second summer week, middle school students identified by their teachers as struggling in mathematics or science were invited to attend each morning session; teachers worked alongside the students to solve a design challenge. Engineering, mathematics, and science professors from the university and a variety of other professionals (e.g., a prosthetics designer, a government climate scientist) interacted with the teachers and students. Teachers spent the afternoons reflecting on the students’ engagement, analyzing instructional practices, and planning for the implementation of design challenges in their classrooms. While undertaking design challenges, teachers and students were involved in collaborative and creative problem solving, communication, and critical thinking. The use of various forms of technology was modeled during the professional development summer institutes. The recognition that every student could be a successful contributor to solving a design challenge was also an explicit element of the TESI project.

The second author was the PI for TESI, and the other two authors were involved in the planning and advisory committees. The teachers interviewed for this study were in the TESI project for 2 years and also participated in a study of the implementation of ideas from that project. Participants from one school included eight eighth-grade mathematics, science, STEM, English as a second language, and special education teachers. Participants from the second school included four sixth-grade teachers of mathematics, science, STEM, and special education (see Table  1 ). All were interviewed in the fall of the second year of the project.

Statewide professional development faculty

The professional work context for each of these nine participants was different than that of the TrMS and RSA educators. All shared a common experience as leaders in a statewide STEM education leadership institute. Yet, each came from a different professional context, and they collectively held a variety of professional roles (see Table  1 ).

The PD faculty were responsible for developing and implementing a week-long summer institute on STEM education and leadership for school and district teams from across the state. The institute focused on the development of and leadership for an implementation plan for STEM education. The content of the institute was grounded in the NGSS, CCSS, and CTE standards ( https://careertech.org ) and informed by the NRC ( 2011a , 2011b ) reports on STEM education. In addition, each faculty member brought a wealth of expertise relevant to STEM education from their professional roles external to this initiative; for example, one was a principal of an elementary STEM school and another a scientist at a national laboratory (see Table  1 ). Many were involved with science and mathematics PD at local and regional levels. Across the year, these institute faculty members developed a list of relevant resources that could be useful to institute participants, including model STEM schools, websites, research and practitioner literature, curricula, and STEM activities. Across multiple meetings, the faculty drew upon these resources and their own expertise to develop sessions for the summer institute. Various sessions focused on the meaning and value of STEM education, including how to integrate isolated school subjects and provide connections to the real-world needs and careers, the importance of partnerships between STEM educators and STEM professionals, equity in STEM learning opportunities, and how to anticipate and address common challenges associated with change. Thus, preparation for and implementation of the various sessions in this institute provided opportunities for all faculty members to share their expertise and clarify key ideas about STEM education.

The PD faculty were invited to participate in this study as their perspectives give us insight into how educators who are promoting the innovation are conceptualizing it, what they identify as important, and the extent to which the messages they convey are coherent and consistent. They created their concept maps during the first of a 2-day planning meeting for the summer STEM education institute. The first author was a member of this faculty and had worked with all but two of the members for at least 5 years.

Data collection

Based on our long-term work within each of the three contexts, we had in-depth information about the STEM-relevant contexts for each of the three participant groups, and the actions group members were asked to take. The above descriptions of each of these contexts were developed in order to address sub-question A about potential relationships between contextual elements and participants’ sensemaking about STEM education.

To capture participants’ conceptualizations of STEM education, we asked them to construct concept maps and used follow-up interviews to clarify the meaning of map elements. At the time of the interviews, each participant had implemented some kind of STEM education-related action multiple times and had opportunities to individually and collectively make sense (envision, enact, select, retain) of STEM education. Initially, each participant was asked if they were familiar with concept mapping and, if needed, given a brief overview about representing concepts and sub-concepts hierarchically. They were asked to construct a concept map in response to two questions: “What is your understanding or conception of STEM education? and What do you see as the most important ideas and sub-ideas?” Due to contextual constraints, participants created their concept maps in varied settings. The participants from the three schools were invited to meet with researchers in pairs or individually at a time convenient to them. The PD faculty developed their concept maps individually while all were in the same room. Each person was given as much time as needed to develop her/his map. The researcher read or wrote while participants were constructing their maps to alleviate potential discomfort. Participants were not held to using a traditional hierarchical structure in their mapping; as such, map formats ranged widely (Figs.  2 and 3 ).

Hierarchically arranged concept map from Hunter, RSA

Non-traditional concept map, Bridget, PD faculty

After concept mapping, semi-structured interviews were used to provide participants with another opportunity to make sense of their ideas about STEM education and inform the research findings. TrMS and RSA participants were interviewed immediately after constructing their maps. Due to time constraints, clarification of the maps of the PD faculty was done informally over the duration of the faculty meeting rather than with semi-structured interviews. However, for three PD faculties who constructed non-traditional concept maps (e.g., Fig.  3 ), semi-structured telephone interviews were conducted. Participants were asked to “talk us through” their concept maps. The interviewer would then follow up on a particular idea or ask a participant to elaborate on specific ideas they brought up. The researcher also asked what, if any, questions participants had about STEM education, and what supported them in coming to these particular views of STEM education. In cases where interviews were conducted in pairs, participants were asked to compare and contrast their maps or to comment on specific ideas that may have appeared on a colleagues’ map. For some participants, the interview prompted them to make modifications to the map or express additional ideas that were not on the map. For others, the interview did not result in additional information. In explaining the components of the map, participants could notice what they had included (or not) and how they had portrayed relationships between ideas.

Data analysis

Concept maps can be analyzed quantitatively and qualitatively (Greene et al. 2013 ). A quantitative analysis involves counting nodes (concepts), hierarchies (chains of sub-concepts out of one node), and cross-links between hierarchies to infer the complexity of the map creator’s understanding of the concept being represented. However, because we allowed each participant to represent their thinking in whatever way it made personal sense, some of the participants’ maps did not readily translate to quantitative analyses (e.g., did not include identifiable nodes or were global in nature, see Fig.  3 ). We chose to analyze the concept maps qualitatively and analyzed the interview data concurrently to aid our interpretation of the concept maps. We looked at the maps holistically, attending to the overall structure, the words used as nodes, and words used as cross-links. These analyses led to our primary results on the participants’ views of STEM education, including the emergence of our themes, and a secondary quantitative synthesis of each theme’s frequency across the participants’ context groups and role groups.

Generating themes

We drew on current research on STEM education as well as a grounded approach based on our interviews with teachers to generate our initial themes (Breiner et al. 2012 ; LaForce et al. 2014 ; Peters-Burton et al. 2014 ; Sanders 2009 ). We developed nine initial themes and added three others as the coding progressed. The initial themes were a synthesis of the way participants represented or talked about the attributes of STEM education and the major attributes that are described across the literature. For example, because project- or problem-based learning (PBL) tends to be situated in real-world contexts, we originally had one theme for PBL that included real-world connections. However, on a majority of concept maps, there were distinct nodes for real-world problem solving and others for attributes that characterized the student learning experience, regardless of whether it was within a PBL approach. Thus, we created different themes for these two distinct aspects of STEM education (RWPS, StLE; see Table  2 ).

The three codes (Val, TchNd, ChPrb in Table  2 ) were added later in the coding process to better capture significant themes that emerged in our analysis. For example, when we began coding the concept maps of the PD faculty, we saw ideas that related to opportunities to practice twenty-first century skills through PBL but also referred more generally to creating a STEM-literate citizenry. Thus, we created a separate theme to capture this more global perspective. Specifically, we coded nodes that focused predominantly on the abilities and dispositions of each student to communicate, work collaboratively, think creatively, or persevere in problem solving as “twenty-first century skills” (21CS). Nodes that reflected a broader conceptualization related to global citizenship and STEM literacy as having economic and other societal benefits were recoded as “value of STEM literacy” (Val).

We also developed two themes to reflect nodes associated with the conditions needed for implementing STEM-oriented teaching or curriculum. Ideas associated with what teachers might need in order to implement STEM education such as content knowledge and time for collaborative planning were coded as “teacher needs” (TchNd). Challenges and problems in implementing STEM education (ChPrb) showed up on some concept maps or, more frequently, emerged during the interviews. These responses ranged from structural constraints, such as lack of collaborative planning time or students in one class not having the same mathematics and science teachers (preventing extending projects across two class periods), to the politicization of STEM education.

Thematic analysis

In January 2015, the first author analyzed each map from the TrMS and RSA participants, generating themes based on the words participants used as nodes (concepts and sub-concepts) and cross-links (e.g., a line labeled “supplement each other” drawn between the nodes for “science” and “math” would be coded as IntDis for integration). Coding rules were developed and used to clarify the coding themes. In August 2015, PD institute faculty maps were obtained and coded by the first author, and coding rules were further elaborated. In September 2015, the second two authors and a research assistant coded six concept maps. After discussions with the first author, coding rules were further clarified and made more specific, especially to distinguish between student learning experiences and instructional practices. To check the reliability of our thematic coding on complex, non-traditional maps, the first author conducted follow-up interviews with three of the PD faculty and found that the initial coding accurately represented the mapmaker’s intentions. Based on the revised and/or clarified coding rules, the first author recoded all 34 concept maps, using the interview transcripts and concept maps concurrently. As the interview protocol probed for explanations about each map element, the transcripts helped clarify meanings or validate interpretations of cross-links and nodes.

Quantifying the themes

We coded 34 concept maps as described above and then counted how many people included each theme in their concept maps. After all maps were coded for the themes, we counted the occurrence of each theme, recorded these for each individual, and compiled the total inclusion of each theme. This allowed us to respond to our main research question. To address our two sub-questions, we then looked at the frequency of theme inclusion for each context group (RSA, TrMS, PD faculty) and also determined the frequency of inclusion of each theme by general role groups: STEM teachers (18 secondary math, science, technology, engineering, CTE teachers), non-STEM teachers (5 secondary special education or ELL teachers), school or district administrators (5), and non-school-based external partners (6 partners from businesses or organizations or regional PD providers). We present a discussion of our analyses in the next section.

Limitations

The use of concept maps to elicit conceptualizations of STEM education has multiple limitations. Although we allowed participants to construct their maps in non-traditional ways, including writing a paragraph instead of mapping, some may have felt uncomfortable portraying their ideas using this type of representation or may not have included all their ideas. While the interviews provided an opportunity for participants to add to or expand upon their representations, participants may have held ideas they did not want to share, lacked the ability or language to represent, or perhaps were not considering at the time of the interview. Moreover, participants may not have mentioned certain ideas they perceived as obvious, such as the inclusion of all students in STEM experiences. There are also limitations related to the participant pool. There were limited numbers of non-STEM teachers (5), administrators (5), and external partners (6) in comparison with the number of STEM teachers (18) who participated. However, the concept maps and interviews with all participants provide insight into the variation that is possible in making sense of STEM education.

We address our main research question by showing the frequency of the various themes relevant to STEM education (coding categories) that were included in individual concept maps (Table  3 ) and providing examples that show different individual’s conceptualizations of the theme at the time. We then address sub-question A by showing the frequency of theme inclusion by context group (Table  4 ) and examining relationships between the conceptualizations of STEM education and the context in which participants implemented STEM education activities. Finally, we address sub-question B by organizing the themes by role group (Table  5 ) and discussing potential relationships between the responsibilities inherent in specific roles and the elements of STEM education that surfaced in the concept maps among participants in that role. Our data suggest that certain aspects of STEM education are more salient in participants’ conceptions, and both context and role group contribute to these conceptions.

Making sense of STEM education

We first tabulated the inclusion of theme by individuals and calculated the percentage of participants who included each theme. As shown in Table  3 , there were three common themes on the concept maps: a connection across disciplinary subjects (IntDis), a focus on what teachers must attend to instructionally (InstPrac) when implementing a STEM approach, and explicit connections between in-school content and out-of-school problems or contexts (RWPS).

Interview data provided detail on how each participant conceptualized these themes. For example, when asked what her inclusion of the word “integration” meant (IntDis), a special education teacher from the TrMS group explained:

The reading, the writing, the art, the creativity. You know? You’re using computer skills. You’re using building skills. … So it makes [students] use everything. And the cool thing is they don’t know they’re using all that. (Brenda, interview, January 29, 2015)

A member of the PD faculty who was also the principal of an elementary STEM school talked about how real-world problems helped the teachers develop integrated curricula:

What we do is intentionally interweave the S, the T, the E, the M into instruction. So, at a typical elementary or middle school, often subjects are segmented and segregated, kind of siloed. Our commitment is that our students are doing STEM every day … . We intentionally plan STEM … we take the standards and cut them all apart and then piece them all together so we have consistent themes or overarching problems for students to solve. (Bridget interview, September 30, 2015)

A middle school science teacher from RSA also included real-world connections and instructional decision-making on his map. In his interview, he explained why real-world connections were important and how he developed these:

And so I started with real world scenarios, just because to me the science, technology, engineering and mathematics, kind of the end goal is getting students more fully prepared for real life. And so having them deal with real world scenarios helps them to do that. Couple of different ways to do that, one I had input from professionals … .And then opportunities to see and experience that real world, or real work, environment or conditions. (Hunter interview, November 4, 2014)

Participants represented these three themes (integration, real-world connections, and instructional practices) separately on their maps but, as seen by these comments, often revealed significant relationships among these themes in their interviews.

Over half of all participants included attributes of students’ learning experiences (StLE) and students’ opportunities to develop twenty-first century skills (21CS) as salient features of STEM education. Ideas related to the attributes of the student learning experience were represented on 59% of concept maps. Comments about this often addressed students’ engagement in the authentic practices of each discipline. A high school math teacher at RSA explained that “Kids should be looking for patterns, engaged in the real work of scientists and mathematicians” (Greg, October 19, 2015). A scientist who was a member of the PD faculty described that the student learning experience should involve “designing and developing within constraints [as this] models real world scenarios. .. realizing it is okay to learn from failure and that there isn’t just one right answer all the time” (Sophie interview, September 30, 2015).

The opportunity for students to develop and practice twenty-first century skills and dispositions was also included on over half of the concept maps. Participants listed specific skills, such as collaboration, communication, and perseverance. Expanding on this area in interviews, some connected these skills to career and life opportunities. As a TrMS math teacher described:

I think the end goal, what I would really want is students who can problem solve. … Life problems, work problems, I mean for years I’ve just thought employers just want employees who can think and take care of the problems at hand. Not have to be told, “Do this, do this, do this.” And so if you’re a problem solver you’re going to be a great employee. If you’re a problem solver you’re going to be a great inventor. (Olivia interview, January 26, 2015)

Less than one third of the participants included an explicit reference to STEM education as providing opportunities for all students to participate and be successful (Equ). Also, less than one third included ideas about technology (Tech), other than to write the word “technology” as part of STEM. We further discuss the low representation of these categories in the next section.

Making sense of STEM education in different contexts

In this section, we address sub-question A regarding the themes educators in different professional contexts included in their conceptualizations of STEM education and the possible relationships between an individual’s conception of STEM education and the context in which she/he works. We first calculated the frequency of the inclusion of each theme for each context group. Table  4 shows that within context groups, different categories were more salient than others. We draw from our descriptions of the PD and school environments to consider potential relationships between the attributes of each context group’s STEM education work and the themes that were most or least commonly identified within that group.

Aside from the attributes common across all participants (interdisciplinary, instructional practices, and real-world problem solving), the statewide PD faculty, a group composed of people with a wide variety of backgrounds, commonly focused on broader concepts such as the global, societal value of STEM education (Val). This was also an overall theme of the summer STEM leadership institute developed by the PD faculty. The maps from the PD faculty also highlighted partnerships (Prtnr) between STEM professionals, teachers, and students. Claudia, a regional PD provider, indicated that STEM education benefits from community connections with “professionals in STEM, professionals related to STEM, informal science educators” and “benefits with support from parents, community professionals, and administrators” (Claudia concept map, May 7, 2015). The development of partnerships between schools and STEM professionals was addressed in multiple sessions during the institute, and two thirds of the PD faculty retained ideas about this attribute of STEM education when constructing their concept maps.

Ideas related to technology (Tech) were not commonly included on the PD faculty maps. Three of the four who included technology were people who worked most directly with it: the STEM school principal whose third- through eighth-grade students all had iPod touches or laptops, one of the business partners, and the district-level CTE director. On the fourth map that included technology, the strand of ideas was “STEM education ➔ multiple academic subjects ➔ technology [is] ill-defined” (Abel concept map, May 7, 2015). Abel’s notation is indicative of the confusion around what the T in STEM education means. At the institute, an invited presenter described how K-12 educators are uncertain about whether technology now means computer science, students’ and teachers’ use of information and communication technology (e.g., the internet; word processing and presentation tools), or tools more commonly found in CTE courses, such as 3D printers.

Forty-four percent of the PD faculty included an explicit relationship between STEM education and equitable learning opportunities (Equ), using phrases such as “teaching every child” (Marion concept map, May 7, 2015). Carlton expanded on this perspective: “It’s about the individual kid, not the industrial model of kids [coming through school]” (Carlton interview, September 30, 2015). Equity was a major theme of the institute, including a focused session at the beginning of the week and embedded in multiple sessions throughout.

Only one third of the PD faculty included standards (Stan), although standards received significant attention in a number of sessions during the institute. Also, less than half of this group included ideas about the student learning experience (StLE) or twenty-first century skills (21CS). The nature of the student experience in a STEM learning environment was modeled in a half-day session, although ideas about students’ opportunities to practice and develop twenty-first century skills were more implicit across sessions. The roles of PD faculty outside of the context of the institute might better explain why these three themes were not more frequently included on the concept maps of this group. We will discuss that in a subsequent section.

As shown in Table  4 , 50% or more of the participants in the TrMS group included attributes directly related to curriculum and instruction: interdisciplinary curriculum, ambitious instructional practices, attributes of students’ learning experiences, twenty-first century skills, standards, and real-world problem solving, in that order. These themes directly relate to elements of the professional development the teachers participated in for 2 years, where STEM design challenges were presented as a way to integrate standard-based mathematics and science content into existing curricula.

Over 50% of the participants from these two traditional middle schools also included ideas about various challenges associated with the implementation of STEM education (ChPrb). This reflects the constraints presented by their school contexts, including “time for planning” and “difficulties with creating in-depth integrated math and science problems.” Another challenge related to school structures that inhibited enacting the interdisciplinary, project-based curriculum units they were exploring in the TESI PD project. An eighth-grade science teacher explained:

The way our building is lined up or our schedule is we’re not in teams by any means. I mean my kids go off and see three different math teachers. So if it was ideal they’d have one math teacher, one science teacher, one humanities and we could do a little bit more of that integration, true integration. (Anthony interview, December 9, 2014).

Over 50% of the TrMS participants included references to standards (Stan) on their maps or mentioned these in interviews. Again, the context was important. Many of the comments reflected a negative relationship between the need to address standards and the desire to enact interdisciplinary, project-based curricula. Shawn, an eighth-grade teacher who had developed a new STEM elective course, commented on standards in this way:

I mean [this STEM course] is a great opportunity and I hope others get the chance and embrace it and run with it because I think it’s got a chance to be really successful and get some kids far better prepared for the real world than just learning back again state standards and stuff. I’ve probably been negative about state standards in my comments, and they’re important, but I don’t know that they focus enough on the STEM related skills, the integration of all this stuff to give kids successful opportunities to fulfill roles in business as problem solvers. (Interview, December 9, 2014)

These participants worked in two traditional middle schools in a district and state context where teachers were attempting to understand how to support students in meeting CCSS for mathematics and language arts, as measured by state achievement test data. Teachers were also just becoming familiar with the NGSS, both through the TESI project and other regional and district-level PD events. While the curricular units provided by the TESI project were aligned, the other instructional materials provided by the district were purchased prior to these new standards.

Ideas related to the access and opportunity for all students (Equ) were included on one third of the TrMS participants’ maps. The TESI summer institute was designed to help teachers recognize ways to support all students’ successful participation in STEM learning. For a week, students who had struggled with the content of their math or science courses joined their teachers in tackling engineering design challenges. Only four teachers explicitly identified this as an important feature of STEM education. A sixth-grade math teacher stated: “All kids bring skills, everyone’s good at something, no one’s good at everything” (Regan concept map, January 29, 2015) and a sixth-grade special education teacher constructed this strand on her map: “STEM education ➔ very inclusive ➔ kids of many levels can access something” (Brenda concept map, January 29, 2015). Others may have implied ideas about equity in other aspects of their concept maps, but there were no other explicit words or ideas either on maps or in interviews that we could code for this theme.

Three themes were seldom included or not included at all. Only one person from the TrMS group included ideas related to technology (Tech) and connecting it to “research skills.” This is not too surprising for traditional schools; one teacher pointed out the non-working Wi-Fi router on her classroom ceiling, and others commented that CTE classes were the only places where students could access technological tools. Students’ use of technology in the form of robotics was modeled in the summer PD but received little explicit attention other than that. Partnerships (Prtnr) and a broader value for STEM education (Val) did not appear on any concept maps in the TrMS group. While a variety of STEM professionals contributed to the activities of the summer institute, the development of partnerships in relation to supporting students’ interests in STEM careers and learning opportunities was not an explicit element of the PD.

Similar to the TrMS group, the participants from RSA most frequently included themes directly related to the classroom (IntDis, RWPS, InstPrac, StLE, 21CS; see Table  4 ). Also, over 50% of the RSA participants included partnerships (Prtnr) as an element of STEM education. This reflected a focus of their school philosophy, where building sustainable partnerships was supported with a half-time faculty position dedicated to cultivating business and academic partners to support student learning. The high school art teacher connected “relevance to real-world experiences” to “work-based learning and internships” (Josh concept map, October 15, 2015) and the principal represented this theme with a connection from STEM education to “extended learning opportunities and mentors” (Sandra concept map, June 4, 2015).

Similar to the other context groups, only 5 of the 13 participants from RSA included ideas about technology (Tech), although the technology was an explicit component of the school. A middle school history and language arts teacher who did include technology on his map explained why he positioned it as one of the major nodes: “I feel technology is embedded into everything. Because technology is just something that helps make the job easier” (Jason interview, November 4, 2014). The robotics and pre-engineering teacher discussed her vision for how technology should be integral to a STEM school:

I think for STEM education, space is very important and that’s one thing that we lack here. For maker space, fabrication projects, things like that. I mean both room as well as having the tools available. So C&C machines, we have a 3D printer but we haven’t been trained on using it yet. You know I mean just . . . any type of thing that you can think that a student might want to use to create. (Rachel interview, November 6, 2014)

The technology was of great importance to some of the RSA participants but not considered by the majority.

Ideas related to standards (Stan) were included on less than one third of the concept maps of the participants from RSA. While these teachers worked in the same state context as the TrMS teachers, they were located in a different district. More importantly, their school context differed. Teachers may have been more focused on the need to develop curriculum to address the school vision of interdisciplinary, project-based learning than to align with standards. However, the high school science teacher was very focused on the NGSS and developed two relevant strands on his concept map, one that connected STEM education ➔ integration ➔ 3D teaching ➔ science practices, concepts, and cross-cutting ideas, and another that connected STEM education to the K-12 Framework (National Research Council 2012 ). Alternately, the high school math teacher talked at length about how the pressures from testing specific standards at specific times was a roadblock to project-based learning: “I could develop a four-year program that would get kids to all standards, but the way it’s going now. .. we are trying to fill in skill gaps so how can we get into that real world stuff?” (Greg interview, October 19, 2015).

Finally, few of the RSA participants (15%) included or talked about opportunities for all students in STEM education (Equ). The principal wrote, “Do everything you can to support student success – make it happen” as the overarching concept on her map, and further explained in her interview:

You do everything you can to support student success and you make it happen. That’s what we’re after. Because every child can learn, every child wants to learn and be successful. And we just have practices and things in place in K-12 that separate out, that rank, and we know in our hearts and in our minds that not all students learn everything at the same pace, the same rate. It doesn’t mean they can’t learn or they won’t learn. (Sandra interview, June 4, 2015)

Also, the robotics teacher connected the curriculum ideas on her map to the challenge she faced in getting more girls interested in STEM areas (Rachel interview, November 6, 2014). Others did not specifically reference ideas related to equitable student opportunities. RSA opened as an inclusive STEM school and from conversations with RSA teachers separate from the data collection for this study, we know teachers are well aware of the need to support all kinds of students in STEM learning. However, based on the concept map data and interviews, teachers were not making explicit connections between the “most important ideas about STEM education” and opportunities for all students.

Making sense of STEM education by role group

Given the multiple roles represented by the participants in this study, we next examined whether there would be notable similarities or differences in the conceptualizations of STEM education based on participants’ professional responsibilities (sub-question B; Table  5 ). Table  5 is organized in descending order of the most commonly included concept map themes by individual participants, making for an easy comparison between the global findings (reported in Table  3 ) and the frequency of inclusion by role group. Teachers of STEM-specific courses comprised the largest group, with 18 participants. Thus, it is not surprising that the most commonly included themes by individual and by context group are also those that STEM teachers most commonly included. Science, mathematics, technology, and CTE teachers are directly responsible for implementing the individually and/or collectively constructed vision of STEM education. They must identify or develop interdisciplinary curricula (IntDis) and determine how to bridge from in-school to real-world problems (RWPS). They understand that supporting students in the project- or problem-based learning experiences (StLE) will require instructional approaches that may differ from traditional, teacher-centered practices (InstPrac).

The interdisciplinary nature of STEM learning was by far the most salient feature for non-STEM teachers as well, and a significant focus by the administrators and external partners.

The art teacher from RSA explained:

I added art in there because I feel like that’s important. Turning it into STEAM. But like literally every single thing is intermingled. Like it’s a melting pot. All of it just goes together. Basically no matter what assignment, project, anything you pick you can connect every single one of these STEM or STEAM aspects into one another. (Brittany interview, November 10, 2014).

Real-world problem solving (RWPS) and ideas about instructional practices (InstPrac) were also included by the majority of non-STEM teachers, but the remaining themes were not consistently included. Many of the non-STEM teachers connected the need for an interdisciplinary approach to real-world problem solving yet faced challenges in connecting this approach to the standards they felt necessary to address. A sixth-grade special education teacher in the TrMS group explained that she wanted to bring in “Kind of authentic experiences and real-world [problems]” yet found that “it’s hard to integrate the 6th grade standards with STEM. I wish we had more time.” (Brenda interview, January 29, 2015).

School and district administrators all included ideas related to instructional practices, and most also included ideas about the student learning experience (StLE) and interdisciplinary curricula (IntDis). Administrators largely recognized most of the thematic elements of STEM education, except for the more global value (Val). In comparison, nearly all the external partners (regional PD providers and business or organization partners) included ideas related to this broader value of STEM education (Val) as well as connections to real-world problems (RWPS). Similar to all the role groups, the interdisciplinary nature of STEM curricula (IntDis) was included by most. External partners included external partnerships at a higher frequency than other groups.

As in the case of PD context, there is an indication in these data that the responsibilities of one’s specific job contribute to the elements of STEM education that are retained. Administrators, who tend to have responsibilities that relate to a large number of educational issues, gave explicit attention to numerous elements. Similarly, the broader outlook of the external partners, reflected in their attention to global values of STEM education in their concept maps, is consistent with their duties and responsibilities inside the STEM education system.

The ways in which the teacher participants made sense of STEM education was also consistent with their roles and responsibilities. Most teachers found interdisciplinary and real-world connections to be especially relevant. However, STEM teachers were also more likely to consider content standards, instructional approaches commonly associated with STEM education such as project-based learning, and twenty-first century skills in their conceptions. Non-STEM teachers were much more attentive to more general attributes of instruction, such as student-centered practices, engagement, and participation.

Those working with the implementation of STEM education are well aware that while core elements have been identified (Kelley and Knowles 2016 ; LaForce et al. 2014 ), there are still varying conceptions of what a STEM school or program entails. In this way, enacting STEM education entails innovation and motivates sensemaking. Our research shows that even when educators have similar professional learning experiences and/or work in the same contexts, they may make sense of what this innovation means quite differently. What is seen as most important to attend to or innovate around may differ in relation to professional roles and contexts.

Sensemaking provided a useful framework (Fig.  1 ) for considering the influence of institutional and professional contexts in shaping each educator’s construction of a plausible story of STEM education. Context appears to have some relationship with the ideas about STEM education noticed and retained by participants. This is most apparent in relation to partnerships, a key feature of the PD faculty work and of RSA. The identity of RSA as a STEM school supported teachers’ sensemaking about elements associated with STEM education such as interdisciplinary curricula, project-based learning, inclusion, and partnerships; these were part of the school vision statement. On the other hand, the professional identities of non-STEM teachers (e.g, English or history teachers) and STEM teachers shaped their individual meaning-making in relation to a STEM-focused curriculum. Teachers at the two middle schools were enacting STEM curricula in the context of a traditional middle school, with compartmentalized science and mathematics and a curricular focus aligned with statewide tests. Given these constraints, teachers in a more traditional school context may not take up ideas about STEM education that they encounter in professional learning experiences as readily as those in a STEM school context. The PD faculty worked in various professional contexts, with most in non-school settings. The STEM education ideas most salient to these scientists, business partners, and regional educators differed notably from those of STEM and non-STEM teachers.

In addition to the influence of institutional and organizational contexts, opportunities for collective reflection on the enactment of ideas associated with STEM education also contribute to an individual’s sensemaking (Davis 2003 ). Talking about actions involves “sensegiving,” which serves both to give information or feedback to others as well as an opportunity to “hear what one thinks” and further develop a plausible story (Weick et al. 2005 , p. 416). For the TrMS teachers, there was an ongoing dialog with their colleagues, the PD providers, their instructional coaches, and their administrators. We can imagine that not only the traditional structures of the schools but also the differing ideas about and experiences with curriculum, instruction, and learning held by everyone involved in these conversations influenced the STEM education ideas the TrMS teachers selected and retained. Similarly, the PD faculty came together at least twice per year over 3 years to continually refine and co-construct their understandings about STEM education. Each drew upon relevant experiences from their professional roles and from educational research as they collectively developed a STEM education framework for each summer institute. At RSA, teachers met weekly to jointly develop curriculum and discuss student progress and school development. Teachers and administrators received feedback from the community of STEM professionals, parents, and district administrators, which also informed their conversations and subsequent sensemaking.

As shown in Table  3 , our findings show the majority of educators in this study shared some common ideas about what is important for STEM education. However, identifying attributes and realizing these in practice are very different. For example, the interdisciplinary or integrated curriculum was the most identified theme across all concept maps. However, this may not be easily accomplished at many middle and high schools in the USA, as disciplinary skills and knowledge are often siloed, pacing guides determine time devoted to a given concept, and students move to different teachers in different groups. Opportunities to set up and engage in long-term STEM-related projects are constrained by these institutionalized practices as well as by space and equipment. Addressing this commonly identified attribute of STEM education will require tremendous creativity and resources.

Our analysis revealed other attributes that only a few included. The overall low representation of STEM education as an opportunity for all students is troubling. It may be that this was a concept educators considered but held distinct from STEM education. However, it has been apparent in education that when equity is not explicitly named and addressed, it is overlooked; Rodriguez ( 1997 ) termed this “the dangerous discourse of invisibility.” The inclusion of all students in STEM learning was emphasized in each of the contexts in this study yet failed to be retained as a salient attribute. The development of a STEM-literate citizenry and increased opportunities for all students to pursue STEM-related professions will require educators to explicitly address how students are included in or excluded from meaningful STEM learning.

Our data suggest that professional roles and contexts influence the vision educators develop about STEM education. These results raise questions about the coherence of this innovation when people in the same school or district make sense of it in such different ways. Given the variety of institutionalized practices and contexts across schools, we are not convinced that a single worldwide definition of STEM education is critical. What we do see as essential is that those working in the same system, be it a department, school, or district, explore the common elements that are being attributed to STEM education and co-construct a vision that provides opportunities for all their students to attain STEM-related goals. Visioning, however, is insufficient, as what is envisioned and what is implemented are often very different. Educators must push on the status quo in areas of instruction, curriculum, learning opportunities, assessment, and school structures. Sensemaking as a collaborative, reflective, and iterative process can surface the differences and commonalities in people’s understandings to better ensure consistency in students’ learning opportunities across classrooms.

We propose that collective sensemaking through professional dialog be an explicit and ongoing activity when planning for and implementing STEM education. Supporting dialog among stakeholders from different contexts and professional roles is critical in order to ensure that diverse perspectives about the attributes for STEM teaching, learning, and curricula can be raised and discussed. For example, community members and policymakers may take a more global perspective focused on economic and societal implications. STEM and non-STEM teachers may focus on different aspects of the learning experience. Administrators are positioned to make sense of how individual teachers’ efforts contribute to student opportunities.

While it has been well established that professional development experiences, school vision statements, or readings about an innovation do not directly translate into the classroom and school practices (Penuel et al. 2008 ), explicitly identifying the ideas educators are and are not selecting and retaining can inform professional learning activities at local and larger scales. Further research is needed to understand more specifically what ideas educators notice, select, and retain about STEM education and how to support educators’ construction of plausible stories that promote a consistent vision of STEM education across a system.

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• STEM Education
• Traditional Middle School (TrMS)
• Concept Mapping
• Sensemaking
• Real-world Problem Solving

What is STEM Education?

STEM education, now also know as STEAM, is a multi-discipline approach to teaching.

• Importance of STEAM education

STEAM blended learning

• Inequalities in STEAM

Additional resources

Bibliography.

STEM education is a teaching approach that combines science, technology, engineering and math . Its recent successor, STEAM, also incorporates the arts, which have the "ability to expand the limits of STEM education and application," according to Stem Education Guide . STEAM is designed to encourage discussions and problem-solving among students, developing both practical skills and appreciation for collaborations, according to the Institution for Art Integration and STEAM .

Rather than teach the five disciplines as separate and discrete subjects, STEAM integrates them into a cohesive learning paradigm based on real-world applications. 

According to the U.S. Department of Education "In an ever-changing, increasingly complex world, it's more important than ever that our nation's youth are prepared to bring knowledge and skills to solve problems, make sense of information, and know how to gather and evaluate evidence to make decisions." 

In 2009, the Obama administration announced the " Educate to Innovate " campaign to motivate and inspire students to excel in STEAM subjects. This campaign also addresses the inadequate number of teachers skilled to educate in these subjects. 

The Department of Education now offers a number of STEM-based programs , including research programs with a STEAM emphasis, STEAM grant selection programs and general programs that support STEAM education.

In 2020, the U.S. Department of Education awarded $141 million in new grants and $437 million to continue existing STEAM projects a breakdown of grants can be seen in their investment report .  

The importance of STEM and STEAM education

STEAM education is crucial to meet the needs of a changing world. According to an article from iD Tech , millions of STEAM jobs remain unfilled in the U.S., therefore efforts to fill this skill gap are of great importance. According to a report from the U.S. Bureau of Labor Statistics there is a projected growth of STEAM-related occupations of 10.5% between 2020 and 2030 compared to 7.5% in non-STEAM-related occupations. The median wage in 2020 was also higher in STEAM occupations ($89,780) compared to non-STEAM occupations ($40,020).

Between 2014 and 2024, employment in computer occupations is projected to increase by 12.5 percent between 2014 and 2024, according to a STEAM occupation report . With projected increases in STEAM-related occupations, there needs to be an equal increase in STEAM education efforts to encourage students into these fields otherwise the skill gap will continue to grow. 

STEAM jobs do not all require higher education or even a college degree. Less than half of entry-level STEAM jobs require a bachelor's degree or higher, according to skills gap website Burning Glass Technologies . However, a four-year degree is incredibly helpful with salary — the average advertised starting salary for entry-level STEAM jobs with a bachelor's requirement was 26 percent higher than jobs in the non-STEAM fields.. For every job posting for a bachelor's degree recipient in a non-STEAM field, there were 2.5 entry-level job postings for a bachelor's degree recipient in a STEAM field. 

What separates STEAM from traditional science and math education is the blended learning environment and showing students how the scientific method can be applied to everyday life. It teaches students computational thinking and focuses on the real-world applications of problem-solving. As mentioned before, STEAM education begins while students are very young:

Elementary school — STEAM education focuses on the introductory level STEAM courses, as well as awareness of the STEAM fields and occupations. This initial step provides standards-based structured inquiry-based and real-world problem-based learning, connecting all four of the STEAM subjects. The goal is to pique students' interest into them wanting to pursue the courses, not because they have to. There is also an emphasis placed on bridging in-school and out-of-school STEAM learning opportunities. 

– Best microscopes for kids

– What is a scientific theory?

– Science experiments for kids  

Middle school — At this stage, the courses become more rigorous and challenging. Student awareness of STEAM fields and occupations is still pursued, as well as the academic requirements of such fields. Student exploration of STEAM-related careers begins at this level, particularly for underrepresented populations. 

High school — The program of study focuses on the application of the subjects in a challenging and rigorous manner. Courses and pathways are now available in STEAM fields and occupations, as well as preparation for post-secondary education and employment. More emphasis is placed on bridging in-school and out-of-school STEAM opportunities.

Much of the STEAM curriculum is aimed toward attracting underrepresented populations. There is a significant disparity in the female to male ratio when it comes to those employed in STEAM fields, according to Stem Women . Approximately 1 in 4 STEAM graduates is female.  

Inequalities in STEAM education

Ethnically, people from Black backgrounds in STEAM education in the UK have poorer degree outcomes and lower rates of academic career progression compared to other ethnic groups, according to a report from The Royal Society . Although the proportion of Black students in STEAM higher education has increased over the last decade, they are leaving STEAM careers at a higher rate compared to other ethnic groups. 

"These reports highlight the challenges faced by Black researchers, but we also need to tackle the wider inequalities which exist across our society and prevent talented people from pursuing careers in science." President of the Royal Society, Sir Adrian Smith said. 

Asian students typically have the highest level of interest in STEAM. According to the Royal Society report in 2018/19 18.7% of academic staff in STEAM were from ethnic minority groups, of these groups 13.2% were Asian compared to 1.7% who were Black. 

If you want to learn more about why STEAM is so important check out this informative article from the University of San Diego . Explore some handy STEAM education teaching resources courtesy of the Resilient Educator . Looking for tips to help get children into STEAM? Forbes has got you covered.  

• Lee, Meggan J., et al. ' If you aren't White, Asian or Indian, you aren't an engineer': racial microaggressions in STEM education. " International Journal of STEM Education 7.1 (2020): 1-16. 
• STEM Occupations: Past, Present, And Future . Stella Fayer, Alan Lacey, and Audrey Watson. A report. 2017. 
• Institution for Art Integration and STEAM What is STEAM education? 
• Barone, Ryan, ' The state of STEM education told through 18 stats ', iD Tech.  
• U.S. Department of Education , Science, Technology, Engineering, and Math, including Computer Science.  
• ' STEM sector must step up and end unacceptable disparities in Black staff ', The Royal Society. A report, March 25, 2021.  
• 'Percentages of Women in STEM Statistics' Stemwomen.com  

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AACC, NSF Announce Winning Teams of 2024 Community College Innovation Challenge

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Jun 13, 2024, 17:15 ET

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Georgia Perimeter College at Georgia State University ; Dallas College ; and County College of Morris took home winning titles following presentations of their STEM innovations to address real-world challenges

WASHINGTON , June 13, 2024 /PRNewswire/ -- Today, the American Association of Community Colleges (AACC), in partnership with the U.S. National Science Foundation  (NSF), announced the three winning teams of this year's  Community College Innovation Challenge  (CCIC). 

The annual competition seeks to strengthen entrepreneurial thinking among community college students by challenging them to develop STEM-based solutions to real-world problems. It also enables students to discover and demonstrate their capacity to use STEM to make a difference in the world and to translate that knowledge into action. 

The first, second and third-place winning teams and their innovations are listed below.

First Place:  Perimeter College at Georgia State University , GA Project: Gorginea Care

Second Place: Dallas College , TX Project: Autonomous Monitoring for Blaze Emergency Response (AMBER)

Third Place: County College of Morris , NJ Project: Doing the MOST with NBD-QC

This week, 12 community colleges selected as finalists in a national competition attended an Innovation Boot Camp where they learned from entrepreneurs and experts in business planning, stakeholder engagement, strategic communication, and marketplace dynamics. The Boot Camp culminated in a Student Innovation Poster Session with STEM leaders and congressional stakeholders, and a 5-minute pitch presentation to a panel of industry and entrepreneurial professionals determining the winning teams.

"Year after year, I am thrilled to witness the promising talent that the Community College Innovation Challenge brings together," said James L. Moore III , assistant director for STEM Education. "The student participants represent both the present and future of STEM by addressing some of the most pressing challenges of our times. NSF is proud to co-sponsor CCIC and to congratulate the students for doing an outstanding job translating their knowledge into action."

Among the ideas the 12 finalist teams presented this year are innovative and transformative solutions that address clean water; renewable energy and energy storage; HIV treatment; women's healthcare; fire prevention; combating plastic waste; and providing accessible solutions for people with disabilities.

"Truly inspiring," said Walter G. Bumphus , president and CEO of AACC. "We are so proud to be afforded the opportunity to provide these resources for community college students to showcase their innovative and creative solutions to real-world issues. The projects featured show the amazing potential these students have to make meaningful economic and societal impact. Congratulations to the team from Georgia Perimeter College at Georgia State University and to all of the finalists."

To receive updates about the CCIC's 2024 winners, follow @Comm_College  or visit www.aaccinnovationchallenge.com .

About AACC As the voice of the nation's community colleges, the American Association of Community Colleges (AACC), delivers educational and economic opportunity for more than 10 million diverse students in search of the American Dream. Uniquely dedicated to access and success for all students, AACC's member colleges provide an on-ramp to degree attainment, skilled careers, and family-supporting wages. Located in Washington, D.C. , AACC advocates for these not-for-profit, public-serving institutions to ensure they have the resources and support they need to deliver on the mission of increasing economic mobility for all. https://www.aacc.nche.edu/ .

About NSF About NSF The U.S. National Science Foundation propels the nation forward by advancing fundamental research in all fields of science and engineering. NSF supports research and people by providing facilities, instruments and funding to support their ingenuity and sustain the U.S. as a global leader in research and innovation. With a fiscal year 2024 budget of $9.06 billion , NSF funds reach all 50 states through grants to nearly 2,000 colleges, universities and institutions. Each year, NSF receives more than 40,000 competitive proposals and makes about 11,000 new awards. Those awards include support for cooperative research with industry, Arctic and Antarctic research and operations, and U.S. participation in international scientific efforts.  https://www.nsf.gov .

SOURCE American Association of Community Colleges

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The following is written by Mary S. Graham, Ph.D., President, Mississippi Gulf Coast Community College, a member of the American Association of...

STEM (Science, Tech, Engineering, Math)