integrated approach in science and technology essay

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• Published: 13 December 2021

Beyond the basics: a detailed conceptual framework of integrated STEM

• Gillian H. Roehrig   ORCID: orcid.org/0000-0002-6943-7820 1 ,
• Emily A. Dare 2 ,
• Joshua A. Ellis 2 &
• Elizabeth Ring-Whalen 3  

Disciplinary and Interdisciplinary Science Education Research volume  3 , Article number:  11 ( 2021 ) Cite this article

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Given the large variation in conceptualizations and enactment of K − 12 integrated STEM, this paper puts forth a detailed conceptual framework for K − 12 integrated STEM education that can be used by researchers, educators, and curriculum developers as a common vision. Our framework builds upon the extant integrated STEM literature to describe seven central characteristics of integrated STEM: (a) centrality of engineering design, (b) driven by authentic problems, (c) context integration, (d) content integration, (e) STEM practices, (f) twenty-first century skills, and (g) informing students about STEM careers. Our integrated STEM framework is intended to provide more specific guidance to educators and support integrated STEM research, which has been impeded by the lack of a deep conceptualization of the characteristics of integrated STEM. The lack of a detailed integrated STEM framework thus far has prevented the field from systematically collecting data in classrooms to understand the nature and quality of integrated STEM instruction; this delays research related to the impact on student outcomes, including academic achievement and affect. With the framework presented here, we lay the groundwork for researchers to explore the impact of specific aspects of integrated STEM or the overall quality of integrated STEM instruction on student outcomes.

Since the term “STEM” (Science-Technology-Engineering-Mathematics) was coined in 2001, there have been numerous efforts to improve K − 12 STEM teaching and learning around the world (Freeman et al., 2014 ). With the release of STEM policy documents across the globe (e.g., Australian Curriculum, Assessment, and Reporting Authority, 2016 ; European Commission, 2015 ; Hong, 2017 ; National Research Council (NRC), 2012), the implementation of STEM in K − 12 education has focused on interdisciplinary or integrated instruction, commonly referred to as “integrated STEM education”, rather than separate disciplinary approaches to the teaching of science, technology, engineering, and mathematics. While integrated STEM education is well established through national and international policy documents, disagreement on models and effective approaches for integrated STEM instruction continues to be pervasive and problematic (Moore et al., 2020 ). Sgro et al. ( 2020 ) argue that, in essence, integrated STEM is “whatever someone decides it means” and that the large variation across integrated STEM curricula suggests a need for “greater clarity about not only what constitutes STEM education, but how educators as a whole conceptualize STEM and the process of integration” (p. 185). In response, this paper puts forth a detailed conceptual framework for K − 12 integrated STEM education that can be used by researchers, educators, and curriculum developers as a common vision.

Various broad definitions of integrated STEM education exist in the literature and policy documents. For example, Moore, Stohlmann, and colleagues (2014) defined integrated STEM education as “an effort to combine some or all of the four disciplines of science, technology, engineering, and mathematics into one class, unit, or lesson that is based on connections between the subjects and real-world problems” (p. 38). Similarly, Kelley and Knowles ( 2016 ) defined integrated STEM as “the approach to teaching the STEM content of two or more STEM domains, bound by STEM practices within an authentic context for the purpose of connecting these subjects to enhance student learning” (p. 3). Common across almost all definitions is the use of real-world contexts to both contextualize learning and motivate student engagement (e.g., Kelley & Knowles, 2016 ; Kloser et al., 2018 ; National Academy of Engineering (NAE) and NRC, 2014). While some researchers argue for integration across all four of the STEM disciplines (e.g., Burrows et al., 2018 ; Chandan et al., 2019 ), others call for the integration of at least two of the STEM disciplines (e.g., Moore et al., 2020 ). Given the prominence of engineering within STEM policy documents (e.g., NRC, 2012; NGSS Lead States, 2013 ), many approaches to integrated STEM specifically include an engineering context or engineering design problem as the context for learning (e.g., Berland & Steingut, 2016 ; Mehalik et al., 2008 ; Moore, Stohlmann, et al., 2014). Indeed, Nathan et al. ( 2013 ) argue, the ideals of STEM integration are not likely to be fulfilled by the integration of any pair of STEM fields … the pairing of technology with engineering (the design sciences) is insufficient to satisfy STEM integration, and also excludes pairing science and math (the natural sciences). Rather, it calls for STEM integration that spans the design and natural sciences. (p. 82).

In addition to the centrality of engineering and connection to real-world problems, other aspects of integrated STEM on which there is consensus in the literature include: (a) the use of student-centered pedagogies (e.g., Asunda & Mativo, 2017 ; Johnson et al., 2016 ; Thibaut et al., 2018 ), (b) supporting the development of twenty-first century skills such as creativity, collaboration, communication, and critical thinking (e.g., Sias et al., 2017 ; Wang & Knoblach, 2018), and (c) connections between STEM disciplines should be made explicit to students (e.g., English, 2016 ; Kelley & Knowles, 2016 ; NAE and NRC, 2014). While there is consensus on these aspects as being central to broad definitions of STEM, the literature does not provide detail on how these aspects should be operationalized for quality implementation of integrated STEM education in K − 12 classrooms.

While integrated STEM education is not restricted to implementation in science classrooms, in the United States there exists a policy mandate to K − 12 science teachers through the Framework for K − 12 Science Education (NRC, 2012) and the Next Generation Science Standard s (NGSS Lead States, 2013 ) and consequently the preponderance of integrated STEM research occurs within the context of science education (Takeuchi et al., 2020 ). Thus, in this paper we specifically focus on STEM integration within K − 12 science classrooms. It is also important to state that integrated STEM is not promoted to the exclusion of other important learning goals within a K − 12 science classroom. Plainly stated, not all science content can and should be taught using an integrated STEM approach; attention should also be paid to the nature of science and engaging students in learning science concepts through inquiry-based learning.

While the field has moved towards increased agreement on definitions and broad characteristics of integrated STEM education, there remains a lack of specification in how these characteristics should be operationalized within curricula and classrooms. Educators and curriculum developers need specifics if the implementation of integrated STEM education is to meet the policy goals of using interdisciplinary and integrated approaches to teaching STEM content to increase students’ interest and readiness for STEM careers (e.g., National Academy of Science, National Academy of Engineering, and Institute of Medicine, 2007; President’s Council of Advisors on Science and Technology [PCAST], 2011). Without clear guidelines, implementation of integrated STEM education comprises a broad range of approaches (Moore et al., 2020 ), many of which, as discussed below, are problematic (e.g., Gunckel & Tolbert, 2018 ; McComas & Burgin, 2020 ). There is a clear need for research to provide critical evidence of the impact of integrated STEM education on student learning and affect toward STEM, as many arguments for integrated STEM are argued from policy and theoretical positions (e.g., NAE and NRC, 2014). The development of valid assessments and protocols to research integrated STEM teaching and learning requires that characteristics of integrated STEM education are developed in explicit detail. Thus, this paper develops a detailed framework for integrated STEM education that expands on previously established components of quality integrated STEM as broad statements to detailed constructs that describe fully what quality integrated STEM implementation should look like in the classroom. First, we examine the policy environment in which integrated STEM education is being promoted. Second, we provide an extensive literature review which expands on the consensus aspects of integrated STEM education described above to provide a more nuanced and detailed discussion of key characteristics of integrated STEM.

STEM policy

It is important to understand the policy context in which integrated STEM education is being promoted, as the myriad approaches are in response to policy directives, originating within the US, that call for addressing pressing issues such as STEM workforce needs (Takeuchi et al., 2020 ). Indeed, dominating policy arguments is the suggestion that continued national prosperity is dependent on meeting STEM workforce needs to address critical challenges such as energy, health, the environment, national security, and global development (e.g., National Academy of Science, National Academy of Engineering, and Institute of Medicine, 2007; PCAST, 2011). The number of STEM jobs is growing faster than non-STEM jobs (U.S. Bureau of Labor Statistics, 2020 ), which may result in a shortage of up to 3.5 million STEM workers in the United States by 2025 (National Association of Manufacturing and Deloitte Report, 2018 ). STEM workforce arguments are used in countries throughout the world to establish new STEM education policies and initiatives (Freeman et al., 2014 ). However, policy documents do not unpack specifics about STEM workforce needs beyond shortages of STEM workers. For integrated STEM education to address policy calls related to the STEM workforce, it is necessary to better understand the knowledge and skills that students need to be successful as STEM professionals.

More specific to the needs of the STEM workforce are concerns about a “creativity crisis” in the United States and around the world (Bronson & Merryman, 2011 ; Kim, 2011 ; Lin, 2011 ). STEM employers are looking for a workforce with not only strong STEM content knowledge and skills, but also an ability to compete in the global economy in a workforce with strong twenty-first century skills (e.g., critical thinking, communication, collaboration, and creativity) (Bronson & Merryman, 2011 ; Charyton, 2015 ). According to a World Economic Forum survey, approximately 65% of today’s Kindergarteners will end up working in jobs that do not currently exist given the rapid growth of automation and artificial intelligence in the workplace (World Economic Forum, 2016 ). Thus, it is no longer enough to expect our students to simply learn isolated facts and content. Rather than positioning students as consumers of information, students should be involved in knowledge construction. The deep understanding of content developed through knowledge construction forms the basis for students to apply twenty-first century skills to create, analyze, evaluate, innovate, and address real-world problems (Stehle & Peters-Burton, 2019 ).

Less visible in the current STEM policy rhetoric are arguments that integrated STEM education should promote increased STEM literacy and awareness, as well as addressing issues in developing countries related to equitable education and poverty reduction (Freeman et al., 2014 ; National Academy of Sciences [NAS], 2014). Indeed, teaching STEM solely from a workforce rationale is viewed by some science educators as problematic (e.g., Hoeg & Bencze, 2017 ; Zeidler, 2016 ; Zeidler et al., 2016 ). For example, Gunckel and Tolbert ( 2018 ) call out the technocratic, utilitarian, and neoliberal underpinnings of engineering design as portrayed in the Framework (NRC, 2012). These critiques are carefully considered and integrated in our development of an understanding of integrated STEM education to guide both educators and researchers seeking to better understand integrated STEM and ensure a positive learning experience for all students.

Integrated STEM framework

Throughout this literature review, we propose a framework for K − 12 integrated STEM education that provides essential details for consistent implementation and evaluation of integrated STEM teaching. Without common understandings of integrated STEM education, it is difficult at best to draw conclusions across studies about teacher practices related to integrated STEM instruction and student outcomes. This common understanding needs to move past definitions and lists of consensus features of integrated STEM that can be interpreted in myriad ways by educators. Our framework includes seven key characteristics of integrated STEM: (a) focus on real-world problems, (b) centrality of engineering, (c) context integration, (d) content integration, (e) STEM practices, (f) twenty-first century skills, and (g) informing students about STEM careers. Table 1 provides a summary of these characteristics, and a detailed literature review for each characteristic follows this overview of the framework. These key characteristics are aligned with and expand upon three of the four consensus features of integrated STEM identified in the preceding sections: (a) integrated STEM is contextualized by a real-world problem, (b) integrated STEM supports the development of twenty-first century skills, and (c) connections between STEM disciplines should be made explicit to students. We note agreement within our framework that integrated STEM requires the use of student-centered pedagogies; however, we focus on student engagement in STEM practices rather than broad notions of student-centered pedagogies. Our framework extends conceptualizations of integrated STEM to explicitly address the nature of integration, the role of engineering, and STEM career awareness. Finally, our framework directly attends to issues of diversity and equity as opposed to the techno-centric focus of prevalent conceptualizations of integrated STEM. It is important to note that none of the characteristics in Table 1 operate in isolation from each other (see Fig. 1 ). The following section grounds each characteristic in the literature and illustrates the connections amongst the characteristics.

Interactions between critical characteristics of integrated STEM

Focus on real-world problems

If learning is not centered on developing solutions to a real-world problem (Characteristic 1), a lesson cannot be considered to be representative of integrated STEM education. Indeed, as noted earlier, the most common feature included in definitions of integrated STEM in the literature is that STEM integration should be centered around a real-world problem or context (e.g., Kelley & Knowles, 2016 ; Kloser et al., 2018 ; Moore et al., 2020 ). Indeed, many students find it difficult to relate to STEM content presented using traditional, disciplinary approaches (Kelley & Knowles, 2016 ). Proponents of integrated STEM education argue that using real-world or authentic problems as a context for learning provides motivation and purpose for learning STEM content (e.g., Kelley & Knowles, 2016 ; Monson & Besser, 2015 ). Research shows that engaging students in learning through authentic engineering design problems improves student interest in science and engineering (Guzey, Moore, & Morse, 2016 ; Lachapelle & Cunningham, 2014 ; McClure et al., 2021 ). However, the selection of a real-world problem requires careful consideration as the ability to engage students with all characteristics of integrated STEM education hinges on the nature of the real-world problem (Fig. 1 ).

Our framework expands consideration of the importance of the nature of these real-world problems as care needs to be taken that these authentic problems generate interest and motivation in learning for all students (Carter et al., 2015 ; Monson & Besser, 2015 ). Given the lack of diversity within many of the STEM fields (Vakil & Ayers, 2019 ), there is a need to increase STEM interest for students that are historically under-represented in STEM. It is important to engage students in real-world problems that are personally motivating and connect STEM content to students’ lived experiences. This has been shown to make learning more meaningful and relevant, which enhances student engagement in science (Djonko-Moore et al., 2018 ) and positions students as epistemic agents in their learning (Miller et al., 2018 ). Often, integrated STEM classroom activities tend to focus on the male-oriented, technical aspects of engineering related to the design of “things”, such as designing cars and rockets (Gunckel & Tolbert, 2018 ). However, research shows that girls and students of color are more motivated by projects with a communal goal orientation, focused on societal issues such as health, the environment, and social justice as opposed to these types of gendered engineering projects (Billington et al., 2013 ; Diekman et al., 2010 ; Leammukda & Roehrig, 2020 ). The emphasis on “things” and technical criteria is oppositional to a communal goal orientation which negatively impacts interest in STEM careers (Diekman et al., 2010 ). This line of research parallels the arguments of Gunckel and Tolbert ( 2018 ), who argue for considerations of the dimensions of care and empathy in integrated STEM. While the literature has demonstrated a clear consensus that integrated STEM education should include an authentic problem to contextualize learning (e.g., Kelley & Knowles, 2016 ; Moore, Stohlmann, et al., 2014), there are important considerations about the nature of such problems if content learning and student motivation are to be promoted as argued in policy documents (e.g., Australian Curriculum, Assessment, and Reporting Authority, 2016 ; European Commission, 2015 ; NRC, 2012 ). Drawing on personal and community interests and lived experiences of students will be more motivating for students, and with purposeful consideration of students’ interests there is the potential to diversify STEM fields.

Centrality of engineering

Given the prominence of engineering within STEM policy documents (e.g., NRC, 2012 ), real-world problems are represented as an engineering design challenge (Characteristic 2) (Moore et al., 2020 ). Engineering is considered central in most definitions of integrated STEM (e.g., Berland & Steingut, 2016 ; Mehalik et al., 2008 ; Moore, Stohlmann, et al., 2014; Nathan et al., 2013 ); even within research that calls for the integration of only two disciplines to be considered integrated STEM, the most common combination is science and engineering (Moore et al., 2020 ). Thus, our framework links real-world problems to engineering design challenges (Characteristics 1 and 2 in Fig. 1 ) to promote the practices called for within current reform documents (e.g., NRC 2012 ).

Developing solutions to an overarching real-world problem relies on using and developing understanding of content from multiple disciplines (e.g., Cavlazoglu & Stuessy, 2017 ; Thibaut et al., 2018 ; Walker et al., 2018 ). Specifically, within integrated STEM education, students are expected to engage in engineering practices to develop possible design solutions to real-world problems (Berland & Steingut, 2016 ; NAE and NRC, 2014 ; NRC, 2012 ). Engineering practices are loosely defined within the NGSS through the eight science and engineering practices; however, successful integration of engineering practices into science classrooms requires a more robust articulation of engineering practices (Cunningham & Carlsen, 2014 ; Moore, Glancy, et al., 2014). In our work, we draw heavily on the Framework for Quality K − 12 Engineering Education (Moore, Glancy, et al., 2014), which proposes three domains consisting of 12 key indicators of quality K-12 engineering (see Table 2 ).

Engineering is a systematic and iterative approach to designing solutions (products, processes, and systems) based on the needs of a client (NRC, 2012 ). As such, design is widely considered to be the central activity of engineering (Dym, 1999 ). Engineering design is an iterative process of “testing the most promising solutions and modifying what is proposed on the basis of the test results leads to greater refinement and ultimately to an optimal solution” (NRC, 2012 , p. 210). In other words, response to failure is central to the engineering design process; failure is expected if innovation is to occur as it can lead to stronger, more innovative designs (Henry et al., 2021 ; Simpson et al., 2018 ). Thus, it is critical that K-12 students have opportunities within integrated STEM curriculum to fully engage in the iterative engineering design process and engage in at least one cycle of evaluating and redesigning a proposed solution or set of solutions (Moore, Stohlmann, et al., 2014). Learning from failure needs to be explicitly scaffolded for students, purposefully engaging them in a reflective decision-making process (Wendell et al., 2017 ).

Unfortunately, in K-12 classrooms engineering design is usually depicted solely as a technical problem (Gunckel & Tolbert, 2018 ). Thus, our framework expands on the Framework for Quality K-12 Engineering Education (Moore, Glancy, et al., 2014) to extend its focus on the technical aspects of engineering design to explicitly consider diversity and equity within STEM. Parallel to the work of professional engineers, students are expected to understand and address the criteria and constraints of a problem in developing possible design solutions (Watkins et al., 2014). Yet, these constraints are usually limited to realistic, but surface-level, issues such as time, access to materials, and budget, often ignoring the social, political, and ethical issues that are inherent in most real-world problems (Gunckel & Tolbert, 2018 ; Roehrig et al., 2020 ). Indeed, some researchers argue the NGSS (NGSS Lead States, 2013 ) and the Framework (NRC, 2012 ) marginalize the moral and ethical considerations within engineering design (e.g., Kahn, 2015 ). Gunckel and Tolbert ( 2018 ) caution that, while engineering education has elevated a focus on ethics, the focus of this approach still draws on technocratic and utilitarian principles. An approach grounded in care and empathy is necessary to reframe engineering education to engage students in considering the societal implications of their design solutions (Gunckel & Tolbert, 2018 ; Jackson et al., 2021 ). Similarly, researchers have promoted the inclusion of socio-scientific issues (SSI) into integrated STEM instruction (Kahn, 2015 ; Owens & Sadler, 2020 ; Roehrig et al., 2020 ). In addition to promoting scientific solutions to a real-world problem, SSI explicitly address moral and ethical considerations (Kahn, 2015 ; Zeidler, 2016 ). This approach to integrated STEM education not only elevates the purpose to include STEM literacy for all citizens regardless of their future participation in a STEM career, but also reimagines the necessary skills needed in the STEM workforce to improve and diversify thinking and approaches to engineering design.

Context integration

The real-world problem and/or engineering design challenge used to motivate student learning should be complex enough to foster multiple solutions (Lachapelle & Cunningham, 2014 ) and engage learners in applying and expanding their knowledge of the STEM disciplines (Berland & Steingut, 2016 ; Monson & Besser, 2015 ). There needs to be clear alignment between the engineering design challenge or real-world problem and specific content learning objectives (see Fig. 1 ), with the challenge or problem framed such that students need to draw upon STEM content knowledge to generate possible designs and make evidence-based decisions. This is represented in Fig. 1 as context integration (Characteristic 3).

Without clear and explicit integration between the problem context and content learning goals, students will resort to tinkering (a form of trial and error), negating the achievement of content learning objectives (McComas & Burgin, 2020 ; Moore, Glancy, et al., 2014; Roehrig et al., 2021 ). This relates to a significant problem pointed out by Takeuchi et al. ( 2020 ) in that there is a lack of a clear focus on specific STEM concepts. In their systematic review of the literature, Takeuchi et al. ( 2020 ) reported that almost 40% of the 154 integrated STEM articles they reviewed focused on students’ career aspirations and choices rather than learning of specific STEM concepts. The real-world problem and engineering design challenge must provide a context for learning target STEM content, as well as being motivating and engaging for students to help promote positive STEM identities (e.g., Tai et al., 2006 ).

Unfortunately, even with a real-world context, design tasks can degenerate into simply making crafts or tinkering solely through trial and error, neither of which require knowledge of STEM content or practices to develop solutions. While engineers develop both products and processes as solutions to real-world problems, K-12 engineering and integrated STEM educators tend to gravitate toward the building of physical products. For example, engineering courses, makerspaces, and digital fabrication labs have proliferated in K-12 schools over the past decade (Adams Becker et al., 2016 ). The focus of makerspaces and fabrication labs is the development of a product, often through “tinkering with materials with an endpoint in mind” (Sheffield et al., 2017 , p.149). In effect, these spaces are the modernized versions of vocational education or shop class (Blackley et al., 2017 ; McComas & Burgin, 2020 ). Studies demonstrate limited content learning in science and mathematics for students participating in hands-on, project-based engineering courses because of the lack of clear and explicit connections to science and mathematics content (Tank et al., 2019 ). Makerspaces, fabrication labs, and engineering programs are not commensurate with characteristics of integrated STEM education unless teachers make explicit connections to mathematics and science content (Sheffield et al., 2015). As such, integrated STEM education requires an authentic problem or engineering design challenge that engages students in explicitly learning and applying science and mathematics concepts.

The practice of engineering requires the use and application of science, mathematics, and engineering knowledge. K-12 STEM education should emphasize this interdisciplinary nature by providing students with opportunities to apply developmentally appropriate mathematics or science content within the context of solving engineering problems (Arık & Topçu, 2020 ; NRC, 2012 ; Reynante et al., 2020 ). Indeed, engineering as a discipline involves an “understanding of the science undergirding physical relationships and the mathematical foundations of models that guide engineering design, as opposed to tinkering or making random modifications without basing those changes upon mathematical and/or scientific analyses” (Householder & Hailey, 2012 , p.12). Design iterations throughout the engineering design process are based on evidence, scientific and mathematical knowledge, and analyses of the data generated through the testing of prototype designs (Mathis et al., 2016 ; Mathis et al., 2018 ).

Our argument is that integrated STEM education at its core is driven by real-world problems and the development of possible solutions to those problems using knowledge and practices from any relevant discipline. If students are to consider and understand the full socio-historical-political context of the problems in developing and evaluating design solutions to real-world problems (e.g., Gunckel & Tolbert, 2018 ), then knowledge and practices from the social sciences are necessary in addition to the technical knowledge of the STEM disciplines. In addition, critical to addressing issues of equity and diversity in STEM, is promoting students’ lived experiences and cultural knowledge, as well as disciplinary knowledge, as relevant to proposing solutions to real-world problems and engineering design challenges. Unfortunately, the cultural knowledge of students who are marginalized and under-represented in STEM are often perceived as deficit and not as legitimate ways of engaging in STEM (Tan & Calabrese Barton, 2018 ). Limited attention has been paid within the integrated STEM education literature to elevating the application of cultural and indigenous knowledge in engineering design; however, promoting STEM interest and learning for all students needs to attend to approaches such as cultural maker education (Tan & Calabrese Barton, 2018 ) and ethno-engineering (Friesen & Herrmann, 2018 ; Kilada et al., 2021 ).

Content integration

In addition to explicit connections between the real-world problem/engineering design challenge and the targeted science and/or mathematics content (Characteristic 3 - contextual integration), it is important that connections between the disciplines (Characteristic 4 - content integration) are also made explicit to students (English, 2016 ; Kelley & Knowles, 2016 ; NAE and NRC, 2014 ). Although teachers may understand the connections across the range of content representations and activities within an integrated STEM lesson, students often struggle to make these connections on their own (Dare et al., 2018 ; Tran & Nathan, 2010 ). Since students seldom make these connections spontaneously (Tran & Nathan, 2010 ), teachers must either help students recognize and identify these connections or explicitly make these connections clear for students. In a study of a high school engineering classroom, Nathan et al. ( 2013 ) discuss productive pedagogical moves to help make these interdisciplinary connections explicit to students. Their suggestions include asking questions, facilitating problem solving, creating models and representations, and explicitly foregrounding disciplinary knowledge to help students to identify the presence of specific content.

Content integration can be achieved through multidisciplinary, interdisciplinary, or transdisciplinary approaches (Bybee, 2013 ; Moore & Smith, 2014 ; Vasquez et al., 2013 ). Some researchers argue that one approach is not superior to another (Rennie et al., 2012 ), whereas others define a continuum of increasing integration from disciplinary to transdisciplinary (e.g., Vasquez et al., 2013 ; Wang & Knoblach, 2018 ). Proponents of an interdisciplinary approach argue that this approach is superior because a theme or real-world problem anchors the learning (e.g., Vasquez et al., 2013 ) in contrast to multidisciplinary approaches that “begin and end with the subject-based content and skills [with] students expected to connect the content and skills in different subjects that had been taught in different classrooms” (Wang et al., 2011 , p.2).

While many researchers define multidisciplinary integration as occurring across multiple classrooms (e.g., Vasquez et al., 2013 ), the calls to integrate engineering and mathematical thinking in science classrooms (e.g., NRC, 2012 ) require integration across the disciplines within a science lesson or unit of instruction (Capobianco & Rupp, 2014 ; Moore, Stohlmann, et al., 2014). In a multidisciplinary approach, each STEM discipline would be identifiable within the curriculum and instruction, whereas in an interdisciplinary approach, each discipline would be difficult to distinguish from one another (Lederman & Niess, 1997 ). Given the argument that integrated STEM education can improve students’ learning of science and mathematics concepts (e.g., Berland & Steingut, 2016 ; Fan & Yu, 2017 ; Guzey et al., 2017 ) and the difficulty faced by students in recognizing the way in which different content areas support and complement each other (English, 2016 ; NAE and NRC, 2014 ), the connections between content areas need to be made explicit for students (English, 2016 ; Kelley & Knowles, 2016 ). As stated in the NAE and NRC ( 2014 ) report:

Connecting ideas across disciplines is challenging when students have little or no understanding of the relevant ideas in the individual disciplines. Also, students do not always or naturally use their disciplinary knowledge in integrated contexts. Students will thus need support to elicit the relevant scientific or mathematical ideas in an engineering or technological design context, to connect those ideas productively, and to reorganize their own ideas in ways that come to reflect normative, scientific ideas and practices. (p. 5)

While not discounting transdisciplinary and interdisciplinary approaches to integrated STEM education, multidisciplinary approaches yield the best approach for students to learn and apply disciplinary content and develop an understanding of the ways in which disciplinary content is connected.

Given the positioning of engineering within national and state science standards, mathematics and technology have received little attention in the literature and their inclusion within integrated STEM curriculum is often limited (Roehrig et al., 2021 ) (e.g., Roehrig et al., 2021 )). Thus, it is critical that more explicit attention is given to mathematics and technology in the development of more robust and detailed models of integrated STEM education.

The case of mathematics

Despite a long history of integration between science and mathematics (e.g., Berlin & White, 1995 ; Davison et al., 1995 ; Huntley, 1998 ), the integration of mathematics is particularly difficult within integrated STEM education (Walker, 2017 ; Zhang et al., 2015 ), and studies show only small impacts on students’ mathematical knowledge (e.g., Becker & Park, 2011 ; NAE and NRC, 2014 ; Nugent et al., 2015 ). For example, Huntley ( 1998 ) describes the interdisciplinary approach as having one discipline that is in the foreground with the second discipline in the background simply to provide context. However, most often in science (and more recently in integrated STEM lessons), mathematics is backgrounded as a tool for data measurement and analysis with few or no conceptual learning goals for mathematics (e.g., Baldinger et al., 2021 ; Ring et al., 2017 ; Roehrig et al., 2021 ; Walker, 2017 ). This treatment of mathematics is reinforced by the NGSS through the inclusion of mathematics and computational thinking as one of the eight science and engineering practices (NRC, 2012 ). This practice presents mathematics as a tool that is central to science and engineering (Hoda, Wilkerson, & Fenwick, 2017 ) including “tasks ranging from constructing simulations, to making quantitative predictions, to statistically analyzing data, to recognizing, expressing, and applying quantitative relationships” (Aminger et al., 2021 , p. 190).

While it is difficult to imagine teaching and learning science or engineering without engaging in mathematical practices, the mathematical connections are most often implicit and may not be transparent to students (Roehrig et al., 2021 ). Successful mathematics integration requires that the role of mathematics be made explicit, such as through putting mathematics in the foreground (Silk et al., 2010 ). For example, in a meta-analysis, Hurley ( 2001 ) found the greatest effect sizes for mathematics learning occurred when students learned science and mathematics content in sequence through a multi-disciplinary approach, rather than interdisciplinary approaches. More recently, Baldinger et al. ( 2021 ) argued that science and mathematics learning opportunities need to be strategically positioned and highlighted across a unit. Indeed, as noted previously, conceptual learning of science and mathematics is improved through a multidisciplinary approach that allows mathematics and science concepts to be explicitly and purposefully foregrounded within a unit.

In a rare study of the implementation of mathematical and computational thinking in K-12 science classrooms, Aminger et al. ( 2021 ) found that teachers were able to improve students’ understanding of scientific phenomena only when engaged in high cognitive demand mathematical tasks, such as mathematical modeling. Modeling uses mathematical equations to represent scientific phenomena and communicate scientific ideas (e.g., Bialek & Botstein, 2004 ; Brush, 2015 ; Lazenby & Becker, 2019 ). While students are expected to interpret the mathematical and scientific meaning represented by an equation (e.g., Bialek & Botstein, 2004 ; Sevian & Talanquer, 2014 ), studies at the postsecondary level show that students rely on algorithmic procedures without making connections between the mathematical equation and the scientific phenomenon (e.g., Bing & Redish, 2009 ). Postsecondary researchers advocate for blended sensemaking, where students’ scientific and mathematical knowledge is activated and used to develop understanding of scientific phenomena (Zhao & Schuchardt, 2021 ). When instruction encourages engagement in mathematical modeling through blended sensemaking, students show improved quantitative problem solving (e.g., Becker, Rupp, & Brandriet, 2017 ; Lazenby & Becker, 2019 ; Schuchardt & Schunn, 2016 ).

The case of technology

Technology is rarely explicitly called out within definitions of integrated STEM education (e.g., Ellis et al., 2020 ; Herschbach, 2011 ). Implicit treatments of technology take two primary forms: the integration of educational technology and technology as the production and use of technology within engineering (Ellis et al., 2020 ; Kelley & Knowles, 2016 ). Unquestionably, educational technology plays an increasingly large role in K-12 classrooms and, as is the case for all teachers, science teachers are involved in using digital technology tools to present content and allow students to complete their work, often through one-to-one technology initiatives. Standards guiding the use of technology in K-12 classrooms, such as the International Society for Technology in Education (ISTE) Standards for Educators, which define the technological skills educators need (ISTE, 2000), are content- and grade-level agnostic (Ellis et al., 2020 ). Most often, these digital technologies are used as replacements to traditional paper and text learning. For example, in science classrooms, digital notebooks have been used instead of paper notebooks (Constantine & Jung, 2019 ). While this allows students to include multimedia such as photos and videos and work collaboratively through web-based tools, these uses of technology are not specific to STEM.

Given the focus on engineering within the NGSS , views of technology within integrated STEM education are often connected to how technology is portrayed within engineering curriculum. In a review of K-12 engineering curricula, technology was primarily represented as the product of engineering (NRC, 2009 ). This representation of technology within integrated STEM education is clearly stated within the NGSS where engineering is defined as “a systematic practice for solving problems, and technology as the result of that practice” (NRC, 2012 , p. 103). Similarly, the Framework states that “technologies result when engineers apply their understanding of the natural world and of human behavior to design ways to satisfy human needs and wants” (NRC, 2012 , p. 12). In essence, under this definition of the “T” in STEM, STEM becomes SEM, resulting in technology being subsumed by engineering.

More productive in defining technology specific to integrated STEM education is the view of the “T” in STEM defined as the tools used by practitioners of science, mathematics, and engineering (Ellis et al., 2020 ; NAE and NRC, 2014 ). To support student engagement in the authentic practices of STEM professionals, students should have opportunities to use STEM-specific tools or technologies (e.g., Bell & Bull, 2008 ; Ellis et al., 2020 ; McCrory, 2008 ). A common example in science classrooms is the use of digital probes to collect and analyze data (e.g., Hechter & Vermette, 2014 ). More recently, with the addition of engineering into science classrooms, new technologies such as computer-assisted design (CAD) software and 3-D printers are being introduced (e.g., Wieselmann et al., 2019 ). Critical to integrated STEM education, however, is that these tools should not be limited to data collection devices; rather, they should encourage deeper student engagement with science content (Bull & Bell, 2008 ). Moving beyond basic data practices, technology practices in STEM education can be elevated to incorporate simulation and modeling practices which have been shown to improve students’ conceptual science understanding (Aminger et al., 2021 ).

Summary of content integration

Given the need for disciplinary knowledge to be activated and applied in integrated STEM lessons, there is a strong argument for a multidisciplinary approach where students have opportunities to both learn the content and connect that content to an authentic problem. Implicit connections are not enough; observations of instruction should yield clear and explicit discussion orchestrated by the teacher to facilitate students’ understanding of the connections across the disciplines. The inter-relationships among the disciplines are complex and require teaching STEM content in deliberate and purposeful ways so that students understand how STEM content is conceptually linked. In the case of mathematics and technology, it is critical that these subjects are not limited to tools in the service of data collection and analysis. When appropriate, curriculum developers and teachers should engage students in higher cognitive demand practices and explicit sensemaking through mathematical and technology-assisted modeling. While the literature related to modeling in physics is more robust (e.g., Hestenes, 2010 ), modeling literature also exists in other scientific disciplines that can be used to guide higher quality mathematics integration (e.g., Lazenby & Becker, 2019 ; Schuchardt & Schunn, 2016 ; Zhao & Schuchardt, 2021 ). Engagement in these data and mathematical practices, as practiced by STEM professionals, is a STEM-specific approach to technology integration.

Integration through STEM practices and twenty-first century skills

Also common across definitions of integrated STEM are references to specific disciplinary practices (e.g., inquiry, engineering design), as well as to shared practices and skills (e.g., critical thinking, creativity) (Moore et al., 2020 ). In addressing real-world problems and engineering design challenges, students should engage directly in authentic STEM practices (Characteristic 5) and twenty-first century skills (Characteristic 6) to develop potential solutions (Fig. 1 ) (e.g., Kelley & Knowles, 2016 ; Moore, Stohlmann, et al., 2014). The nature of the engineering design challenge is critical in promoting the desired learning outcomes and should be structured with multiple possible solution pathways. For example, if the task is too constrained, then the design space becomes limited, and students will not have the opportunity to develop important twenty-first century skills, such as critical thinking and creativity.

STEM practices

Engaging students in STEM practices is a common component of definitions of integrated STEM education (e.g., Kelley & Knowles, 2016 ; Moore et al., 2020 ). These practices are “a representation of what practitioners do as they engage in their work and they are a necessary part of what students must do to learn a subject and understand the nature of the field” (Reynante et al., 2020 , p.3). Engaging students in STEM practices is supported broadly by pragmatism, which emphasizes learning by doing (Asunda, 2014 ), and more specifically by social constructivist learning theories that underpin reforms in STEM education that advocate for students’ active construction of knowledge as opposed to transmission of knowledge (e.g., Guzey, Moore, & Harwell, 2016 ; Riskowski et al., 2009 ).

Central to knowledge construction and the work of STEM professionals are data practices (Duschl et al., 2007 ). Data practices include the creation, collection, manipulation, analysis, and visualization of data (Weintrop et al., 2016 ). Given that engineering design challenges afford multiple solution pathways without a single correct solution (Lachapelle & Cunningham, 2014 ) and “data do not come with inherent structure that leads directly to an answer” (Weintrop et al., 2016 , p. 135), it is important that students are actively engaged in data practices and using data to make decisions as they engage in the engineering design process. Within the Framework (NRC, 2012 ), this is called out as the practice of engaging in argument from evidence , which features the use of evidence and scientific and mathematical knowledge to develop explanations in science and justify design decisions in engineering.

Argumentation is a common practice within both science and engineering fields (Couso & Simarro, 2020 ); however, while scientific argumentation is well-supported within the research literature (e.g., Berland & McNeill, 2010 ), the level to which K-12 students use both evidence and STEM content to justify design decisions is in its infancy (e.g., Mathis et al., 2018 ; Purzer et al., 2015 ; Valtorta & Berland, 2015 ). Argumentation and decision-making require considering the advantages and disadvantages of possible design solutions in light of available evidence and any defined criteria and constraints (Wendell et al., 2017 ).

Siverling et al. ( 2017 ) argue that students’ application of scientific and mathematical content is promoted through the explicit use of evidence-based reasoning within integrated STEM lessons. For example, the classroom activities may require students to justify their thinking about why an initial design solution should be pursued during the planning phase and additionally require students to use evidence and STEM content when evaluating a tested design solution and justifying it to the client (Mathis et al., 2016 ; Mathis et al., 2018 ). This formal evidence-based reasoning explicitly asks students to make claims about their designs and design decisions that are supported by both evidence (from iterative testing) and reasoning (using scientific and mathematical content) (Siverling et al., 2019 ). Students do not spontaneously use science and mathematics content to justify and explain their design choices; rather, students focus on cost and material limitations when engaging in engineering design tasks (e.g., English et al., 2013 ; Guzey & Aranda, 2017 ). Thus, explicit inclusion of evidence-based reasoning in K-12 integrated STEM lessons is necessary to scaffold students in connecting science and mathematics content to the engineering design challenge.

STEM content knowledge is not the only consideration in making design decisions. In evaluating a possible design solution, students are expected to prioritize “criteria and trade-offs that account for a range of constraints, including cost, safety, reliability, and aesthetics as well as possible social, cultural, and environmental impacts” (NGSS standard HS-ETS1–3). It is important that the social and cultural aspects of proposed solutions are not ignored, as we truly intend to develop a STEM literate citizenry and develop a future workforce who think more deeply about their work beyond the traditional technocratic focus (Gunckel & Tolbert, 2018 ; Roehrig et al., 2020 ; Zeidler, 2016 ).

Students should have agency in design decisions as they engage in the engineering design process (e.g., Berland & Steingut, 2016 ; Johnson et al., 2016 ; Saito et al., 2015 ). Engineering design challenges should be constructed with multiple solution pathways, allowing students to determine their own solution trajectories and opportunities to build knowledge as possible design solutions develop from students’ questions, ideas, and explorations. Miller et al. ( 2018 ) argue that we must also position students as epistemic agents as opposed to receivers of STEM content, without which the call from the Framework (NRC, 2012 ) for students to engage in STEM practices will not be realized. Miller et al. ( 2018 ) define epistemic agency as “students being positioned with, perceiving, and acting on, opportunities to shape the knowledge building work in their classroom community” (p. 1058). Specifically, students should have opportunities to: (a) build on personal and cultural knowledge as a resource for learning, (b) build knowledge, (c) build a knowledge product that is personally useful, and (d) change structures that constrain and support action. When afforded epistemic agency, students can propose solutions to personally meaningful problems, rather than simply learning the canonical facts of the discipline (Schwarz et al., 2017) and mimicking the proscribed practices. Engaging students in engineering design challenges contextualizes learning around meaningful and authentic problems, providing a sense of agency as students can see the content learning goals as useful and relevant to developing solutions to the problem (e.g., Schwarz et al., 2017). Researchers argue that real-world problems should position students as not only knowledge builders, but also change agents in their community, further promoting epistemic agency and the development of STEM identity (Billington et al., 2013 ; Leammukda & Roehrig, 2020 ; Miller et al., 2018 ).

• Twenty-first century skills

In addition to specific STEM practices, integrated STEM instruction should support the development of twenty-first century skills (e.g., Moore, Glancy, et al., 2014; Sias et al., 2017 ). Broadly, twenty-first century skills include knowledge construction, real-world problem solving, skilled communication, collaboration, use of information and communication technology for learning, creativity, and collaboration (Partnership for twenty-first Century Learning, 2016 ); these are the skills “necessary for a person to adapt and thrive in an ever-changing world” (Stehle & Peters-Burton, 2019 , p.2). A recent trend has been to include the arts, as proponents of STEAM education argue that the integration of the arts will enhance students’ critical thinking and problem-solving skills and cultivate their creativity (Trevallion & Trevallion, 2020 ). However, these arguments are already central to agreed-upon goals of integrated STEM education (NAE and NRC, 2014 ; Moore, Glancy, et al., 2014), and creativity is pivotal within the STEM disciplines without the insertion of the arts. Integrated STEM education provides a rich environment for the development of critical thinking, collaboration, creativity, and communication (Stehle & Peters-Burton, 2019 ).

The ill-defined nature of real-world problems and engineering design challenges requires that students engage in critical thinking, drawing on their STEM content knowledge and lived experiences to propose possible design solutions. Engaging in the engineering design process inherently incorporates creativity and critical thinking as there is no single correct solution, thus promoting the potential of transformative and innovative design solutions (Stretch & Roehrig, 2021 ; Petroski, 2016 ; Simpson et al., 2018 ). As students iteratively test and improve their design solutions, they will experience design failure. As previously noted, failure should be expected if innovation is to occur, and the ability to learn from failure can lead to stronger designs and innovation through the application of creativity and critical thinking (Henry et al., 2021 ; Simpson et al., 2018 ).

Given the highly interdisciplinary and integrative nature of engineering, students should also be provided opportunities to work together in teams to enhance their collaboration skills (Riel et al., 2012; Rinke et al., 2016 ; Thibaut et al., 2018 ), which are necessary to develop negotiated design solutions that synthesize across differing understandings of the same problem space (Wendell et al., 2017 ). Indeed, in the K-12 classroom, small group activities account for approximately half of instructional time in science classrooms with the expectation that small groups co-construct knowledge of STEM content and design solutions to real-world problems (Wieselmann et al., 2020 ; Wendell et al., 2017 ). Sharunova et al. ( 2020 ) used Bloom’s taxonomy (Anderson & Krathwohl, 2005 ) to define a continuum of cognitive engagement that groups engage in during small group engineering design activities. Integrated STEM learning environments involve “new levels of communication, shared vision, collective intelligence, and direct coherent action by students” (Asunda, 2014 , p. 8). Further, researchers call for integrated STEM activities wherein students are expected to collectively apply what they have learned to develop possible design solutions and improve these designs through iterative analysis and evaluation (Asunda et al., 2015; Dolog et al., 2016 ; Sharunova et al., 2020 ).

Promoting STEM careers

The final characteristic, promoting STEM careers (Characteristic 7), is the least common feature of integrated STEM within the literature. As such, it stands somewhat separate from the other characteristics of the integrated STEM framework but undergirds the policy motivation for including integrated STEM education in K-12 classrooms. With the goal of promoting future participation in STEM careers in mind, integrated STEM education should expose students to details about STEM careers (Jahn & Myers, 2014 ; Luo et al., 2021 ). This should include both allowing students to engage in the authentic work of STEM professionals (Kitchen et al., 2018 ; Ryu et al., 2018 ) and critically promoting student development of STEM identities. A growing body of research has shown that STEM interest, attitude, and identity serve as predictors of sustained pursuit in the STEM disciplines rather than academic performance in STEM coursework (Avraamidou, 2020 ; Rodriguez et al., 2017 ; Tai et al., 2006 ). Furthermore, identity research has shown that students who show interest and enjoyment in STEM do not necessarily see themselves pursuing a future STEM career (Carlone et al., 2011 ); this is especially true for students from historically underrepresented groups of people who are less likely to show interest in and identify with the STEM domains (Rodriguez et al., 2017 ). Further, STEM interests and career aspirations are largely developed by eighth grade (Tai et al., 2006 ), suggesting a need to introduce students to STEM careers early in their education. In addition to introducing students to STEM careers, research shows that a focus on connections to personal experience and knowledge can help shape students’ identity within STEM (Ryu et al., 2018 ; Carlone et al., 2014 ; Sias et al., 2017 ).

Although supporting students in developing solutions to real-world problems through engaging in STEM practices and twenty-first century skills may also help to develop positive STEM identities and interest in STEM, these activities do not require any explicit connection to STEM careers. Research exploring the development of students’ understanding of engineering is limited and debate remains about whether implicit modeling of STEM professions by engaging students in hands-on STEM activities leads to durable and robust understandings about the work of engineers and other STEM professionals (e.g., Svihla et al., 2017 ). However, explicit discussion of STEM professions can help students to understand specific career opportunities and align these professions with their interests (Kitchen et al., 2018 ; Ryu et al., 2018 ).

Implications and use of the framework

Each of the seven critical characteristics of integrated STEM education (Table 1 ) has important implications for teachers in their planning and implementation of integrated STEM if integrated STEM in K-12 classrooms is going to be successful in promoting STEM literacy and increasing diversity in the STEM fields. Careful consideration is critical in selecting the context for an integrated STEM lesson, as research shows differences in motivation to engage in STEM for students of color and women who are under-represented in STEM as compared to White males (e.g., Billington et al., 2013 ; Diekman et al., 2010 ; Leammukda & Roehrig, 2020 ). While some science topics lend themselves to simple engineering design activities, such as designing a mousetrap car to travel as far as possible, these activities are not contextualized in a real-world problem. In contrast, students could be asked to design habitats to protect equatorial penguins impacted by climate change, a problem that requires knowledge and application of the scientific concepts of heat transfer (Sheerer & Schnittka, 2012). This engineering design challenge is contextualized by a real-world problem created through human impact on the environment and could easily be adapted to include considerations of human-caused environmental issues and local policies and traditions in developing design solutions. By contextualizing an engineering design challenge in a real-world problem, we ask students not only to understand the technical criteria and constraints of a problem but also to consider the problem within the context of a potentially difficult moral and ethical dilemma. Teachers should seize such opportunities to guide students in sense-making, understanding the authenticity of the context, and approach these problems with a critical perspective. Attention to selecting real-world problems and related engineering design challenges that promote positive STEM identities for students that are under-represented in STEM not only addresses reported workforce needs but brings new perspectives and approaches to how STEM content and practices are applied in the real-world.

Unfortunately, even with a real-world context, engineering design tasks can degenerate into tinkering and iterative improvement of designs through random trial and error (McComas & Burgin, 2020 ; Moore, Glancy, et al., 2014; Roehrig et al., 2021 ) if these integrated STEM lessons are poorly planned. As well as providing a motivating context designed to promote positive STEM identities, the real-world problem and engineering design challenge must provide a context for learning specified STEM content. This could involve the reactivation of prior knowledge or the explicit teaching of STEM content within a unit of instruction. We suggest that a pedagogical approach closer to multidisciplinary integration might better afford students’ recognition of the STEM content inherent within an integrated STEM unit. In other words, quality integrated STEM units (e.g., Bhattacharya et al., 2015 ; Karahan et al., 2014 ; Moore, Guzey, et al., 2014; Moore et al., 2015 ) should include lessons designed to explicitly teach relevant STEM content. Given that students rarely make these connections spontaneously (Tran & Nathan, 2010 ), it is critical that teachers use specific pedagogical approaches, such as evidence-based reasoning (Mathis et al., 2016 ; Mathis et al., 2018 ), to help make these connections explicit. Strong teacher facilitation and questioning is needed to help students recognize the connections across the disciplines and use these connections to develop stronger design solutions through iterative and reflective processes.

Our integrated STEM framework helps to not only provide more specific guidance to educators, but also support for integrated STEM research. Despite the push for integrated STEM in K-12 classrooms, the development of observation protocols that assess STEM-integrated teaching has been slow. Until valid protocols are developed, STEM education researchers continue to rely on existing instruments that predate current STEM education initiatives, such as the Reformed Teaching Observation Protocol (Sawada et al., 2002 ). The lack of a detailed integrated STEM framework thus far has prevented the field from systematically collecting data in classrooms to understand the nature and quality of integrated STEM instruction; this delays research related to the impact on student outcomes, including academic achievement and affect. This framework provides detailed guidance on teacher practices one would expect to observe within an integrated STEM lesson. With this framework, the groundwork is now set for researchers to explore the impact of specific aspects of integrated STEM or the overall quality of integrated STEM instruction on student outcomes as this framework could guide the development of observational protocols for integrated STEM which are currently lacking in the field (e.g., Dare et al., 2021 ).

Conclusions

Our framework addresses a critical need in the field to move beyond simple definitions of integrated STEM to detailed descriptions that operationalize central constructs such as the nature of integration itself. Based on intentions of STEM policy documents and the extant literature, we proposed an integrated STEM framework that includes seven key characteristics of integrated STEM: (a) focus on real-world problems, (b) centrality of engineering, (c) context integration, (d) content integration, (e) STEM practices, (f) twenty-first century skills, and (g) informing students about STEM careers. While these key characteristics include commonly agreed upon components of integrated STEM (e.g., Johnson et al., 2016 ; Kelly & Knowles, 2016; Moore, Stohlmann, et al., 2014), our framework conceptualizes each of the key characteristics in detail, operationalizing integrated STEM for educators, curriculum developers, and researchers. This is critical as statements such as “an effort to combine some or all of the four disciplines of science, technology, engineering, and mathematics into one class, unit, or lesson that is based on connections between the subjects and real-world problems” (Moore, Stohlmann, et al., 2014, p. 38) do not provide enough information about critical issues such as how to integrate any subset of the STEM disciplines or what real-world problems would be appropriate to drive learning in STEM for all students.

Most importantly, our framework directly attends to issues of diversity and equity as current definitions and implementation of integrated STEM are content-focused and consider only the technical aspects of engaging in solving real-world problems and/or engineering design challenges. Our framework specifically addresses issues raised by critics of integrated STEM (e.g., Gunckel & Tolbert, 2018 ; Roehrig et al., 2020 ; Zeidler, 2016 ) to give full consideration to the socio-historical-political context in which the engineering design challenge resides and use this knowledge in making design decisions. The framework also attends to the development of STEM identities for all students through understanding how the nature of the real-world problem and/or engineering design challenge can constrain or afford interest and engagement in STEM for girls and students of color (e.g., Billington et al., 2013 ; Diekman et al., 2010 ; Leammukda & Roehrig, 2020 ). Also important to promoting positive STEM identities for all students is elevating students’ lived experiences and cultural knowledge as valid forms of knowledge to be drawn on as they engage in developing solutions to real-world problems.

Availability of data and materials

Data sharing is not applicable to this article as no datasets were generated or analyzed during the current study.

Abbreviations

National Academy of Engineering

National Academy of Science

Next Generation Science Standards

National Research Council

President’s Council of Advisors on Science and Technology

Socio-scientific Issues

Science-Technology-Engineering-Mathematics

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Acknowledgements

This research was made possible by the National Science Foundation grants 1854801, 1812794, and 1813342. The findings, conclusions, and opinions herein represent the views of the authors and do not necessarily represent the view of personnel affiliated with the National Science Foundation.

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GR wrote the manuscript based on substantive discussions with ED, JE, and ERW. ED, JE, and ERW provided significant feedback on the manuscript. All authors read and approved the final manuscript.

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• Published: 12 November 2019

Interdisciplinarity revisited: evidence for research impact and dynamism

• Keisuke Okamura   ORCID: orcid.org/0000-0002-0988-6392 1 , 2  

Palgrave Communications volume  5 , Article number:  141 ( 2019 ) Cite this article

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Addressing many of the world’s contemporary challenges requires a multifaceted and integrated approach, and interdisciplinary research (IDR) has become increasingly central to both academic interest and government science policies. Although higher interdisciplinarity is then often assumed to be associated with higher research impact, there has been little solid scientific evidence supporting this assumption. Here, we provide verifiable evidence that interdisciplinarity is statistically significantly and positively associated with research impact by focusing on highly cited paper clusters known as the research fronts (RFs). Interdisciplinarity is uniquely operationalised as the effective number of distinct disciplines involved in the RF, computed from the relative abundance of disciplines and the affinity between disciplines, where all natural sciences are classified into eight disciplines. The result of a multiple regression analysis ( n  = 2,560) showed that an increase by one in the effective number of disciplines was associated with an approximately 20% increase in the research impact, which was defined as a field-normalised citation-based measure. A new visualisation technique was then applied to identify the research areas in which high-impact IDR is underway and to investigate its evolution over time and across disciplines. Collectively, this work establishes a new framework for understanding the nature and dynamism of IDR in relation to existing disciplines and its relevance to science policymaking.

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Introduction: a new testbed for evaluating interdisciplinary research.

Many of the world’s contemporary challenges are inherently complex and cannot be addressed or resolved by any single discipline, requiring a multifaceted and integrated approach across disciplines (Gibbons et al., 1994 ; Frodeman et al., 2010 ; Aldrich, 2014 ; Ledford, 2015 ). Given the widespread recognition today that cross-disciplinary communication and collaboration are necessary to not only pursue a curiosity-driven quest for fundamental knowledge but also address complex socioeconomic issues, interdisciplinary research (IDR) has become increasingly central to both academic interest and government science policies (Jacobs and Frickel, 2009 ; Roco et al., 2013 ; NRC, 2014 ; Allmendinger, 2015 ; Van Noorden, 2015 ; Davé et al., 2016b ; Wernli and Darbellay, 2016 ). Accordingly, various national and international programmes, focusing especially on promoting IDR, have recently been launched and developed in many countries through specialised research funding and grants or through staff allocations (e.g., Davé et al., 2016a ; Gleed and Marchant, 2016 ; Kuroki and Ukawa, 2017 ; NSF, 2019 ).

Driving these pro-IDR policies and the attendant rhetoric is an implicit assumption that IDR is inherently beneficial and has a more substantial impact compared with traditional disciplinary research. However, this assumption has rarely been supported by solid scientific evidence, and in most cases, the supposed merit of IDR has been based on anecdotal evidence from specific narrative examples or case studies (for related perspectives, see e.g., Jacobs and Frickel, 2009 , p. 60; Weingart, 2010 , p. 12). Considering the fact that significant resources have been and are being invested in promoting IDR, better clarity regarding the relationship between interdisciplinarity and its potential benefit, particularly the research performance, could help increase accountability for such policy actions.

Extant literature has investigated the relationship between interdisciplinarity and the research performance by using various data sources and methodologies, with different operationalisation of both dimensions (e.g., Steele and Stier, 2000 ; Rinia et al., 2001 ; Rinia et al., 2002 ; Adams et al., 2007 ; Levitt and Thelwall, 2008 ; Larivière and Gingras, 2010 ; Chen et al., 2015 ; Elsevier, 2015 ; Yegros-Yegros et al., 2015 ; Leahey et al., 2017 ). Owing to such diverse investigation approaches, it is unsurprising that the results are usually neither consistent nor conformable and sometimes are even contradictory among the literature. Given this situation, it is desirable that a more robust and reproducible methodology be developed and implemented to systematically assess the value of IDR in practice. The present study seeks to contribute to this goal by developing a new testbed for IDR evaluation. The focus is especially placed on highly cited paper clusters known as the research fronts (RFs), which are defined by a co-citation clustering method (Small, 1973 ). In this new approach, the research interdisciplinarity is characterised by the disciplinary diversity of the papers that compose the RF, and the research performance is operationalised and measured as a field-normalised citation-based measure at the RF level.

This proposed RF-based approach has three major advantages over common approaches that focus, for instance, on individual papers (Steele and Stier, 2000 ; Adams et al., 2007 ; Larivière and Gingras, 2010 ; Chen et al., 2015 ; Elsevier, 2015 ; Yegros-Yegros et al., 2015 ) to investigate the potential effect of interdisciplinarity on high-impact research. First, through the analyses of RFs, it is possible to capture a snapshot of the most lively, animated and high-impact research currently being undertaken in the academic sphere, since the papers composing RFs are classified as the most highly cited papers for each science discipline. As science policymakers, leaders, funders and practitioners are often most interested in promoting and supporting high-impact research, the evidence and insights obtained through this investigation of RFs can assist them in formulating more accountable policy recommendations that otherwise cannot be adequately addressed. Second, the RF is a unique manifestation of knowledge integration from different science disciplines. By construction, the interdisciplinarity operationalised at the RF level does not represent a mere parallel existence of discrete knowledge sources from multiple disciplines; rather, it indicates the state of the knowledge integration from multiple disciplines to create new knowledge syntheses. This organic scientific knowledge structure can be captured more effectively and robustly through RFs than through, for instance, an individual paper’s reference list. Consequently, the emergence of a new high-impact research area will also be more reliably detected at the RF level than at the paper level. The third advantage of the proposed RF-based approach is related to the technicalities. As discussed, RFs are unique self-organised units of knowledge in which bibliographically important information is effectively compressed and integrated. As this study considers thousands of papers, it is considerably more efficient and effective to handle RFs compared with a multitude of papers while conducting data retrieval, analysis and visualisation. These multifold advantages of the RF-based approach enable this study to comprehensively and uniquely assess the value of interdisciplinarity.

Methods: through the lens of emergent research fronts

The analyses in this study were based on the data retrieved from the Essential Science Indicators (ESI) database, published by Clarivate Analytics, and data published by the National Institute of Science and Technology Policy (NISTEP) of Japan. In this section, the definitions for the main terms used in this paper—the RFs, the research areas, the research impact and the interdisciplinarity index—are provided. Subsequently, the regression model specification used in this study and the rationale behind it are detailed.

Research fronts and (broad) research areas

The bibliometric data for the research papers (regular scientific articles and review articles) and citation counts were derived from more than 10,000 journals indexed in the Web of Science Core Collection published by Clarivate Analytics. The master journal list is updated regularly, with each journal being assigned to only one of the 22 ESI research areas (see Supplementary Table S1 ). Given a pre-set co-citation threshold, the original ‘ESI-RFs’ were defined based on the number of times the pairs of papers had been co-cited by the specified year and month within a five-year to six-year period. The ESI-RF investigation in this paper was focused on papers classified as ‘Highly Cited Papers’ in the ESI database, which are the top 1% for annual citation counts in each of the 22 ESI research areas based on the 10 most recent publication years.

Based on the ESI framework, the NISTEP’s Science Map dataset (NISTEP, 2014 , 2016 , 2018 ) defines a set of ‘aggregate RFs’ using a second-stage clustering in each of the three data periods: 2007–2012, 2009–2014 and 2011–2016, which are denoted in this study as S 2012 , S 2014 and S 2016 , respectively. Each dataset comprised approximately 800–900 of such ‘aggregate RFs’ (hereinafter referred to as ‘RFs’). The i -th RF in the aggregate dataset S   =   S 2012   ∪   S 2014   ∪   S 2016 was denoted by RF i . After excluding two RFs with missing data, there were | S | = 2,560 RFs collected for the total data period (2007–2016), with a cumulative number of 53,885 papers (Table 1 ).

For this study’s purpose, the 22 ESI research areas were reorganised into nine broad categories based on the classification scheme in Supplementary Table S1 . Of these, we focused on the following eight categories composed of 19 ESI natural science areas: ‘ Environmental and Geosciences ’, ‘ Physics and Space Sciences ’, ‘ Computational Science and Mathematics ’, ‘ Engineering ’, ‘ Materials Science ’, ‘ Chemistry ’, ‘ Clinical Medicine ’ and ‘ Basic Life Sciences ’, which we denote collectively as \({\mathscr{R}}\) . The other category, composed of the three ESI ‘non-natural-science’ areas—‘ Economics and Business ’, ‘ Social Sciences, General ’ and ‘ Multidisciplinary ’—was excluded from the analyses because the main research output were books rather than journal papers and thus were under-represented in the data.

Research impact measure

Although higher citations do not necessarily represent the intrinsic value or quality of a paper, research impact is commonly operationalised as citation-based measure (e.g., Steele and Stier, 2000 ; Rinia et al., 2001 , 2002 ; Adams et al., 2007 ; Levitt and Thelwall, 2008 ; Larivière and Gingras, 2010 ; Chen et al., 2015 ; Elsevier, 2015 ; Yegros-Yegros et al., 2015 ), which is due to not only its intuitive and computational simplicity but also the data availability and tractability. Moreover, the citation-based research impact is often defined as a field-normalised measure, that is, the absolute citation counts divided by the world average in each discipline, in order to take into account for the disciplinary variations in publication and citation practices. This study also used a surrogate field-normalised citation-based measure of research impact; however, in contrast to previous studies, it was defined and measured at the RF level rather than at a paper level (Steele and Stier, 2000 ; Adams et al., 2007 ; Larivière and Gingras, 2010 ; Chen et al., 2015 ; Elsevier, 2015 ; Yegros-Yegros et al., 2015 ), at a journal level (Levitt and Thelwall, 2008 ) or at a research programme level (Rinia et al., 2001 , 2002 ).

Let N i be the number of papers comprising RF i , and let \(N_i = \mathop {\sum}\nolimits_{{\mathrm{A}} \in {\mathscr{R}}} {N_{i,{\mathrm{A}}}}\) be its decomposition based on the research areas, where N i ,A is the number of papers in RF i attributed to each research area A  ∈   \({\mathscr{R}}\) . Let X i be the actual citation counts received by RF i . Let also C A;y/m be the baseline citation rate for each research area A as noted on the ESI database as of the specified year and month (‘y/m’), which is defined as the total citation counts received by all papers attributed to research area A divided by the total number of papers attributed to the same research area in the 10 years of the Web of Science. Then, the mean baseline citation rate for each research area A, denoted 〈 C A 〉, was obtained by averaging C A;y/m over all the ESI data periods from March 2017 to January 2019 (i.e., from y/m = 2017/03 to 2019/01; bimonthly) (Supplementary Table S2 ). Subsequently, the research impact measure for RF i was defined by

that is, the ratio of the actual citation counts earned by RF i to the expectation value of the citation counts for the same RF.

Interdisciplinarity index

The context-dependent nature of research interdisciplinarity has made its identification and assessment far from trivial, hitherto without a broad consensus on its operationalisation (Porter and Chubin, 1985 ; Morillo et al., 2003 ; Huutoniemi et al., 2010 ; Klein et al., 2010 ; Wagner et al. 2011 ; Siedlok and Hibbert, 2014 ; Adams et al., 2016 ). Numerous attempts have been made to develop methodologies for operationalising interdisciplinarity in practice, not only at the paper level (Morillo et al., 2001 ; Adams et al., 2007 ; Porter and Rafols, 2009 ; Larivière and Gingras, 2010 ; Chen et al., 2015 ; Elsevier, 2015 ; Yegros-Yegros et al., 2015 ; Leahey et al., 2017 ) but also at a journal level (Morillo et al., 2003 ; Levitt and Thelwall, 2008 ; Leydesdorff and Rafols, 2011 ) or at a research programme level (Rinia et al., 2001 ; Rinia et al., 2002 ). Still, it is most popularly defined at a paper level, either in terms of ‘knowledge integration’, as measured through the proportion of references from different disciplines, or ‘knowledge diffusion’, as measured through the proportion of citations received from different disciplines (Porter and Chubin, 1985 ; Adams et al., 2007 ; Van Noorden, 2015 ). Regardless of the operationalisation level, a more refined quantitative approach to interdisciplinarity, conceptualised as the disciplinary diversity, necessarily requires the following three aspects: ‘variety’ (number of disciplines involved), ‘balance’ (distribution evenness across disciplines) and ‘dissimilarity’ (degree of dissimilarity between the disciplines) (see Rao, 1982 ; Stirling, 2007 ). Most previous IDR studies have evaluated interdisciplinarity based on either variety or balance, while some recent studies (e.g., Porter and Rafols, 2009 ; Leydesdorff and Rafols, 2011 ; Mugabushaka et al., 2016 ) have made efforts to incorporate the aspect of dissimilarity as well.

This study also operationalises interdisciplinarity as an integrated measure of the aforementioned three aspects; however, in contrast to previous studies, it was uniquely operationalised at the RF level. Specifically, the interdisciplinarity index for RF i was defined and evaluated using the following ‘canonical’ formula (Okamura, 2018 ):

Here, w i ,A denotes the relative abundance of a research area A in RF i , defined by, using the previous notations, w i ,A  =  N i ,A / N i , satisfying \({\sum\nolimits_{{\mathrm{A}} \in {\mathscr{R}}}} {w_{i,{\mathrm{A}}} = 1}\) . The effective affinity (i.e., similarity) between each pair of research areas A and B in \({\mathscr{R}}\) , denoted 〈 M AB 〉 in (2), was defined as the time-averaged Jaccard indices (see Supplementary Methods and Discussion ), where, as before, the bracket ‘〈…〉’ represented the average over the 12 ESI data periods. Figure 1 shows the chord diagram representation of the affinity matrix (see Supplementary Table S3 for the source data), from which it was evident that the degree of affinity varied considerably for different pairs of the disciplines.

A chord diagram representation of the affinities between research areas. The affinity indices were defined as the time-averaged Jaccard similarity indices and were evaluated between each pair of research areas ( Supplementary Methods and Discussion ). They were assigned to each connection between the research areas, represented proportionally by the size of each arc, from which it is evident that the degree of affinity varied considerably for different pairs of the disciplines (see Supplementary Table S3 for the source data)

The interdisciplinarity index (2) is unique because it is conceptualised as the effective number of distinct disciplines involved in each RF and is robust regarding the research discipline classification scheme. Specifically, it has the special property of remaining invariant under an arbitrary grouping of the constituent disciplines, given that the between-discipline affinity is properly defined for all pairs of disciplines. For instance, suppose one is interested in measuring the interdisciplinarity of RF i based on the classification scheme \({\mathscr{R}}\) 1 and someone else wishes to measure the interdisciplinarity of the same RF i based on the more aggregate classification scheme \({\mathscr{R}}\) 2 . Then, for the interdisciplinarity index to be a consistent measure of disciplinary diversity, both approaches must result in the same value for the interdisciplinarity; that is, \({\it{\Delta }}_i\left[ {{\mathscr{R}}_1} \right] = {\it{\Delta }}_i\left[ {{\mathscr{R}}_2} \right]\) . Otherwise, it results in an inconsistent situation as the interdisciplinarity changes with respect to the level (or ‘granularity’) of the research discipline classification, while the physical content of the RF (i.e., the constituent papers) remains the same. Note that popular (dis)similarity-based diversity measures such as the Rao-Stirling index (Rao, 1982 ; Stirling, 2007 ) and the Leinster-Cobbold index (Leinster and Cobbold, 2012 ) do not generally satisfy this invariance property; to the best of our knowledge, the only known diversity measure that respects this invariance property is given by the formula (2), the theoretical grounds for which have recently been established for a general diversity/entropy quantification context (Okamura, 2018 ).

Using this formula, the interdisciplinarity index for each RF in S was obtained, from which it was found that 43.6% of the RFs were mono-disciplinary (i.e., Δ = 1) and more than half were interdisciplinary (Fig. 2a ; median = 1.2, range = 2.5; see also Supplementary Fig. S1a ).

Relationship between research impact and interdisciplinarity. a The histogram for the interdisciplinarity index (median = 1.2, range = 2.5, interquartile range = 0.58); b The histogram for the log-transformed research impact (mean = 1.2, SD = 0.83); c The scatterplot showing the associations between the interdisciplinarity index and the log-transformed research impact. The solid line in the scatterplot represents the robust linear model fit. The shaded region and the dashed lines, respectively, indicate the 95% confidence interval based on the standard error of the mean and on the standard error of the forecast, including both the uncertainty of the mean prediction and the residual

Regression model

Based on the aforementioned operationalisations of the research impact and the interdisciplinarity index, the relationship between the two variables was analysed using a regression analysis method. As the histogram analysis showed that the original research impact distribution was skewed, it was log-transformed so that the distribution curve was closer to a normal curve (Fig. 2b ; mean = 1.2, SD = 0.83; see also Supplementary Fig. S1b ). The scatterplot of the log-transformed research impact against the interdisciplinarity index indicated that these variables were relatively linearly related (Fig. 2c ; see also Supplementary Fig. S2a–c ). Subsequently, the following multiple linear regression model was investigated:

where, x i was a l ×  k vector for predictive variables, and β was a k  × l vector for the regression coefficients, which were the unknown parameters to be estimated (with k being some integer). To deal with the possible issue of heteroscedasticity, the model was analysed using heteroscedasticity-robust standard errors (i.e., the Huber-White estimators of variance). In addition, a test for serial correlation (i.e., the Breusch-Godfrey Lagrange multiplier test) was conducted as a post-estimation procedure, which indicated that there was no serial correlation between the residuals in each model considered (see below).

For comparability, five different regression models corresponding to different specifications of the predictive variables were analysed and labelled Models 1–5, with the following sets of predictive variables, respectively, defined for each model:

In Model 1, the interdisciplinarity index was used as the only predictive variable, which was added to the intercept term (constant). In Model 2, the variables associated with IntlCollab and IntlCiting , denoting the proportion of internationally collaborated papers in papers comprising an RF and in the citing papers, respectively, were included as additional predictive variables. Models 3, 4 and 5, in the same manner, represented the prior model with a new set of predictive variables, respectively, added as follows: Year dummy variables for the different years (2012, 2014 and 2016) of the Science Map to capture the possible time-fixed effects; a ‘ Research Area ’ control set to represent the proportion of papers belonging to each research area A  ∈   \({\mathscr{R}}\) ; and a ‘ Country ’ control set to represent the proportion of papers for which authors from each country of \({\mathscr{C}}\)  = { US, France, UK, Germany, Japan, South Korea, China } contributed (measured on a fractional-count basis). The last two control sets were introduced to, respectively, account for the possible discipline-related and country-related effects that could reflect such factors as research environment, practices and cultures intrinsic to each discipline or/and country.

In interpreting the regression results, each regression coefficient β k (i.e., the k -th component of β in Eq. ( 3 )) indicated that a one point increase in the predictive variable x k was associated with β k point increase in ln( I ), or equivalently, [exp( β k )−1] × 100% increase in the research impact ( I ) at the specified significance level. Care should be taken in interpreting the results for the proportion variables ( IntlCollab , IntlCiting , ‘ Research Area ’ and ‘ Country ’ control sets) as the regression coefficients for each of these variables represented the effect on the criterion variable (i.e., the log-transformed research impact) associated with a 100% increase in the proportion variable. For the time-fixed effects, the base category was chosen as Year  = 2014, against which the effects of the other two data periods (corresponding to Year  = 2012 and 2016) were measured. For the ‘ Research Area ’ control set, the effect of the proportion of each research area in \({\mathscr{R}}\) was measured against the set of ‘residual’ (i.e., ‘non-natural-science’) ESI research areas. Finally, for the ‘ Country ’ control set, the effect of the share of each country in \({\mathscr{C}}\) was measured against the set of those countries not listed in \({\mathscr{C}}\) .

Results: interdisciplinarity as a key driver of impact at research fronts

The results of the multiple regression analyses for all the five models ( n  = 2,560; two-tailed) are summarised in Supplementary Table S4 . Based on the adjusted- R 2 for each model (the bottom row of the table), Model 5 was found to be the preferred model in terms of the goodness-of-fit, and therefore, this model was considered in detail in this study; see Table 2 for the summary table.

Particularly, the estimated coefficient for the interdisciplinarity index was found to be positive and statistically highly significant. Specifically, a one point increase in the interdisciplinarity index in an RF (i.e., an increase in the effective number of distinct disciplines by one) is, on average, associated with approximately a (( e 0.186 −1) × 100% ≈) 20% increase in the research impact, holding other relevant factors constant ( P  < 0.001). This appears to imply that, on average, a high-impact RF is more likely to be formed either in the presence of disciplines that are more dissimilar or with a more balanced mix of distinct disciplines, or both. What this indicates is that while the papers composing the RFs were already high-impact papers as they were classified as ‘Highly Cited Papers’ in the ESI database, nevertheless the degree of the ‘high-impact’ at the RF level was found to be higher on average as the interdisciplinarity level increased. Notably, this implication was found to hold sufficiently generally, reproducing the same results qualitatively for each data period separately (Supplementary Fig. S2a–c ).

Though outside the main scope of the present study, the regression results led to additional intriguing implications for the research impact predictors. Particularly, the regression coefficient for IntlCollab implied that a 1% increase in the international collaboration in an RF was, on average, associated with an approximately 0.6% increase in the research impact ( P  < 0.001), which was also found to hold sufficiently generally across the three data periods. By contrast, the regression coefficient for IntlCiting was found to be negatively significant ( P  < 0.001). For the time-fixed effects, the research impact was found to be, on average, statistically significantly lower in the ‘2012’ data compared with the ‘2014’ or ‘2016’ data ( P  < 0.001). However, no statistically significant difference was observed between the ‘2014’ and ‘2016’ data (see also Supplementary Fig. S1b , which already indicated this trend via the kernel density estimations for the criterion variable). Further, the coefficient for each of the ‘ Research Area ’ variables was found to be positively significant ( P  < 0.001), indicating that, on average, a paper belonging to either area of \({\mathscr{R}}\) is likely to have a higher research impact compared with a paper attributed to the ‘residual’ (i.e., ‘non-natural-science’) research area. Finally, the result for each of the country-share variables in \({\mathscr{C}}\) provided some intriguing insights into its effect on the research impact. For instance, the result for the variable ‘ US ’ implied that, on average, replacing 1% of the contributions from the ‘residual’ countries with that from the US resulted in an approximately 0.3% increase in the research impact ( P  < 0.001). These observed relationships between the research impact and each predictor variable, along with their policy implications, should be investigated in future studies.

Discussion: evolving landscape of cross-disciplinary research impact

To further enhance our understanding of the relationship between interdisciplinarity and research impact, a more detailed investigation of the finer structures and evolutionary dynamism of high-impact research over time and across disciplines is desirable. For this purpose, we present in the following a new bibliometric visualisation technique and demonstrate its potential use in the study of interdisciplinarity.

‘ Science Landscape ’: a novel bibliometric visualisation approach

Significant efforts have been made to visualise scientific outputs, especially bibliometric data regarding the citation characteristics. Such efforts have been partially successful in displaying the links between and across various research disciplines or subject categories (Small, 1999 ; Boyack et al. 2005 ; Igami and Saka, 2007 ; Leydesdorff and Rafols, 2009 ; Porter and Rafols, 2009 ; Van Noorden, 2015 ; Klavans and Boyack, 2017 ; Elsevier, 2019 ). Each alternative form of ‘science mapping’ has its own merit in particular situations, offering complementary and synergistically beneficial implications not only for a deeper understanding of academic (inter-)disciplinarity but also for policy implementation. To contribute to the evidence-base in this fast-growing and innovative field, here we present a new technique—called the Science Landscape —that visualises research impact and its development patterns in relation to the entire natural science discipline corpus. The same research impact measure and the interdisciplinarity index as used in the previous sections were employed to ensure methodological consistency between the empirical implications drawn from this new visualisation technique and the quantitative evidence already obtained from the regression analyses.

In the Science Landscape diagrams (Fig. 3a–c ), the eight (broad) research areas were arranged along the edge of a circular map, with the angle of each research area being proportional to the number of papers attributed to that research area. Each RF was then mapped onto the circular map for each data period (Supplementary Fig. S3a–c ), so that the distance from the edge to the centre indicated the RF’s interdisciplinarity index; that is, the closer it was to the centre, the greater the degree of interdisciplinarity. The angle around the centre was determined by the disciplinary composition; that is, the closer it was to a particular research area, the higher its share in the disciplinary composition. A similar circular research field frame (27 subject areas) is used in the ‘Wheel of Science’ for Elsevier’s SciVal system based on Scopus data (Klavans and Boyack, 2017 ; Elsevier, 2019 ); however, the objectives and what is mapped and how it is mapped are dissimilar. In particular, the Science Landscape shown here was based on 3D mapping technology, so that the height of each RF i was proportional to the log-transformed research impact, ln( I i ), with the highest (‘over the clouds’) and lowest (‘under the sea’) research impact levels being depicted in red and blue, respectively. Here the heights of the RFs were not added vertically; rather, at each map position, the maximum height value was used to depict the surface of the landscape. The rationale behind this method was that for the current purpose of investigating the cross-disciplinary spectrum of research impact, it was more meaningful and implicative to visualise ‘individually outstanding high-impact RFs’ rather than ‘a number of low-impact RFs additively forming high peaks’.

Dynamic evolution of research impact across disciplines. Corresponding to each data period—2007–2012 ( a ), 2009–2014 ( b ) and 2011–2016 ( c )—the Science Landscape diagrams are shown. The figures on the left show the top views and the figures on the right show the birds-eye views. The eight ‘base’ research areas are arranged along the edge of the circular map, and the angle allocated to each research area is proportional to the number of papers from each discipline. The highest and lowest levels of research impact are depicted in red and blue, respectively

Moreover, each RF’s concrete disciplinary composition was indicated by the direction(s) towards which the RF’s peak tails (see Supplementary Fig. S4 ). For instance, in the Science Landscape for 2009–2014 (Fig. 3b ), there is a high research impact peak ( I  = 100.7) near the centre that has one tail towards ‘ Comp & Math ’ and another tail towards ‘ Basic Life Sciences ’ (the solid square region). In light of the original NISTEP’s Science Map dataset (NISTEP, 2016 ), this peak corresponds to the RF characterised by feature words such as ‘RNA Seq’ and ‘next generation sequencing’. Then, intuitively, this correspondence indicates that during this period, there was a scientific breakthrough related to new sequencing technology that occurred at the intersection of these two disciplines. Further technical and mathematical details including the explicit functional form of the 3D research impact profile are presented in Supplementary Methods and Discussion .

Provided the above encoding, the Science Landscape diagrams (Fig. 3a–c ) clearly illustrate how the shape of interdisciplinarity has changed over the three data periods. It is noticeable that the overall landscape of the research impact has never been static, monolithic nor homogeneous; rather, it evolves dynamically, both over time and across disciplines. One of the most remarkable features can be seen in the northwest of the map (dashed circle region) at the low ivory-white-coloured ‘mountains’ in 2007–2012 (Fig. 3a ), where new high-impact RFs are evolving and developing into a group of yellow-coloured mid-height ‘mountains’ in the years up to 2009–2014 (Fig. 3b ) and towards 2001–2016 (Fig. 3c ). This dynamic research impact growth indicates the increased IDR focus around the region during the data period. Thus, this visualisation can assist identifying where the scientific community’s focus of attention is undergoing a massive change, where high-impact IDR is underway worldwide, and where new knowledge domains are being created. Each landscape appears to represent the superposition of the following two research impact evolutionary patterns; one that has steady, stable or predictable development that accounts for the ‘global’ or ‘evergreen’ structure of the landscape, and the other that represents a breakthrough in science or a discontinuous innovation, induced ‘locally’ in a rather abrupt or unpredictable manner. The challenge of science policy, therefore, is developing ways to address each of these dynamic evolutionary patterns and the mechanism thereof and to promote IDR in a more evidence-based manner with increased accountability for the investments made.

Summary and conclusions: towards evidence-based interdisciplinary science policymaking

This study revisited the classic question as to the degree of influence interdisciplinarity has on research performance by focusing on the highly cited paper clusters known as the RFs. The RF-based approach developed in this paper had several advantages over more traditional approaches based on a paper-level or journal-level analysis. The multifold advantages included: quality-screening, cross-disciplinary knowledge syntheses, structural robustness and effective data handling. Based on data collected from 2,560 RFs from all natural science disciplines that had been published from 2007 to 2016, the potential effect of interdisciplinarity on the research impact was evaluated using a regression analysis. It was found that an increase by one in the effective number of distinct disciplines involved in an RF was statistically highly significantly associated with an approximately 20% increase in the research impact, defined as a field-normalised citation-based measure. These findings provide verifiable evidence for the merits of IDR, shedding new light on the value and impact of crossing disciplinary borders. Further, a new visualisation technique—the Science Landscape —was applied to identify the research areas in which high-impact IDR is underway and to investigate its evolution over time and across disciplines. Collectively, this study established a new framework for understanding the nature and dynamism of IDR in relation to existing disciplines and its relevance to science policymaking.

Validity and limitations

The new conceptual and methodological framework developed to reveal the nature of IDR in this paper would be of interest to a wide range of communities and people involved in research activities. However, as with any bibliometric research, this study also faced various limitations that may have impacted the general validity of the findings, and thus, its practicability in the real policymaking process is necessarily limited. To conclude, some of these key issues and challenges are highlighted.

First, both the regression analysis results and the Science Landscape visualisations should be assessed with caution as they may be highly dependent on the research area classification scheme, which is not unique. Research area specifications other than those used in this study could also have been applied. For instance, a factor-analytical approach (Leydesdorff and Rafols, 2009 ) to identify a ‘better justified’ set of academic disciplines could be useful in providing a more nuanced assessment and understanding of the nature of interdisciplinarity and could possibly have higher robustness and reliability. Moreover, a different research area arrangement along the edge of the circular map would have resulted in different Science Landscape visualisations, and the cross-disciplinary spectrum of research impact might have been more plentiful or profound than observed in this study.

Second, in relation to the first point, the quantification of the affinity between the research areas could have been refined in other acceptable ways. Our rationale behind the definition of the between-discipline affinity based on the Jaccard-index was that papers from closer (i.e., with higher affinity) research areas were more likely to be co-cited, and thus more likely to belong to the same ESI-RF (see Supplementary Methods and Discussion ). In this approach, the affinity matrix was defined solely using the bibliometric method, and therefore its matrix elements may have been more or less biased because of the publication/citation practices of the existing disciplines. Consequently, it may have failed to capture the inherent ‘true’ between-discipline affinities responsible for the ‘true’ interdisciplinarity operationalised at the RF level.

Third, it is unlikely that the regression model specification used in this study included every salient research impact predictor. For example, factors such as the types of research institute, departmental affiliations, individual journal characteristics and funding opportunities (e.g., funding agencies and programmes/fellowships) were not considered in the model owing to their unavailability in the dataset. Moreover, the links between the different scientific specialties irrespective of their academic discipline could have also influenced the research performances. These omitted variables may also have affected the regression results because they may be associated with both the criterion variable (i.e., the research impact) and some predictive variables including the interdisciplinarity index.

Finally, there are inherent limitations in using citation-based methods to evaluate research performance. Combining bibliometric approaches with expert judgements from qualitative perspectives will be favoured to extract the policy implications and recommendations from a wider context. Although the societal impacts of research (see e.g., Bornmann, 2013 ) were beyond the scope of the present work, it is hoped that this study’s findings can be extended to incorporate such societal aspects. In so doing, it is also important to consider not only the benefits but also the costs of IDR (Yegros-Yegros et al., 2015 ; Leahey et al., 2017 ) for interdisciplinary approaches to provide viable policy options for decision-makers.

With further conceptual and methodological improvements, it is hoped that future studies can reveal more about the nature of IDR and its intrinsic academic and/or societal value by overcoming some of the aforementioned limitations. Continued efforts will contribute to the development of the more evidence-based and accountable IDR strategies that will be imperative for addressing, coping with and overcoming contemporary and future challenges of the world.

Data availability

The datasets generated and/or analysed during this study are not currently publicly available, but are available from the corresponding author on reasonable request.

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Acknowledgements

This work was conducted as part of the in-house research activities of the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan. This work also contributes to the MEXT’s ‘Science for RE-designing Science, Technology and Innovation Policy (SciREX)’ programme, hosted at the National Graduate Institute for Policy Studies (GRIPS), for which the author serves as Policy Liaison Officer. The views and conclusions contained herein are those of the author and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the government of Japan.

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What do integrated STEM projects look like in middle school and high school classrooms? A systematic literature review of empirical studies of iSTEM projects

• Felicity I. McLure   ORCID: orcid.org/0000-0003-3664-9146 1 ,
• Kok-Sing Tang 2 &
• P. John Williams 2  

International Journal of STEM Education volume  9 , Article number:  73 ( 2022 ) Cite this article

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The past 20 years has seen a growing focus on the integration of Science, Technology, Engineering and Mathematics (iSTEM) disciplines in schools to provide students with authentic experiences in solving real-world problems. A frequently stated aim for iSTEM projects has been increasing engagement and interest in pursuing STEM subjects in senior high school and tertiary studies. In order to better understand the iSTEM projects’ landscape in school classes, this systematic literature review analysed empirical studies of integrated STEM projects carried out in secondary schools to answer the following questions: What are the characteristics of the projects described and to what extent do these projects reflect characteristics of effective STEM projects; and to what extent does research into iSTEM projects in classrooms investigate specific methods of integration of STEM domains? Thirty-five peer-reviewed publications were identified from database searches that met the following inclusion criteria: (a) integrating two or more of the STEM areas, (b) middle/high school education and (c) explicitly describing the research intervention. The review revealed a diversity of iSTEM approaches in the literature, with Engineering and Science, particularly Physics, the most commonly integrated fields. Concerns are raised about the degree to which projects are relevant to students and their context and address the diversity found within student cohorts. A gap was found in the literature in detailing how teachers and students enact integration of STEM skills in these projects.

Introduction

Integration of STEM (Science, Technology, Engineering and Mathematics) fields in projects from K-12 has been proposed as a means of improving engagement with these fields and increasing the selection of related courses at senior high school and university level (Honey et al., 2014 ). However, despite these efforts, enrolments in STEM fields such as Physics, Engineering, Computing and Mathematics at tertiary level continue to be of concern (Office of the Chief Scientist, 2020 ).

However, despite the focus over the past 20 years on engaging student interest in STEM fields through providing students opportunities to use skills and knowledge from different STEM domains to solve problems, little is known about the types of projects that are being characterised as integrated STEM projects in the classroom and the ways in which the domains are integrated. When teachers or researchers talk about projects that integrate STEM, are certain STEM domains, such as engineering and science, more likely to be addressed than others? In addition, to what extent and in what ways are data being collected and analysed to explain how STEM domains are being integrated by teachers and students while carrying out projects characterised as integrated STEM projects? As a snapshot of the types of projects that integrate STEM, this systematic literature review aims to investigate these questions by analysing empirical studies of projects that claimed to integrate STEM domains, within classroom settings, from 2000 until the end of 2021.

Definitions of integrated STEM

There has been much debate about what constitutes integrated STEM education and hence there has also been disagreement about the most effective ways to approach instruction when integrating STEM domains (Moore et al., 2020 ; Nadelson & Seifert, 2017 ; Sgro et al., 2020 ). STEM integration is frequently defined as the attempt to support students in making connections between two or more of the STEM disciplines within an authentic context (Kelley & Knowles, 2016 ; Moore et al., 2014 ). This models real-world experiences where teams of professionals from differing disciplines work together to solve real-world problems. For the purposes of this systematic literature review, we examined STEM projects that involved interdisciplinary or transdisciplinary integration of at least two domains (Honey et al., 2014 ; Kelley & Knowles, 2016 ; Li, 2018 ). Interdisciplinary integration involves relating closely linked concepts and skills from two or more disciplines with the aim of deepening knowledge and skills (Vasquez et al., 2013 ). Transdisciplinary integration applies knowledge and skills from two or more disciplines to real-world problems and projects to shape the learning experience (Vasquez et al., 2013 ).

There are differences in the interpretation of the T and the E in STEM at the school level. Some curricula interpret Technology as digital technology, while in other countries, Technology is design and technology. For the purposes of this research, we adopt the Australian conception in which Technology represents both digital technology and design and technology (ACARA, 2022 ). Few jurisdictions include Engineering as a school subject (apart from the USA), so in the STEM context, this element of the acronym is increasingly considered as a reference to the Engineering design process, as promoted by the Next Generation Science Standards (NGSS, 2022 ).

Prior reviews of integrated STEM literature

Even though the acronym “STEM” was only coined in 2001, there has been a large amount of literature published on the topic. Trends in STEM literature over the preceding period were analysed by Li et al. ( 2020 ) who found that research in STEM education has increased in importance over the two decades since the term was first used, but that there was a lack of consensus about what constitutes STEM and particularly, integrated STEM. The diversity of opinions and definitions of STEM has contributed to difficulties in carrying out general literature reviews to describe the field (Li et al., 2020 ). As a consequence, many of the literature reviews available focus on narrow areas of integrated STEM education.

For instance, a review of commonly used teaching strategies in integrated STEM education (Mustafa et al., 2016 ) indicated that project-based learning approaches were most prominent. Likewise, a systematic literature review by Thibaut et al. ( 2018 ) investigating the instructional practices employed when implementing integrated STEM projects found that integration of STEM content, problem-centred or problem-based learning, inquiry-based learning, design-based learning and cooperative learning were the most common frameworks used. However, neither of these reviews analysed the ways in which STEM domains were explicitly or implicitly integrated within each of these instructional approaches.

A systematic review looking at the major challenges in implementing integrated STEM projects identified limited teacher confidence, lack of guidance to teachers in planning projects, and knowing how to effectively integrate STEM areas, as the major reasons why teachers avoided carrying out such projects (Arshad et al., 2021 ). Teachers themselves confirmed that, while they think that carrying out integrated STEM projects is beneficial to students, they frequently encounter challenges in fitting STEM projects into a busy curriculum, have not been provided with pedagogical tools for implementing such projects, lack support through professional development and collaboration opportunities, and hold concerns about whether students will learn the required curriculum content (Margot & Kettler, 2019 ). However, the characteristics of projects being presented to students as integrating STEM, have not been analysed. Considering the lack of clarity and consensus surrounding definitions of integrated STEM projects amongst researchers, it is not surprising that teachers are unclear and are lacking in confidence about how to proceed.

Consequently, without a clearly defined theoretical framework for integrated STEM education, there has been a lot of debate about what constitutes best practice in the integration of STEM fields. Based on a detailed analysis of literature published about integrated STEM, Roehrig et al. ( 2021 ) developed a comprehensive framework to conceptualise good practice when developing integrated STEM projects. They identified seven characteristics of effective STEM projects:

Making an engineering design process central to the project, during which students participate in at least one cycle of designing, evaluating and re-designing;

Choice of authentic problems which are relevant to the students’ contexts, which take into account the diversity of students, and address social, political or ethical aspects of the problem or socio-scientific issues (SSI);

The context of the problem needs to allow for explicit connections with developmentally appropriate subject content, skills and learning goals;

In addition, explicit connections should be made between the content in targeted disciplines which could involve multidisciplinary, interdisciplinary or transdisciplinary approaches;

Development of STEM practices are necessary in order to produce solutions, such as active social construction of understanding, collection, analysis, manipulation and visualisation of data, argumentation supported by evidence-based reasoning and consideration of multiple aspects of the problem (e.g., social benefits or costs);

Employment of twenty-first century skills such as creativity and collaboration;

Explicit links are made with possible future STEM careers.

In particular, in order to cater for diversity within the classroom, rather than taking a deficit view of what is keeping certain students from engaging with STEM, researchers and teachers are encouraged to think about what can be changed about STEM projects in order to address the interests, skills and experience of all students (Zeidler, 2016 ). Brotman and Moore ( 2008 ) identified important ways in which curricula can become more inclusive, including more gender-inclusive, by: including students’ interests and experiences; using real-world problems; engaging with societal problems that are burning issues for students; and encouraging active participation, agency, collaboration and communication. Zeidler ( 2016 ) highlights the importance of addressing socio-scientific issues as a sociocultural response to designing inclusive STEM projects. In this review, we adopt Roehrig et al.’s ( 2021 ) view of what constitutes effective integrated STEM projects.

Although reviews clarify some of the methodologies and teaching approaches used or recommended for integrating STEM in schools, what is less clear is what types of projects are being put forward as integrated STEM projects, the STEM domains that are most commonly integrated, and an understanding of how integration is achieved. While some jurisdictions provide guidelines for integrating STEM domains (e.g., NGSS Lead States, 2013 ) the focus of this paper is the enacted curriculum, that is, how guidelines and recommendations for integrated STEM are translated in practice within classrooms (Cal & Thompson, 2014 ). This systematic literature review seeks to understand these aspects by focusing on empirical studies that describe the integrated STEM projects (the enacted curriculum) being implemented with enough detail to answer the following research questions.

Research questions

Considering middle/high school projects that are identified by the authors as integrated STEM projects:

What are the characteristics of the projects described?

What disciplines are explicitly (or implicitly) integrated in these projects?

To what extent do these projects reflect characteristics of effective STEM projects identified by Roehrig et al. ( 2021 )?

What are the foci of research in empirical studies of integrated STEM projects? To what extent does research into iSTEM projects in classrooms investigate specific methods of integration of STEM domains?

In order to systematically review the literature to answer the research questions the following Preferred Items for Systematic Reviews and Meta-Analysis (PRISMA) (Moher et al., 2009 ) steps were addressed: establishing relevant inclusion/exclusion criteria; determining a search strategy; searching and screening potential studies; evaluating included studies; analysis and synthesis of themes. The inclusion and exclusion criteria utilised were:

Inclusion criteria

Empirical studies reporting the implementation of an iSTEM project.

The authors identify two or more disciplines of STE or M addressed. The project may also include STEAM (with the Arts) or STEMM (with Medicine) dimensions.

The iSTEM project is explicitly described; summarised in the methodology and/or illustrated with excerpts/examples in the results.

The projects involved middle school (Grades 5–8) or high school students (Grades 9–12) or appropriate equivalents.

Data may be qualitative and/or quantitative.

The intervention can take place outside of the school setting—informal settings.

Exclusion criteria

Study is published earlier than 2000.

Study describes STEM projects with elementary and university age students.

Limited description of the project/s being implemented.

Theoretical papers.

Review papers.

Papers not written in English.

Search strategy

Title, abstract and keywords were searched in ProQuest, ERIC, Scopus, Sage Journals and Web of Science databases using a search for terms agreed between the authors, these being: “integrated STEM” OR “integrated STEAM” OR “integrated STEMM” OR “interdisciplinary STEM (STEAM/STEMM)” OR “Science, Technology, Engineering and Mathematics” AND “project*” AND “secondary school” OR “high school” OR “middle school”. It was decided to limit the scope of the study to publications from January 2000 onwards, since the term STEM was coined in 2001.

Data screening and extraction

The data screening process is described in Fig.  1 . The search results ( N  = 221) were imported into an Excel spreadsheet and duplicates and conference proceedings were removed ( n  = 106). Each author then independently checked the titles and abstracts of the remaining articles ( n  = 115), excluding those studies that did not meet the inclusion criteria ( n  = 71). Where conflicts arose, the authors consulted and discussed whether to include or exclude the study.

PRISMA flowchart

In the second phase of screening, the authors individually examined the full text of studies ( n  = 44) and made decisions to include or exclude the studies based on the inclusion criteria. Where conflicts relating to decisions about exclusion/inclusion occurred, the authors met to resolve them.

Finally, authors extracted data from the remaining 35 studies, including publication date, country of the author and setting of the study, study design, data type collected, type of class (unidisciplinary or multidisciplinary) data was collected in, STEM fields integrated, whether integration is elaborated, a description of the scope of the project(s), instructional approach, cohort and research focus. One other author then checked the extracted data for accuracy. The extracted data were then summarised, and further thematic analysis was carried out where appropriate.

Data analysis

For most of the data extracted, analysis involved aggregating numbers of papers within each category. However, in the areas of domains of STEM integrated, instructional approaches, whether student context/interests are addressed, student autonomy and research foci, themes were identified within each area. For instance, within the research foci, the theme ‘development of students’ content knowledge’ arose as an important focus of research within these articles. In order to determine which domains were integrated within the project, the authors first searched for statements by the authors of the study that specifically identified domains such as Physics or Engineering. In some cases, when domains were not explicitly identified, the authors identified domains from the description of the project and the activities carried out which implied that certain domains were addressed. Data from each paper were placed under each of these themes as appropriate. When new themes arose during this initial analysis, these were added. Once saturation of themes was achieved and no more major themes arose (Bryman, 2012 ), the authors cross checked each other’s analysis of themes.

Research question 1: characteristics of studies

The 35 articles which met the inclusion criteria were published in 25 different journals (see Additional file 1 for a complete list). The majority of these journals had either a Science focus (e.g., Journal of Research in Science Teaching ) or at least two STEM areas (e.g ., Journal of Science Education & Technology ) (Fig.  2 ). No articles were found in journals which focused solely on Mathematics.

Subject area focus of publishing journals

There were no articles found before 2010, although the number of articles for each year has increased steadily since then (Fig.  3 ). The research described in the included articles was carried out in 8 different countries, 60% in the USA (Fig.  4 ). The majority of studies had a case study design or were quasi-experimental using pre/post tests (Fig.  5 ). In one article, the methodology was unclear. Thirteen studies focused on qualitative data, seven on quantitative data, while 14 collected both qualitative and quantitative data. Data types collected from the studies are described in Table 1 (as many studies utilised multiple data sources, the total number in Table 1 exceeds the sample size of 35). The cohorts who participated in iSTEM projects and who were the focus of the papers ranged from Grade 5 to Grade 12 students and included mixed age groups (Fig.  6 ). Some of the articles described participation in a range of different STEM projects for several grade levels.

Publication date of included articles

Countries where research was carried out

Reviewed articles study design

Cohort described in the reviewed studies

We also examined the types of classes in which the iSTEM projects were carried out. About half of the projects were implemented in unidisciplinary classes (i.e. classes that normally focus on one of the STEM subject areas). Of these, 14 were projects implemented as part of Science classes, two as part of Engineering classes and one as part of a Technology class. Eighteen of the studies implemented iSTEM projects in a multidisciplinary class where the focus was specifically on integrating several STEM areas.

In response to research question 1a, we firstly examined the STEM areas that were integrated within the project. Twenty-four of the studies elaborated which areas were integrated, while five gave limited descriptions of integration, and integration was not the focus for six studies. Areas of integration are listed in Table 2 . Science skills and content knowledge featured in all but two of the studies, while 31 studies included an Engineering focus. Twenty studies explicitly discussed integration of technology (e.g., through robotics, electronics, 3D printing, computer programming). Likewise, 20 of the studies indicated that mathematics was integrated into the project. Although all the studies claimed to be integrating a number of STEM areas, two studies only focused on one area (Table 2 ).

Within the Science domain, content knowledge from Physics, Chemistry, Biology and/or Earth Science (including Astronomy) was identified as a focus of the project (Table 3 ). Physics topics were the most commonly included Science topics in STEM projects. Note that some projects included more than one Science learning area.

To what extent do these projects reflect characteristics of effective STEM projects identified by Roehrig et al. ( 2021 ) ?

Firstly, we examined whether the engineering design process was central to projects. A wide variety of projects were described. These could be organised under four broad themes described in Table 4 : (i) design challenges which involved constructing prototypes (23 studies); (ii) hands-on learning activities (11 studies), such as making DNA models to understand genetically modified organisms (Wanoho et al., 2021 ); (iii) student-designed inquiry projects (3 studies), such as experiments aimed at explaining metal purification methods (Daman Huri & Karpudewan, 2019 ); and (iv) abstract problem solving (2 studies), such as brainstorming to solve problems related to space travel (Moreno et al., 2016 ). There were several articles that described more than one project, such as a study which looked at the integration of mathematics into a number of different STEM projects, including designing and making ballistic devices and understanding the properties of circles and theorems (Nathan et al., 2017 ). The 23 design challenges met the criteria for an engineering design process as they included at least one cycle of designing, evaluation and re-designing. However, the hands-on learning activities, where the teachers guided students through activities, gave limited opportunities for them to engage with an engineering design process.

In addition to examining the types of projects described, the instructional approaches identified by the authors in each paper could be categorised according to five key principles identified by Thibaut et al. ( 2018 ): integration of STEM content, problem-centred learning, inquiry-based learning, engineering design-based learning and cooperative learning. Instructional approaches are summarised in Table 5 . Some articles identified more than one instructional approach. The most common approach was an engineering design approach followed by problem-based/oriented learning. Both of these approaches were often combined with inquiry approaches and included cooperative learning. Engineering design was also incorporated into some of the problem-based learning approaches. However, two of the studies focused on presenting learning through a series of guided tasks, such as a NASA unit, “Thinking Like an Astronaut” (Moreno et al., 2016 ) rather than utilising an engineering design process. Additionally, the focus of one study was on preparing students for assessment. Five studies also specifically referenced a focus on Social Scientific Issues (SSI) (e.g., Wanoho et al., 2021 ). All of the studies claimed to integrate STEM content. However, six of the articles examined did not identify the instructional approach that they used.

Secondly, we examined each of the articles to understand whether the authors explicitly took into account the students’ context or interests in order to produce authentic problems. Of the design challenges, 12 consisted of a design brief which considered the students’ context, although student context or authenticity of the projects was not the main focus of these papers, and was often only mentioned in passing. The example which most clearly addressed the students’ context was one in which they designed an amphitheatre, within a budget, to meet the needs of the local community (Newman et al., 2015 ). The other design briefs focused on designing “things” without any explicit relationship to the students’ context (c.f., Gunckel & Tolbert, 2018 ) (e.g., a CO 2 powered model drag racer (Chien, 2017 ) or designing and building a balsa wood house to survive in a wind tunnel (Barrett et al., 2014 )).

Of the projects that focused on teaching a concept or concepts through hands-on activities, none of these considered the context of the students explicitly, although two projects addressed SSIs. Of the projects which focused on inquiry learning, two were context specific. However, students were given agency in designing experiments. Neither of the abstract problem-solving projects specifically engaged with student context.

One way of ensuring that projects are relevant to students is allowing for student design or choice of project topic. Fifteen of the 35 studies implemented projects that were externally designed, either by the researchers or by other experts such as NASA or Curriculum developers (e.g., Petrosino et al., 2016 ; Wilhelm et al., 2013 ). A further seven studies described teacher/researcher collaborative efforts to design the STEM project/s (e.g., De Meester et al., 2020 ). Teachers were instrumental in designing 11 of the projects (e.g., Wieselmann et al., 2021 ). Only two of the 35 studies gave students agency in choosing the problem to be studied (Kapon et al., 2021 ; Newman et al., 2015 ).

Of the 35 studies examined, only three mentioned that they made explicit links for students with possible future STEM careers as part of the project design. For instance, in the project described by Burrows et al. ( 2014 ), career connections were explicitly discussed in class and included in assessment questions. However, 18 studies did mention that one of the goals for introducing integrated STEM projects to students is that participation in these may increase engagement with future STEM careers and two of these studies examined whether students had changed their perspective about STEM careers as a result of doing these projects. However, neither of these papers mentioned whether this was an aspect that was explicitly addressed in lessons. In one study, including a “STEM Career Connections” component was considered, but the project designers chose not to because they did not think this was critical to the success of the project (Gale et al., 2020 ). The rest of the articles did not mention STEM careers at all.

Research question 2: foci of research

In response to research question 2 (What are the foci of research in empirical studies of integrated STEM projects? To what extent does research into iSTEM projects in classrooms investigate specific methods of integration of STEM domains?), the research questions for each study and the outcomes reported were examined. The research themes that were identified are displayed in Table 6 . It should be noted that some studies had multiple research foci.

It can be seen from the research foci presented in Table 6 that there is a very limited focus in the literature on describing the ways in which the STEM domains are practically integrated as iSTEM projects are enacted. The largest group of studies focused on the degree to which students had developed STEM-related content knowledge or skills as a result of participating in an iSTEM project. Many of these utilised a pre/post-test design, and in some cases compared results with a control/comparison group (e.g., Chen & Chang, 2018 ). Of the 12 studies which focused on the degree of content knowledge acquisition, 10 indicated that students had improved content knowledge, while two studies showed no significant learning had taken place. Four studies observed students actively applying STEM knowledge and skills to solve problems. Likewise, most studies noted that STEM skills, including twenty-first century skills, such as creativity and collaboration, improved as a result of participation in these projects. However, one study showed no noticeable improvement in skills.

Students’ experience of the lessons in terms of their motivation, self-efficacy and engagement was also a prominent theme, mostly evaluated through questionnaires, interviews, journals and video recordings (e.g., Chu et al., 2020 ). Seven studies observed high levels of engagement and motivation amongst students as they carried out STEM projects. Likewise, students’ attitudes towards STEM subjects and intentions to continue in the STEM pipeline were determined through questionnaires (e.g., Lou et al., 2011 ). Most of the studies examining changes in attitudes towards STEM indicated an improvement as a result of the STEM projects, although one study indicated no improvement had taken place.

The degree and types of participation of students while completing iSTEM projects, including gender differences, were analysed through classroom observations, videos and journal entries (e.g., Gardner & Tillotson, 2020 ; Wieselmann et al., 2020 ). For instance, Wieselmann et al. ( 2020 ) showed that boys and girls participate differently in STEM activities within small groups—the boys tending to be controlling and competitive and ignoring the girls’ contributions.

Teachers’ perceptions of the efficacy of the iSTEM intervention based on questionnaire and interview responses was the focus of five studies (e.g., Gardner & Tillotson, 2019 ). A number of challenges for implementing STEM projects were described by teachers, such as scheduling difficulties, difficulties using technology, and in making links to the curriculum (Stohlmann et al., 2011 ). Fidelity of implementation of specific iSTEM approaches by teachers was also analysed in two studies (e.g., Petrosino et al., 2016 ), and three studies considered the challenges that arise when integrating STEM domains (e.g., Stohlmann et al., 2011 ).

Surprisingly, the research questions in only five studies specifically targeted the enactment of STEM integration within an iSTEM project. For the most part, these studies carried out detailed analyses of audio/video recordings (e.g., multimodal discourse analysis (Nathan et al., 2017 )) of groups participating in STEM projects to understand teacher and student choices/actions/discussions. Mathis et al. ( 2018 ) presented a case narrative using quantitative content analysis to describe how students chose to use science and mathematics content through different engineering design phases while solving an engineering problem. Burrows et al. ( 2018 ) focused on engineering skills and identified numerous ways in which science, and to a lesser extent mathematics, was integrated while enacting these skills in an informal, community-based project. On the other hand, Dare et al. ( 2018 ) focused on iSTEM projects within the Science classroom. Teachers identified the time spent addressing the domains of STEM in each lesson. Teachers were then categorised as having low, moderate or high levels of STEM integration within their classes. They found that teachers are not always aware of how to meaningfully make explicit connections between domains, struggling to integrate mathematics and engineering into science instruction. In particular, engineering appeared to be an add-on, especially for those who had low levels of integration. Wieselmann et al. ( 2020 ), on the other hand, found that girls and boys, working in small groups, engaged with science or engineering focused lessons in different ways and may need practice and support in moving between these two discipline areas. In order to promote STEM integration, Nathan et al. ( 2017 ) found that cohesion between fields is best achieved when students themselves find their own ways to integrate fields as they apply ideas to more abstract principles.

This systematic literature review focuses on two areas that have not previously been investigated: what are the characteristics of projects being classified by researchers/teachers as integrated STEM projects; and to what extent are the specific ways in which integration of STEM domains investigated in the classrooms where they are enacted? In order to take a snapshot of the integrated STEM project landscape, we limited the review to empirical studies of iSTEM projects carried out with middle/high school students.

The authors of the 35 articles which met the inclusion criteria for this literature review identified a wide variety of projects that they considered exemplified integrated STEM. Making the engineering design process central to effective iSTEM projects is one of the recommendations made by Roehrig et al. ( 2021 ). Although engineering design was prominent amongst the instructional approaches identified by authors, other instructional approaches were also prominent, such as project based/oriented learning (Table 5 ). This is consistent with the findings of Mustafa et al. ( 2016 ) and Thibaut et al. ( 2018 ). However, several projects made no mention of engineering design, focusing on inquiry approaches or hands-on learning. In particular, the projects which presented hands-on learning activities left little or no room for design/re-design by students.

In terms of the types of projects students were engaging with, the authors identified four types (Table 4 ). Consistent with the engineering design approach used in many of the projects, 23 of the 35 studies gave students a design brief which allowed students to design some kind of physical model or prototype in order to solve a specific problem. These clearly fit the recommendations of Roehrig et al. ( 2021 ). However, although 23 of the projects identified by the authors as iSTEM did have an engineering design focus, surprisingly, 16 of the projects described did not specifically use the engineering design cycle. For instance, there were 11 projects which focused on teacher directed, hands-on activities to communicate content knowledge and skills to support students’ learning (Table 4 ) rather than employing the engineering design cycle to address a specific problem. Although these projects allowed students to construct models, for instance 2D and 3D models to explain lunar periodicity and phases (Wilhelm et al., 2013 ) or DNA models to understand genetically modified organisms (Wanoho et al., 2021 ), the engineering design process was not followed as students were given limited agency in the design process. This raises the question of whether these fit into the category of integrated STEM projects, especially if the characteristics of effective STEM projects identified by Roehrig et al. ( 2021 ) are considered. These findings indicate that researchers (and teachers) may not be operating under coherent definitions of what constitutes an integrated STEM project. We would argue, together with Roehrig et al. ( 2021 ), that projects that do not allow students to design their own solutions to problems, evaluate those designs and then re-design do not meet criteria for best practice in integrating STEM domains.

Another feature of effective iSTEM projects is that they enable students to engage with authentic problems which are relevant to their context. On the whole, the engineering design challenges (Table 4 ) gave students agency in the design/re-design process and the inquiry tasks also allowed students to design experiments. However, considering the recommendations of Roehrig et al. ( 2021 ) that effective iSTEM projects should be relevant to the students’ context, relate to their interests, and take into account diversity amongst students, it is concerning that only 11 of the studies specifically mentioned that problems relevant to the students’ contexts or interests were considered when designing the iSTEM project. For instance, one of the projects, that included a service-learning component, asked students to design an amphitheatre for a local park that the community and school could share (Newman et al., 2015 ). In addition, five projects explicitly consider socio-scientific issues, such as producing genetically modified organisms, in the project design (Wanoho et al., 2021 ). These projects may meet the criteria for projects that are authentic and relevant to students of Roehrig et al. ( 2021 ). However, it was unclear whether the SSIs addressed were of particular importance to the students carrying out the tasks. This begs the question about the extent to which students’ interests and concerns are being considered as iSTEM projects are designed.

In addition, 19 of the projects asked students to design and build artefacts that did not explicitly consider the student context, although these studies stressed the importance of providing real-world problems, that professionals may engage with, to increase student engagement. For instance, a competition to build a robotic arm was thought to be motivating for students, but no mention was made about how this device was relevant to students’ lives (Chu et al., 2020 ). It may not be sufficient to simply provide design problems that represent the types of problem-solving experiences that occur in industry but, as indicated by Brotman and Moore ( 2008 ), projects should address issues and concerns that are important to students in order to engage their interest.

This problem is compounded by the fact that, in almost all the studies, students were not given choice about the project that they would investigate. This limits the ability for the iSTEM experience to address diversity of interests and life experiences within the student cohort.

The two exceptions, where students were given choice, were a study in which the students developed the problem that they would investigate: understanding the difference in efficiency between a stationary and tracking solar panel (Kapon et al., 2021 ); and a service project where students identified problems within their communities to be solved (Newman et al., 2015 ).

In addition to our concerns over some of the instructional designs of projects being put forward as integrated STEM projects, the degree of integration within projects was not always evident. All of the studies claimed that STEM fields were being integrated within these projects (c.f., Thibaut et al., 2018 ). However, for some of these studies, integration of STEM was either not the focus or the ways in which these fields were integrated was not evident. When considering the degree of integration of Science, Technology, Engineering and Mathematics within each of the iSTEM projects in this study, it was evident that the Science and Engineering fields dominate within these projects (Table 2 ). This is consistent with Bybee’s ( 2010 ) description of the variety of definitions of STEM integration, ranging from Science and Engineering to all four domains. Thirteen of the 35 studies included at least all four domains. In addition, two studies included Social Science and English together with STEM. While 31 studies included the Engineering domain, the majority of these utilised an Engineering Design process rather than the development of engineering content knowledge. All but two of the studies included Science skills or knowledge, and technology was less likely to be identified as a domain that was integrated into the project (20 studies). This is consistent with studies which show that, even though digital technologies are frequently used in projects, the use of these technologies is often assumed rather than explicitly examined (Ellis et al., 2020 ). Mathematics was also not explicitly included in 15 of the 35 studies. It is possible that in other studies, even though connections with mathematics and technology are not explicitly addressed, they may be seen as tools of science or engineering (Baldinger et al., 2021 ).

The predominance of physics (21 studies) and astronomy (4 studies) as the Science content area addressed (Table 3 ) may be related to the number of design briefs that asked students to build prototypes. When limited connections are made between STEM projects and the students’ context and interests, and the value to students and the communities that they live in are not made explicit, and when many of these projects have a physics and engineering focus, stereotypes of these subjects may be further consolidated in students’ perceptions. Chemistry topics (8 studies), while less common, tended to be associated with inquiry tasks, such as designing experiments to understand the processes involved in mineral purification (Daman Huri & Karpudewan, 2019 ) or problem solving, for instance to stop corrosion on a metal bridge (Yüceler et al., 2020 ).

The inclusion of biology topics (11 studies) was also less common than for physics and were sometimes associated with teaching activities to understand biological concepts, such as body systems (Ntemngwa & Oliver, 2018 ) or design challenges based on biological examples (Gale et al., 2020 ). However, several of the projects that included biology identified SSIs in the local community, for which students designed solutions through an engineering design process (e.g., Newman et al., 2015 ). These projects met many of the characteristics of effective STEM projects identified by Roehrig et al. ( 2021 ). It may be that incorporating a biology topic into an engineering design cycle appropriate for middle and high school is more challenging to designers than inclusion of physics concepts.

Considering that one of the rationales for introducing iSTEM projects in middle/high school has been to increase students’ understanding of what careers in STEM entail, and hence increase students’ willingness to consider STEM careers in the future (Honey et al., 2014 ) our finding that almost no studies explicitly made connections between the iSTEM projects and possible careers, as suggested by Roehrig et al. ( 2021 ), is surprising. This may have been due to the research focus of the paper being unrelated to career choice. However, even in the cases where one of the research questions was to understand the influence of participation in iSTEM projects on students’ future choice of careers, no mention was made of how students’ were informed about connections between their learning in the project and possible careers.

Finally, in response to research question two, the main focus of research involving integrated STEM projects has been on learning outcomes, the degree to which students are learning specific STEM skills and content knowledge as a result of these projects (Table 6 ). In addition, affective aspects including change in attitudes to STEM, motivation and engagement throughout the STEM project were major foci of research. On the other hand, there were only five studies of exactly how students and teachers enact the integration of STEM domains throughout the project. The focus on learning outcomes related to iSTEM projects may be in an attempt to address the concerns raised by teachers about whether participation in STEM projects is in fact resulting in students learning the required curriculum content (Margot & Kettler, 2019 ). Likewise, iSTEM projects have been promoted as a way forward for increasing students engagement with and interest in pursuing STEM subjects later in school and at university (Honey et al., 2014 ), which may explain the number of studies which focus on increasing these affective aspects of learning.

The small number of studies which analyse the enactment of integrated STEM projects, however, is more surprising, particularly when teachers have indicated that they need more direction and support on how to effectively integrate learning areas (Arshad et al., 2021 ; Margot & Kettler, 2019 ). In addition, Roehrig et al. ( 2021 ) identify that making explicit connections between the content of the targeted disciplines is one of the essential factors for effective iSTEM projects. Of the five studies that investigated the enactment of integration, Burrows et al. ( 2018 ), Mathis et al. ( 2018 ) and Nathan et al. ( 2017 ) were the only studies which specifically addressed the ways in which domains were integrated. Burrows et al. ( 2018 ) briefly described how science content was integrated within engineering skills. Nathan et al. ( 2017 ), on the other hand, did not focus on integration of all domains but analysed the ways in which the teacher guided engagement with mathematics as students completed mechanical and electrical engineering design projects. Mathis et al. ( 2018 ) took the approach of focusing on each of the engineering design phases within an iSTEM project and analysing how students chose to use science and mathematics in each phase while solving the engineering challenge.

On the other hand, Dare et al. ( 2018 ) developed an innovative method for measuring the degree of integration within a series of lessons within a Science classroom by using a digital teaching log to identify the length of time spent addressing each domain in each lesson. This allowed the authors to identify teachers who had low, medium and high levels of integration. However, the study did not analyse how individual domains were integrated. Likewise, the study of Wieselmann et al. ( 2020 ) looked at frequency of certain performances, such as reasoning, encouraging and suggesting, within lessons that they identified as focusing on either Science or Engineering, rather than on how Science and Engineering were integrated. What is clear is that it is challenging to find ways in which to measure the degree of integration of domains and describe ways in which they are integrated. This finding suggests that there is much scope for classroom-based studies to probe effective strategies for integrating STEM domains.

Limitations and recommendations

It is possible that by including some of the search terms, such as projects, into the search engine criteria some integrated STEM studies may have been missed. The search also only included studies in English, which, perforce, limits the number of studies.

However, we offer the following recommendations for further research based on the scope of the studies that have been included. Firstly, further research is needed into the types of projects that would engage a greater diversity of students. For instance, a focus on designing “things” (Gunckel & Tolbert, 2018 ), untethered to students’ interests or concerns, may be one of the reasons why girls, in particular, are less motivated than boys to participate in integrated STEM projects (Brotman & Moore, 2008 ; Koul et al., 2021 ). Students’ beliefs that STEM careers do not address their diverse interests and concerns, including gendered interests, has been identified as one of the reasons that females are not choosing to continue to study subjects such as engineering, physics and computer science (Su et al., 2009 ). The higher enrolment of females in biology and, to a lesser extent, chemistry in preparation for caring careers, such as in the health sector, is indicative of gendered interests that are, on the whole, not being addressed within the context of iSTEM projects (Eccles & Wang, 2016 ). This is highlighted by the preponderance of physics-based projects presented in these studies (Table 3 ). Projects which only set one type of problem, such as building a ballistic device (Nathan et al., 2017 ) or CO2-powered model drag racers (Chien, 2017 ) may be of interest to some students, but do not take into account the diversity of students (Roehrig et al., 2021 ), and may, in fact, perpetuate stereotypical perceptions of engineering as the preserve of males (Master et al., 2016 ). We would suggest that, in order to address diverse interests within the student cohort, further research is needed into whether targeting biology within the Science domain of iSTEM projects increases the engagement and interest of girls in STEM.

Secondly, further research is needed regarding the effects of giving students more agency in choosing the problem that will be addressed through the STEM project.

Thirdly, the effects on attitudes towards STEM careers of making explicit links with possible careers as students carry out STEM projects is another area of research suggested by the results of this literature review.

Finally, the limited number of studies which investigate specific ways in which STEM domains are integrated suggests that further research is needed into methodologies for measuring the degree of integration and understanding best practice to effectively integrate STEM domains.

This systematic literature review addresses two main research questions: What are the characteristics of the projects described and to what extent do these projects reflect characteristics of effective STEM projects identified by Roehrig et al. ( 2021 ); and to what extent does research into iSTEM projects in classrooms investigate specific methods of integration of STEM domains?

It was evident that there were a wide variety of ways in which researchers and teachers understand STEM integration. While a majority of studies claimed to integrate, at least, Engineering and/or Science, only half of the studies presented students with an engineering design challenge which asked students to apply the engineering design cycle, as recommended by Roehrig et al. ( 2021 ). Mathematics and technology were less likely to be explicitly addressed within these projects. The specific ways in which integration of STEM domains occurred was only discussed in a small number of papers. The majority of studies focused on the effects of iSTEM projects on content and skill acquisition or on attitudes towards STEM. Only five studies examined the enactment of STEM integration within the classroom, and of these, only three explicitly examined processes for integrating domains, leaving much scope for further investigations in this area. This suggests that there is an extensive gap in our understanding of the practical ways in which STEM integration occurs and is made explicit to students (Roehrig et al., 2021 ). Another recommendation of Roehrig et al. ( 2021 ) was that projects should be relevant to students interests and context. Only 11 studies explicitly took into account the context of the students or their interests, and of these, some made assumptions about what the students may be interested in. Additionally, only two studies gave students choice in determining the engineering design question. This lack of student agency and relevance may provide a further barrier for engaging with iSTEM for some students. Further research is required to understand the importance of student agency in designing iSTEM projects and in finding ways to more authentically address student context and interest. In addition, a major rationale for introducing iSTEM projects into schools has been to raise student awareness of careers in STEM. The limited number of studies that explicitly made connections between the projects described and possible STEM careers, suggests that this is another area for further study.

Availability of data and materials

All data generated or analysed during this study are included in this published article and its supplementary information files.

Abbreviations

Integrated Science, Technology, Engineering and Mathematics

Project based learning

Project centred learning

Problem oriented project based learning

Socio-scientific issues

Science, Technology, Engineering, Mathematics and Medicine

Science, Technology Engineering, the Arts and Mathematics

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McLure, F.I., Tang, KS. & Williams, P.J. What do integrated STEM projects look like in middle school and high school classrooms? A systematic literature review of empirical studies of iSTEM projects. IJ STEM Ed 9 , 73 (2022). https://doi.org/10.1186/s40594-022-00390-8

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Integrated stem approaches and associated outcomes of k-12 student learning: a systematic review.

1. Introduction

2. conceptual framework, 2.1. integrated stem approaches, 2.2. k-12 student outcomes in integrated stem approaches, 2.3. research questions, 3. methodology, 3.1. method, 3.2. information sources and search strategy, 3.3. phases of study selection, 3.4. data extraction and synthesis, 4.1. data extraction for ecological sentences, 4.2. ecological sentence synthesis, 5. discussions, 5.1. synchronization-based integrated stem approach and associated outcomes of k-12 student learning, 5.2. thematic-based integrated stem approach and associated outcomes of k-12 student learning, 5.3. project-based integrated stem approach and associated outcomes of k-12 student learning, 5.4. cross-curricular-based integrated stem approach and associated outcomes of k-12 student learning, 5.5. specialized school-based integrated stem approach and associated outcomes of k-12 student learning, 5.6. community-focused integrated stem approach and associated outcomes of k-12 student learning, 6. conclusions, 6.1. recommendations for practice, 6.2. recommendations for further research, author contributions, data availability statement, conflicts of interest.

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Le, H.C.; Nguyen, V.H.; Nguyen, T.L. Integrated STEM Approaches and Associated Outcomes of K-12 Student Learning: A Systematic Review. Educ. Sci. 2023 , 13 , 297. https://doi.org/10.3390/educsci13030297

Le HC, Nguyen VH, Nguyen TL. Integrated STEM Approaches and Associated Outcomes of K-12 Student Learning: A Systematic Review. Education Sciences . 2023; 13(3):297. https://doi.org/10.3390/educsci13030297

Le, Hong Chung, Van Hanh Nguyen, and Tien Long Nguyen. 2023. "Integrated STEM Approaches and Associated Outcomes of K-12 Student Learning: A Systematic Review" Education Sciences 13, no. 3: 297. https://doi.org/10.3390/educsci13030297

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• DOI: 10.32890/MJLI2019.16.1.7319
• Corpus ID: 203699223

Enhancing Science Achievement Utilising an Integrated STEM Approach

• A. A. Yaki , R. M. Saat , +1 author Hutkemri Zulnaidi
• Published in Malaysian journal of learning… 2 June 2019
• Engineering, Education

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• Review article
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• Published: 31 July 2019

A review of the effect of integrated STEM or STEAM (science, technology, engineering, arts, and mathematics) education in South Korea

• Nam-Hwa Kang   ORCID: orcid.org/0000-0002-0572-0002 1  

Asia-Pacific Science Education volume  5 , Article number:  6 ( 2019 ) Cite this article

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Integrated STEAM education in South Korea is an approach to preparing a quality STEM workforce and literate citizens for highly technology-based society. Through a literature review, this study examined the STEAM education initiative in South Korea and investigated its effects on learning and teaching. Studies in South Korea found that teacher professional development courses increased teachers’ recognition of the initiative as well as their confidence in teaching STEAM. Teacher interviews showed that coaching in classroom practices within teachers’ professional development was helpful. Although studies reported that many science teachers adopted STEAM in science teaching, there was a lack of research on how teachers taught STEAM lessons, let alone the connections between teachers’ perceptions of STEAM and their classroom practices. As for STEAM effects on student learning, a number of meta-analyses showed that students’ experiences with STEAM were effective in both cognitive and affective learning. The effect was higher in affective domains. Interviews with college students who had STEAM experiences in grade school showed that the effects could be long-term. The meta-analysis studies failed to identify significant mediating factors, which required further in-depth research on how contextual variables function in student learning. This paper provides a glimpse of what can be achieved through STEAM efforts, and what should be further researched for better theory and practice.

Introduction

Understanding science and mathematics knowledge and practices, as well as technological and engineering practices, has become a priority for national education programs across the world (Kelley & Knowles, 2016 ). The United States Next Generation Science Standards (NGSS) includes engineering design and practices as primary elements of science education (NGSS Lead States, 2013 ). The UK has also put forth educational policy agenda promoting science, technology, engineering, and mathematics (STEM) integration both in and out of schools (STEM Learning, 2018 ). Germany also created a national STEM forum to promote STEM education for all levels of education, formal and informal (Nationales MINT (STEM) Forum, 2014 ). Similarly, the Ministry of Education in South Korea issued a nation-wide policy agenda in 2011, which included the promotion of integrating science, technology, engineering, arts, and mathematics education (STEAM hereafter). All these efforts in developed countries to reform STEM education are to meet the challenges of the twenty-first century which require strengthening the workforce in STEM areas to address global issues and STEM literacy for a new era (Kelley & Knowles, 2016 ).

Integrated STEAM education in South Korea is an approach to preparing a quality STEM workforce and literate citizens for highly technology-based society by integrating science, technology, engineering, arts and mathematics in education. It is named differently from STEM due to its emphasis on arts (fine arts, language arts, liberal arts, and physical arts) as an important component of integration. While the STEAM reform movement is in alignment with STEM reform in other countries, its added component, i.e., arts, was inspired by the concurrent social discourse on education for creativity and a well-rounded citizen in the twenty-first century (Baik et al., 2012 ). Also, the national concern for students’ low confidence and interest in learning science regardless of high achievement (Organization for Economic Co-operation and Development, 2013 ) factored in promoting the integration of arts with STEM education for affective goals. A similar idea now can be found elsewhere (e.g., Henriksen, 2014 ; The STEAM journal, 2013 ). Since then, the South Korean government has allocated a substantial educational budget for promoting STEAM through various routes. With the idea of creating innovative thinkers by integrating ideas from STEAM fields, i.e., all subjects in schools, the term, ‘convergence education’ has been coined and used to refer to the integrated STEAM education initiative. Convergence refers to creating new ideas or products formed by interdisciplinary or multidisciplinary thinking. Thus, the main goal of integrated STEAM education is to develop ‘talents in convergence’.

This study examined STEAM education initiatives in South Korea and investigated their effects on learning and teaching. In doing so, we gain insight into future directions of STEAM or STEM education research and practices.

Integrated STEM education in the literature

Because South Korean STEAM education is informed by and aligned with STEM initiatives in other countries, a review of STEM education in international literature would provide a context for understanding STEAM education in South Korea. Based on a growing need for literate citizens in a highly technological society, and an increasing national need for a STEM workforce, a recent curricular reform movement calls for an integrated approach to teaching science and mathematics in which technology and engineering provide methods and contexts of learning (National Academy of Engineering and National Research Council, 2014 ). For example, Bybee ( 2010 ) calls for quality science education that includes technology and engineering:

A true STEM education should increase students’ understanding of how things work and improve their use of technologies. STEM education should also introduce more engineering during precollege education. Engineering is directly involved in problem solving and innovation, two themes with high priorities on every nation’s agenda…. the creation of high-quality, integrated instruction and materials, as well as the placement of problems associated with grand challenges of society at the center of study. (p. 996).

Whereas there have been initiatives for integrated STEM education in a number of developed countries including South Korea, the mechanisms of integration for STEM disciplines and instructional approaches are largely undertheorized (National Academy of Engineering and National Research Council, 2014 ). Given the limited research, instructional design for integrated STEM can be informed by the literature on problem-based learning (PBL). In a number of reviews on integrated STEM programs, researchers found that integrated STEM programs commonly utilize real-world complex problems as instructional contexts in which students apply knowledge and practices from multiple disciplines (Banks & Barlex, 2014 ; Kelley & Knowles, 2016 ; Lynn, Moore, Johnson, & Roehrig, 2016 ; National Academy of Engineering and National Research Council, 2014 ). PBL is a well-researched and widely accepted student-centered instructional approach in which students are given an ill-structured real-world problem to investigate viable solutions for by applying knowledge and skills from various sources (Hmelo-Silver, 2004 ; Savery, 2006 ). PBL helps students develop knowledge involved in problem solving and cognitive skills such as critical and analytical thinking. Additional characteristics of PBL such as working in collaborative groups and engaging in self-directed learning lead to learning outcomes such as communication competency and motivation to learn. This approach was succinctly summarized in Hmelo-Silver ( 2004 ).

In PBL, student learning centers on a complex problem that does not have a single correct answer. Students work in collaborative groups to identify what they need to learn in order to solve a problem. They engage in self-directed learning (SDL) and then apply their new knowledge to the problem and reflect on what they learned and the effectiveness of the strategies employed.… The goals of PBL include helping students develop 1) flexible knowledge, 2) effective problem-solving skills, 3) SDL skills, 4) effective collaboration skills, and 5) intrinsic motivation. (p.235).

Drawing on this literature, integrated STEM education programs could anticipate similar learning processes and outcomes. PBL is also considered to be critical for integrated STEM education because unstructured problem solving is considered one of the key twenty-first century competencies (Organization for Economic Co-operation and Development, 2016 ).

PBL in science education typically involves scientific practices, but PBL of integrated STEM education programs have an additional unique feature originating from engineering and technology education. In many integrated STEM education programs design practices in technology and engineering is increasingly emphasized (Fortus, Dershimer, Krajcik, Marx, & Mamlok-Naaman, 2004 ; Kelley & Knowles, 2016 ; NGSS Lead States, 2013 ). These are also influenced by art education that addresses design processes reflecting the practices of architects, graphic designers, industrial designers, landscape architects, etc. (Davis, 1998 ; Sanders, 2012 ). Many integrated STEM programs include problems that require design in which students create a prototype or a model as a solution for a given problem. In these programs, a set of design practices guide students’ problem solving, which is sometimes called design-based activity (e.g., Fortus et al., 2004 ). Table  1 compares design processes in the area of technology (International Technology Education Association, 2007 ), engineering (National Research Council, 2010 ), and art education (Davis, 1998 ). The design activities in different areas have common processes, from problem identification to the evaluation of multiple solutions because they are all problem-based activities. Furthermore, design problems are all real-world problems that require considerations of constraints, optimization and trade off in design process. Also important is, “concern for users or audiences, human factors,” (Davis, 1998 , p. 8) which requires empathy, i.e., being sensitive to other people’s needs and feelings. In addition, all the design processes are described as teamwork in which collaboration and communication are emphasized (Davis, 1998 ; National Research Council, 2010 ).

Design activities provide a context for STEM integration in which learning and application of science and mathematics concepts and practices occur as students work in teams to find solutions for real world problems (Fortus et al., 2004 ; Kelley & Knowles, 2016 ).

Studies about STEM programs have found that explicit scaffolding for integration is essential (Fortus et al., 2004 ). For example, during simple mechanical device design activities, Crismond ( 2001 ) found that inexperienced high school students made few connections between designs and science ideas and rarely applied science ideas learned in one activity to another. On the other hand, experts like university engineering design instructors spontaneously made connections to concepts and utilized concepts in making key design decisions. Similarly, Berland and Steingut ( 2016 ) also found that high school students engaged in engineering design tend to focus on completing design tasks without consistent effort to understanding the underlying concepts from mathematics or science. They found that students rarely saw the value of understanding the concepts behind designs. These studies suggest that integrated STEM learning environments should help students investigate relevant concepts and understand how concepts support design goals. In order to avoid students’ framing of design activities as mindless trial-and-error exercises (Scherr & Hammer, 2009 ), conceptual goals must be made explicit to help students recognize the value of conceptual goals as well as technical goals. In doing so, integrated STEM education can be effectively materialized in the classroom.

Whereas there has been some discussion on similarities and differences between scientific and engineering practices (Fortus et al., 2004 ; National Academy of Engineering and National Research Council, 2014 ; NGSS Lead States, 2013 ) there has been a dearth of research on scientific practices as learning outcomes of integrated STEM programs. In order to make STEM integration meaningful for effective coordination of practices from different disciplines, as well as conceptual learning, further research is needed.

Contexts of integrated STEAM in South Korea

A unique feature of integration for STEM in South Korea is an integration of STEM with arts that encompasses fine arts, language arts, liberal arts, and physical arts. STEAM programs in South Korea therefore call for all school subjects to be involved, which can provide rich learning opportunities. Whereas integrated STEAM initiatives in Korea include education both in and out of school (Jho, Hong, & Song, 2016 ), most STEAM programs in South Korea focus on programs for school education. Thus, this paper addresses STEAM initiatives for elementary and secondary school programs.

South Korea adopts a national curriculum that covers grades 1 to 12 over 6 years of primary school, and 3 years of lower and 3 years of upper secondary school. The curriculum for grades 1 and 2 is thematically integrated, whereas the curriculum for grades 3 to 12 includes subjects such as science, technology, mathematics, language arts, social studies, and fine arts. Up to lower secondary school, a certain number of class hours across all subjects is required for all students as part of compulsory education. School subjects are more divided in upper secondary school curriculum. For example, science is divided into physics I and physics II, chemistry I and chemistry II, life science I and life science II, earth science I and earth science II. In upper secondary school, students select subjects to specialize in, while a minimum number of credits are required in different subject areas for a diploma.

Although Korean science curriculum addresses STS (science, technology, and society) issues in secondary school sciences, technology is offered as a separate subject required for all upper primary and lower secondary school students. The technology curriculum has evolved a great deal over the past half century. Initially, it addressed building artifacts from wood, metal, electric components and other materials. Since the ‘90s, engineering and computer use has been included in its content. In a recent revision of the national curriculum, ICT (information and communications technology) content is separated from the technology curriculum, and is required of all secondary school students (Korea Ministry of Education, 2015 ). Thus, the individual disciplines of STEAM are all required for every secondary school student.

Consistent with the discipline-based curriculum, secondary teachers in South Korea are prepared to teach a specific discipline that they majored in their undergraduate degree program, whereas elementary teachers are prepared to teach all subjects. Science teachers, for example, are prepared in physics, chemistry, biology, or earth science teacher education programs. Similarly, there are separate technology and ICT teacher education programs. There are also secondary teacher education programs at the master’s degree level for those who want to teach the discipline they studied for their bachelor’s degrees.

The discipline-based school curriculum has changed a little by including programs for “creative experience” (CE) as required credits. These programs are designed by teachers, and provide career exploration and club activities in which interdisciplinary knowledge and skills as well as affective outcomes are expected. Thus, some teachers design CE programs for STEAM education (Korea Foundation for the Advancement and Creativity, 2019 ). In terms of required course hours, the current 2015 Revised Korean National Curriculum requires 9~13% of total class hours to be CE across elementary and secondary schools (Korea Ministry of Education, 2015 ).

STEAM reform initiative in South Korea

Since the late ‘90s, South Korea has observed a decrease in STEM career aspiration among young age groups, and student interest in learning science has remained low (Martin, Mullis, Foy, & Hooper, 2016 ). In high schools, students select sciences much less often than the humanities or social studies, and universities are compelled to accept less qualified applicants for STEM majors (Jang & Kim, 2002 ). This has led to national concerns for global economic competitiveness.

STEAM reform initiatives have arisen as a result, and their impact has been researched. Significant national funding for research and development for STEAM has been devoted to two major areas: teacher professional development, and STEAM curricular program development. The funding from the Ministry of Education is provided to a government agency called the Korea Foundation for the Advancement and Creativity (KOFAC) that organized programs for STEAM initiatives. Jho et al. ( 2016 ) described the entire structure of the initiative in their paper, and in this section, the main programs for STEAM initiatives are briefly reviewed.

Teacher capacity in STEAM

Since the beginning of the governmental STEAM initiative in 2011, KOFAC has provided teacher professional development for STEAM to both elementary and secondary school teachers through two programs: formal teacher professional development programs (STEAM PD hereafter), and a STEAM research group of teachers (STEAM-RGT hereafter) support program. The STEAM PD provides formal courses to teachers of all levels and subjects for free of charge. Whereas the number of course hours has changed since 2011, PD has kept its format of three levels: online courses as an introductory level, a basic blended program, and an advanced blended program. The online course consists of 15 h and is offered in three types: one for elementary, one for lower secondary and the last for upper secondary school teachers. The courses are offered to teachers across all subjects who are interested in learning about the initiative. The introductory online course provides an overview of STEAM for teachers to understand the policy agenda, its basic goals, and orientation toward approaches to teaching integrated STEAM lessons. Almost half of the course introduces examples of STEAM lessons and demonstrations, which distinguish courses for teachers at different school levels. This introductory online course is available at any time, and teachers get one credit for taking the 15-h online course. Footnote 1

The basic blended program is designed for any teachers who want to know more about STEAM. This program used to be 60 h-long, but is now 45 h-long, awarding 3 PD credits. The basic program has two major elements: to get teachers familiar with cutting-edge science and technology by observing science and engineering labs and to expose them to STEAM programs developed for schools. The purpose is to get teachers ready for teaching STEAM lessons. In principle, the program addresses competency for teaching STEAM in the classroom including subject matter knowledge, pedagogical content knowledge (PCK) for integrated content, teaching strategies, and teachers’ own STEAM literacy development (Korea Foundation for the Advancement and Creativity, 2019 ). This program includes three, full day, face-to-face workshops in the summer in which participants visit cutting-edge STEM research labs, take lectures from scientists, engineers, and scholars in the arts and humanities whose work involves interdisciplinary research, get introduced to existing STEAM programs for schools, and develop their own STEAM lesson plans as a team. During the semester following the summer workshop, teachers are required to teach at least 15 STEAM lessons with online consulting for implementation. Toward the end of the semester, teachers are provided with an opportunity to share the results of their STEAM lesson implementation with other participants during a half-day sharing session. Thus, the basic program lasts for about four months in total. Annually, about 300 (150 elementary and 150 secondary) teachers are recruited for the program.

The advanced PD program is open to any STEM teachers or teachers who have finished the basic program. This advanced course used to be 60 h-long, but is now 52 h-long, awarding 3.5 PD credits. The main goal for teachers is to develop competency in creating STEAM contents for teaching (Korea Foundation for the Advancement and Creativity, 2019 ). Upon completion, teachers are expected to be leaders who can lead STEAM professional development in their schools or local educational agencies. The program consists of a four-day workshop in the summer, followed by mandatory implementation of STEAM lessons in the fall. Annually, about 300 (150 elementary and 150 secondary) teachers are recruited for the course. The formats of the basic and advanced programs are very similar, but the basic program focuses on using ready-made STEAM programs, while the advanced program focuses on the creation of new STEAM lesson materials.

The STEAM-RGT support program exists to support teachers’ self-guided professional development by facilitating teacher groups’ work as learning communities (Jho et al., 2016 ). KOFAC calls for STEAM-RGT applications and provides those selected with financial support for attending meetings, and for materials to implement STEAM lessons with. These STEAM-RGTs are responsible for creating STEAM lesson plans, implementing them, and reporting their effects on student learning. In 2011, the first year of the STEAM initiative, 47 STEAM-RGTs from 16 STEAM schools (schools that implement STEAM programs) were funded. In the following year and thereafter, 180 STEAM-RGTs have been selected for funding annually. Half of the groups are composed of elementary teachers, and the other half are composed of secondary teachers. In 2018, the number of STEAM-RGTs funded increased to 230 groups, indicating a rise in governmental support for STEAM PD (Korea Foundation for the Advancement and Creativity, 2019 ). Although the initial STEAM-RGTs were formed within a school, many STEAM-RGTs are now cross-school communities.

Teachers of STEAM RGTs are provided with an annual opportunity to showcase their teaching in the form of a conference. In addition to financial support, professional development workshops and mentoring have been instituted since 2015 to support STEAM-RGTs. Jho et al. ( 2016 ) reports a case study of STEAM-RGTs.

Teachers apply every year for STEAM-RGT support funding, and typically half of the teachers applying are new. It is very common to find teachers who have taken three formal STEAM PDs applying for STEAM-RGT funding, indicating that STEAM PD motivates teachers to further their STEAM competency.

STEAM curricular program development

Since 2012, STEAM teaching and learning materials development projects are funded to provide teachers with evidence-based effective STEAM curricular materials. Projects are funded in four areas: thematically integrated STEAM, technology-use STEAM, science and art integrated STEAM, and future career related STEAM. The topics for thematically integrated STEAM programs have been cutting-edge STEM topics such as autonomous vehicles, big data, artificial intelligence, and human brain research. In the area of technology-use STEAM program development, researchers utilized smartphone applications, drones, Arduino and other recent technologies as major technological tools for student learning. Science and art integrated STEAM programs center on music and art curriculum. Future career related STEAM programs introduce recent STEM development such as blockchain technology, data mining, and intelligent farming in relation to a variety of industrial field and jobs.

The number of projects funded has varied annually from 10 to 20 projects per each area. Each project is expected to develop curricular materials for at least 24 class periods in elementary or secondary schools. As a Research and Development project, materials should be tested in schools and their effects should be measured and reported. Also, a common assessment of student interest and teacher satisfaction across all projects is administered to evaluate overall effects. As of June 2019, a total of 666 program modules developed and tested are available at the STEAM homepage hosted by KOFAC (Korea Foundation for the Advancement and Creativity, 2019 ).

Commissioned by KOFAC, a framework for the STEAM program was developed (Baik et al., 2012 ) and has been widely used. The framework integrates science learning with design under the motto of ‘emotional touch with creative design’ (Korea Foundation for the Advancement and Creativity, 2019 ). The framework utilizes PBL and emphasizes developing talents in integrated STEAM thinking by increasing interest in science and technology, connecting lessons to everyday experience, and developing creative thinking skills. Also emphasized are three features of STEAM lessons including use of personally or socially relevant problems, application of creative design for problem solving and emotional experiences such as interest, a sense of achievement, intellectual satisfaction, passion, confidence, fun, and so on. An example of STEAM curricular materials development project can be found in Kim and Chae ( 2016 ). In the study, the research team developed a series of lesson materials (lesson plans, worksheets, and teacher guides) whose goals were to help students understand how a Korean wind instrument works, design their own wind instrument, and perform for an audience. The curricular content included parts of STEAM disciplines across 10 lessons. Students were expected to understand the science of sound through technological measurement, and then engineering the design of an instrument and performing on it were expected to provide emotional experience. This curricular program is typical of science and art integrated STEAM curricular materials development projects that integrate components of the national curriculum of all relevant subjects. Thus, the materials could be easily utilized in schools. Other types of STEAM curricular materials developed were similar in terms of using the PBL centered design framework.

In late 2015 and early 2016, following five years of the initiative, a nationwide survey was administered about the degree to which STEAM programs are provided in schools (Korea Foundation for the Advancement and Creativity, 2019 ). Out of 11,526 elementary and secondary schools in nationwide, 56% responded to the survey, which showed that 55% of elementary schools, 48% of middle schools, and 32% of high schools offered STEAM lessons to their students. Most of these schools offered STEAM lessons mainly through regular classes (67% of responses) once or twice a month (60% of responses). This appeared to be a very fast diffusion over five years. As a reason for offering STEAM lessons, teachers’ own initiative was most frequently mentioned (28% of responses), while support from the school district came second (22% of responses). This showed that the STEAM initiative has successfully onboarded teachers, and its implementation took both top down and bottom up approaches.

• STEAM effects

Presented in this section are reviews of studies on the effects of the STEAM initiative in three aspects: teacher development in STEAM, meta-analysis of STEAM impact on student learning, and students’ perceptions of STEAM lessons.

Teachers in STEAM

Since the inception of the STEAM reform initiative, teacher capacity building has been emphasized. Research on teachers for STEAM were identified using “teachers” (in Korean) and “STEAM” as search words in two major academic paper search engines in Korea (Korean Studies Information Service System [KISS] and Research Information Sharing Service [RISS]). From the search results, papers whose titles had STEAM and teachers together were included in the review, but non-empirical studies were eliminated. Furthermore, studies about early childhood or preservice teachers were excluded for review because they were not yet the main target of the STEAM initiative. Thus as of 2017, a total of 28 empirical studies about teachers in STEAM reform initiatives were identified. These studies examined teacher perceptions of STEAM and/or teachers’ capacity of implementing STEAM in schools.

Teacher perceptions

Teacher perceptions of STEAM have been a significant topic of research as teachers are a critical factor in instructional reform (Wallace & Kang, 2004 ). In the beginning of the STEAM initiative, a study showed that only 10% of elementary teachers in a large school district indicated that they were aware of the STEAM initiative (Shin & Han, 2011 ). A nationwide survey of secondary teachers also demonstrated that 93% of teachers either only knew the name, or did not know what the initiative was about at all (Lee et al., 2012 ). This has changed a great deal over the years to the extent that 28% of elementary or secondary teachers initiate offering STEAM lessons in schools (Korea Foundation for the Advancement and Creativity, 2019 ).

Successful implementation of reform initiative requires more than materials, resources, or professional development for teachers. Teachers would respond to STEAM with unique attitudes and beliefs, and thus each teacher would implement STEAM differently. In order to identify necessary supports for various teachers’ needs, a diagnostic model called the Concerns-Based Adoption Model (CBAM) has been used as a tool (American Institutes for Research, 2018 ). In the model, teachers’ concerns are examined in seven stages of concern including no concern, informational concern, personal concern, managerial concern, consequential concern, collaboration concern, and refocusing concern. Among these stages, consequential concern (concern about the effect on students), collaboration concern (interest in collaborating with colleagues), refocusing concern (interest in adaptation for better effect) are high level concerns that represent proactive attitudes toward implementing the reform initiative. In other words, teachers with high levels of concern for these three types are willing to adopt and/or adapt the reform initiative.

Six studies used parts of, or a complete CBAM survey, to identify teachers’ perceptions of STEAM. Two of the studies examined elementary teachers’ concerns for STEAM in which one of them surveyed teachers in STEAM schools and the others surveyed teachers in normal schools (Chae & Noh, 2014 ; Lee, 2014a ). Studies showed that more teachers in STEAM schools demonstrated higher level concerns. For example, the degree of refocusing concern in STEAM schools was on an average 84 on the scale, whereas the average degree in normal schools was 58. Similar trends were also found in other studies that examined both elementary and secondary school teachers. Teachers in STEAM schools or teachers of STEAM-RGT had more high-level concerns. Taken together, the more teachers were involved in STEAM, the higher level of concerns are prevalent among teachers.

A study compared perceptions of teachers who had been leaders of the STEAM initiative in their schools and those who never experienced STEAM (Moon, 2015 ). In the study, teachers who were leaders of STEAM demonstrated high scores on consequential, collaboration and refocusing concerns. The other group scored highly on managerial concern. Interviews with these teachers confirmed the survey results, and also revealed different perceptions about STEAM between the two groups of teachers. Through experiences, STEAM leaders tended to view STEAM lessons as flexible, so that they could be adapted to local needs. They were more confident in its effect on student learning than those who didn’t teach STEAM. The other group, however, tended to view STEAM as a highly structured teaching model and as a reform fad that would soon to be replaced with another fad. The difference between the two groups, teachers who taught STEAM, and those who did not teach STEAM, was also found in a study about collective teacher efficacy (Lee, 2014b ). Whereas teachers’ collective teacher efficacy (efficacy belief about teachers in one’s own school) was not related to teachers’ years of teaching, teachers who taught STEAM lessons demonstrated significantly higher collective teacher efficacy than those who did not. Again, the more teachers were involved in STEAM the more proactive and confident they were in STEAM.

A KOFAC commissioned survey report on teachers’ perceptions of the STEAM lessons provided an overall view of teachers’ own STEAM teaching (Kang et al., 2018 ). Using the same survey questions responses from 1,815 elementary and secondary teachers were collected between 2014 and 2017. Eight survey items in the 5-scale Likert asked about the innovativeness of STEAM lessons, their relation to cutting-edge STEM, connection to everyday life, and ability to stimulate student interest in learning STEM. The average response was positive, ranging from 4.1 to 4.3 each year. Overall, teachers who implemented STEAM seemed to perceive that their teaching met the STEAM reform intention.

Taken together, these studies showed that in a relatively short period of time, the STEAM initiative became widely known among teachers, and that a rather large proportion of teachers implemented STEAM in schools. Studies also found that the teachers who taught STEAM had positive perceptions of STEAM, meeting the goals of the STEAM initiative.

Teacher implementation capacity

When it comes to implementation, teaching capacity, and other challenges teachers perceive matter the most. Studies about teacher professional development have supposedly addressed how much capacity teachers were able to build through STEAM PD. For example, Han, Hwang, and Yoo ( 2016 ) examined who was participating in STEAM PD and the effect of STEAM PD since the inception of STEAM reform. Over three years, 696 teachers participated in PD at the advanced level. Thirty-eight percent were elementary teachers, and 65% had more than 10 years of experience in teaching. Also, 78% of the secondary teachers were teaching science. Thus, it seems that more experienced teachers and science teachers tended to pay attention to the initiative. Using surveys and reflection papers of 696 participants, the study found that professional development programs were effective in improving teachers’ STEAM teaching competency thanks to built-in implementation and reflection elements. Participant teachers reported that a cycle of STEAM lesson planning during face-to-face meetings over the summer, implementation of the lessons in the subsequent semester, and sharing of implementation results were useful for them in building confidence and improving their STEAM teaching capacity (Han et al., 2016 ).

Park, Byun, and Sim ( 2016 ) examined how teachers in STEAM schools implement STEAM lessons in regards to frequency and curriculum organizations. Responses from a total of 705 teachers from 252 elementary and secondary STEAM schools were analyzed. The results showed that about 70% of teachers taught STEAM lessons either an hour every week or every other week. Given the study was conducted at the end of the fifth year of the initiative, the results showed a very successful rate of teacher adoption of STEAM in schools.

The study also showed that elementary and lower secondary teachers (66% of elementary and 74% of lower secondary school teachers) provided STEAM mostly as a part of regular curriculum, but only 50% of upper secondary school teachers taught STEAM in regular classes. Because the Korean curriculum is discipline-based, it is important to know whether STEAM lessons are taught during classes of various subjects to meet the goal of interdisciplinary or convergence education. The results showed that 75% of elementary teachers taught STEAM in science class, while 25% of lower secondary school teachers and 50% of upper secondary school teachers taught STEAM in science class. These results should be carefully interpreted. In general, STEAM lessons were associated with science more than any other subjects. Given the general trend, it is plausible that elementary teachers who teach all subjects tended to consider science as the main content of STEAM lessons, while lower secondary school teachers treated it as being multidisciplinary, encouraging teachers across multiple subjects to teach STEAM lessons. With regard to upper secondary schools, only half of the teachers taught STEAM lessons in regular classes, while science was the dominant subject to be used. On the other hand, special classes for STEAM could be interdisciplinary in its nature. Further research on patterns of teacher implementation is necessary.

To find out necessary support for teachers’ implementation of STEAM, Park et al. ( 2016 ) also surveyed what teachers felt challenging in teaching STEAM lessons, and whether the perceived challenges differ according to teachers’ years of teaching. They found that there was no significant difference in teachers’ perceived challenges. All the teachers in the study felt they needed more time to prepare STEAM lessons, though worried about increasing their workloads due to STEAM.

More detailed challenges were revealed in another study. J.-M. Lee and Shin ( 2014 ) interviewed 25 elementary teachers about their perceived challenges in teaching STEAM lessons. The common difficulties cited included curriculum reorganization and constructing STEAM lesson materials, guiding students’ group activities, conducting proper student assessment, and a conservative school climate. Addressing these challenges experienced by teachers would be critical for successful STEAM in schools.

Connections between perceptions and implementations

There has been little research connecting teacher perceptions and implementations. To gain insight into potential connections, the results of three research studies that reported interviews about teachers’ perceptions and implementations (Kang et al., 2017 ; Kang & Kim, 2015 ; Kang, Lee, Rho, & Yoo, 2018 ) were reanalyzed for this review. Among the total of 25 teachers interviewed in those reports, 2 secondary teachers had no experience teaching STEAM lessons, 4 of the teachers taught STEAM but stopped teaching STEAM lessons (drop-outs), and the other 19 teachers were teaching STEAM at the time of the interview. Among the 25 teachers, 10 were teaching in elementary schools, 9 were teaching science, 2 were teaching mathematics, 1 was teaching technology, and 3 were teaching social studies, English and art respectively.

All the teachers interviewed perceived STEAM as a way to integrate two or more disciplines in using everyday connections. Also, they believed that STEAM lessons could be a way to stimulate student interest in science learning and school learning in general. However, when the teachers had to elaborate on how to teach STEAM, their ideas diverged. To the two secondary teachers who never taught STEAM, STEAM was a way to extend students’ science learning to be more well-rounded in terms of content, while student problem solving or design element of STEAM was not essential. Thus, integration became, “addition of extra content to the existing science content to be covered” (Kang & Kim, 2015 ). A similar view was also demonstrated by most of the elementary teachers. Although they were teaching all subjects and thus could have easily integrated subjects into STEAM lessons, most of the elementary teachers viewed STEAM lessons as science with some ‘spice’ of relevant content from different subjects. An issue salient to the elementary teachers was to, “make sure the content to be integrated is in the curriculum for the grade” (Kang et al., 2017 ). The teachers were concerned about teaching at their students’ levels and constrained the content of STEAM lessons to the curriculum for the grade of their teaching. This result corroborated survey results by Park et al. ( 2016 ) in which most elementary teachers stated they taught STEAM in science classes. To these teachers, the main purpose of integrated STEAM was to make science intriguing and engaging.

On the other hand, most secondary teachers expressed that they felt a need to schedule a special class for STEAM for a number of reasons. They viewed STEAM as requiring, “a special way of teaching” that incorporated problem- or project-based approaches with multidisciplinary content. Thus, these teachers preferred club activities or special classes provided afterschool where students could be engaged in STEAM activities for an extended time. This made the subject-specific school schedule irrelevant. Again, this result corroborated survey results by Park et al. ( 2016 ) that showed half of upper secondary school teachers taught STEAM in special classes. To these teachers, the discipline-based curriculum was a serious barrier to integrated STEAM, and they avoided the barrier by using non-regular class time.

However, some of these teachers had also taught STEAM in regular class periods, in collaboration with teachers across multiple disciplines. For example, an art teacher, technology teacher and a science teacher planned a lesson on ‘light’ as a theme, where the culminating project was to build an LED lamp in a variety of shapes and colors of their choice. For this project, students learned basics in each subject, while the project was completed in technology class (Kang et al., 2017 ).

The findings showed that seemingly the same ideas about the nature of integrated STEAM actually diverged in practice. Thus, understanding of teachers’ perceptions of STEAM should be accompanied by understanding of their pedagogical practices (Kang & Wallace, 2005 ).

STEAM teacher drop-outs

The four teachers who stopped teaching STEAM had a number of reasons. Two of them (teacher A and B hereafter) had transferred to different schools. Teacher A’s new school was running a different reform initiative for which he had to work on. He wanted to continue teaching STEAM, but he felt it was not possible without school support. On the other hand, teacher B was optimistic about continuing to teach STEAM lessons, but she was, “looking for teachers who could work together” (Kang et al., 2017 ). The other two drop-outs were both math teachers. They felt STEAM did not properly address math content and wanted to have more mathematics-focused STEAM programs. These issues of attrition can be generalized to any teachers who want to teach STEAM lessons. Changing schools always requires finding teachers at the new school to collaborate with on creating and implementing STEAM lessons. This might be more challenging when a new school aims at a different educational agenda. Also, teachers who are concerned with content coverage may feel that interdisciplinary lessons fall short of enough in-depth content learning.

STEAM-RGT could be a solution for the issue of school transfers and developing new STEAM programs to meet the teachers’ needs. When there is a lack of within school support, teachers can get support from STEAM-RGTs when they are formed with member of different schools. Also, STEAM-RGTs can be formed by teachers who share concerns and goals such as mathematics-focused STEAM program development.

Little research has been conducted about how STEAM-RGT works. Whereas teachers’ learning community has been researched widely (Cochran-Smith & Lytle, 1999 ; McLaughlin & Talbert, 2001 ; Wineburg & Grossman, 2000 ), STEAM-RGT is unique as they focus on developing interdisciplinary curricular materials. Two studies in South Korea were found to have examined STEAM-TRG groups’ work. In particular, one study examined how teachers of different disciplines or subject matter had overcome disciplinary differences and were able to work together to create STEAM lessons collaboratively (Lee, Lee, & Ha, 2013 ). To understand the communication processes, the researchers interviewed teachers, observed teachers’ group discussions, and examined reflective essays. The study used the notion of a trading zone by Galison ( 2010 ) in its analysis, showing an evolutionary process from the beginning of group formation until the implementation of collaboratively developed STEAM lessons. In the process, teachers encountered and overcame a number of challenges including cultural and linguistic differences across disciplines, different motivations for integration, and various understandings of what makes meaningful integration. This study and the other (Jho et al., 2016 ) examined successful or exemplary cases of on-going STEAM-RGTs. To find out ways to facilitate and support STEAM-RGTs, further research on the process of continuation or discontinuation of STEAM-RGTs and related processes is needed.

Meta-analysis of STEAM impact on student learning

Many studies in South Korea examined STEAM effects on student learning. Two major academic search engines in Korea (RISS & KISS) were used to identify research papers on STEAM’s impact on student learning, using “learning” (in Korean) and “STEAM” as search words. Eliminating all studies about pre-school students, 357 papers published between 2011 and 2016 were found. Of these, 160 addressed student learning from STEAM lessons empirically. These studies report different sizes of STEAM effect on students learning while their measure of student learning and aspects of student learning were all different in one way or another. In this context, a meta-analysis can be a good way to estimate the overall effect of STEAM on student learning. Most studies about student learning from STEAM showed positive effects, but the size of the effects differed across studies. Furthermore, some studies found statistical significance in certain variables while others did not. Meta-analysis is a statistical procedure that can help make sense of these differences. When the treatment effect (or effect size) is inconsistent from one study to the next, meta-analysis can be used to identify a common effect by treating each study as one data point in a larger population of studies (Borenstein, Hedges, Higgins, & Rothstein, 2009 ; Hunter, 2004 ).

A total of 11 meta-analyses were published in peer-reviewed journals in Korea from 2012 till 2018. Among these 11 studies, 6 analyzed papers only on STEAM in elementary and secondary schools that STEAM initiative aims. Table  2 provided an overview of the 6 studies.

The number of papers analyzed in the studies varied not only because of the time of study, but also because some of the studies included non-experimental study (experimental group only design) while the others included only quasi-experimental studies.

The meta-analysis results showed medium to high effects on student learning (Table 2 ). These studies also examined a number of variables that could moderate the effect. The moderators examined included sample size, number of STEAM class periods, lesson product types, lesson mediums, student types (gifted or not), grades or school levels, types of emotional experience, number of integrated subjects, class types (regular or non-regular class), and gender. Most of these variables did not significantly moderate the effect size. The moderators that had significant effects in some studies were non-regular class type (effect on affective domain, Cho, 2018 ; Kim & Kim, 2016 ), use of ICT mobile tools (effect on affective domain, Rho & Yoo, 2016 ), and elementary level (effect on technology-centered STEAM, Kim & Kim, 2016 ). However, the same moderators did not have significant effects in other studies (Kang, Lee, et al., 2018 ; Shin, 2018 ).

Given the overall positive effects of STEAM on student learning across all meta-analyses, the effect sizes varied across diverse dependent variables. Among the six studies, two that examined all the dependent variables in research provided an overall picture of STEAM effects on students. The mean effect size in the two studies was medium (Table 2 ). Kang, Lee, et al. ( 2018 ) analyzed research published between 2011 and 2016 while Shin ( 2018 ) analyzed research published between 2012 and 2018. Also, the two analyses were different in that Kang, Lee, et al. ( 2018 ) examined STEAM effect on both elementary and secondary, but Shin ( 2018 ) only analyzed STEAM effect only on elementary students. Although their analysis methods were different and thus the results were not directly comparable, the end results from the two studies showed to be quite similar (Table  3 ).

The two studies found significant effects in similar variables. STEAM seemed to have different degrees of effects on various aspects of learning outcomes. More effective aspects included affective domain, career aspiration, thinking skills and so on. These results were in alignment with the goals of STEAM initiative that wants to go beyond content learning.

Student perceptions of STEAM

As reviewed in the previous section students’ affective domains such as attitudes towards STEM and interest in learning STEM were influenced the most by STEAM programs. However, there is little research on how students perceive STEAM lessons in comparison with regular ones. Annual survey reports on student perceptions of STEAM programs commissioned by KOFAC and two research papers provided an overall picture of how students experienced STEAM in schools (Kang et al., 2017 , Kang, Lee, et al., 2018 ; Lee, Chung Lee, Shin, Chung, & Oh, 2013 ; Lim et al., 2014 . A report examining the long-term effects of STEAM as perceived by students also exists (Kang, Im, et al., 2018 ).

Distinct features of STEAM classes

The annual commissioned reports used the same survey questions to find out student perception of and satisfaction with STEAM lessons implemented in STEAM schools and lessons provided by STEM-RGTs or STEAM curricular program developers funded by KOFAC. Students’ perceptions about STEAM lessons were examined with eight questions concerning general satisfaction, a sense of fun, a sense of challenge, and the features of STEAM lessons they liked the most or least. Among the questions, responses to two questions revealed how students experienced STEAM class. Students were asked about the most distinct feature of STEAM class in comparison with regular classes, and which aspect of STEAM classes they favored the most. Students had to choose one feature from six: integration of subjects, student-centered focus, group work, self-guided work, everyday relevance of STEM, and STEM career information. Over the past three years, every year exhibited similar results. More than half of all students, both elementary and secondary, selected either the integration of subjects or group work as the most distinctive feature of STEAM classes, also nominating either of the two as their favorite feature of STEAM classes.

Students’ perceptions were presented in their own words by Lim et al. ( 2014 ). The study analyzed interviews with 24 6th grade students about their perceptions of STEAM after 12 class periods of a STEAM unit on energy. The students indicated that they enjoyed student-centered design activities and discussion on diverse topics about a problem (interdisciplinary nature). They stated that they were, “more focused than listening to the teacher talking,” and that they found discussion on diverse topics engaging (p. 125). On the other hand, the students stated that thinking for themselves and coordinating different ideas within a group were very challenging. These results aligned with the annual student survey results. Further qualitative in-depth research on student experience with STEAM would help to understand how STEAM can be effective and may shed light on ways to make STEAM learning more meaningful.

J. Lee, T. Lee, Shin, Chung, & Oh, ( 2013 ) examined students’ pictures of people talented in convergence, and whether the images differed between students who had taken STEAM classes versus those who hadn’t. In the study, students were asked to draw a picture of a person talented in convergence with a brief explanation. Analysis of the drawings showed a difference between two groups of lower secondary school students ( n  = 90). Students who had previously taken STEAM classes ( n  = 41) presented images with collective cognitive processing (39%) such as images of many people sharing ideas or different experts working together, but none of students from the no STEAM experience group ( n  = 49) presented collective cognitive processing. Most of those from the non-experienced group depicted images of individual cognitive processing such as famous individuals, a person thinking alone (76%) or famous inventions. Although further research on where their images came from is necessary, the results along with the survey results in other studies indicate that STEAM class could provide proper images of the interdisciplinary nature of current STEM fields. Also, students would understand what to expect when they choose a career in any STEM field.

Student perceptions on long-term effect

The quantitative studies about the effect of STEAM on student learning, as shown in the meta-analysis papers, demonstrated positive immediate effects because they measured student learning outcomes soon after STEAM interventions. However, there was a lack of research on long-term effects. A KOFAC commissioned report surveyed college students who had experienced STEAM programs in secondary school years, and asked those who with no STEAM experience to compare their perceived effects on STEAM or science-related school work during secondary school years (Kang, Im, et al., 2018 ). A sample of those who had STEAM experience were also interviewed about their views on the effects of STEAM lessons and its perceived long-term effects.

With comparable proportions of undergraduate majors, 157 STEAM experienced and 142 non-experienced college students’ survey responses were analyzed. A total of 37 from the STEAM experienced group were interviewed. All the interviewees were college freshmen or sophomores who were mostly science or engineering majors, apart from a few nursing majors.

The main comparison made between the two groups from the survey was whether they felt STEAM experience (for experienced group) or science related school work (for non-experienced group) improved 13 specific core competencies promoted by STEAM and the national science education curriculum. The college students were asked how effective STEAM (or science-related schools work) was on a 5-scale for each competency. With independent t-tests, it was found that on all items except ‘confidence in science and mathematics’, the STEAM experienced group rated significantly higher ( p  < .001) than those without experience (Table  4 ).

Interview data complemented the survey results. The most frequently mentioned positive aspect of STEAM lessons from interviews was self-directed problem solving. Out of this type of activities, they stated, they gained confidence, identity as science learners, and a sense of achievement. Interviews also showed that challenges given during the self-directed problem solving were closely related to the increase in self-esteem. This was also related to entrepreneurship. Many of the interviewees stated that they tended to try out things that were seemingly difficult thanks to their STEAM experience. This corroborated meta-analysis results in that the students perceived affective or emotional experience as significant outcomes.

Another common positive aspect of STEAM was teamwork. The students related their improved ability of communication and caring for team members to long-term group work they had in STEAM classes. These students felt that their STEAM experiences were unique and different from typical school learning. This was particularly salient in their teamwork skills because they could easily compare themselves with others during college team projects.

In the interviews, the positive effects from STEAM experiences were commonly related to their perceived long-term effects on their college studies. Most of the students stated that self-directed learning skills and teamwork skills helped their college classes and many of them contrasted themselves with those who were weak in the skills who had no previous STEAM experience.

The interviews also showed that the STEAM effects on affective domains were related to their decisions regarding college majors and career aspirations. In particular, many engineering and science majors in the interview stated that their decisions about their college majors were informed by their STEAM experience.

Interestingly, many of the engineering majors mentioned that their STEAM experience directly helped their coursework, because they had very similar experiences in high school STEAM lessons. Apparently, engineering design elements of STEAM prepared engineering majors for their college work.

Taken together, the results from interviews with college students who had experienced STEAM corroborated meta-analysis results. Also, the results provided a glimpse of how STEAM programs could have produced relatively long-term effects on students.

Conclusions and implications

This study examined the STEAM initiative in South Korea and reviewed the studies about its effects on teaching and learning. Based on a literature review, evidence of the effects, challenges, and further research topics were identified. Studies have shown that the STEAM initiative was well received by teachers. In terms of increasing teacher capacity to teach integrated STEAM lessons, studies in South Korea found that teacher professional development courses increased teachers’ recognition of the initiative and confidence in teaching STEAM. Teacher interviews showed that coaching in classroom practices within teachers’ professional development was helpful. This could be related to studies about teacher perceptions that revealed differences between teachers who had taught STEAM lessons (teachers in STEAM schools or STEAM-RGTs), and those who had not. Teachers’ STEAM teaching capacity could be strengthened by professional development with elements of collaborative and/or reflective classroom implementation. Further research on effective STEAM professional development program design principles is necessary.

It was also found that there was a lack of research on the connections between teachers’ perceptions of STEAM and their classroom practices. In particular, the high frequency of using science classes for teaching STEAM should be carefully examined in relation to how teachers perceive what STEAM is. Unless science classes are allocated more time in the curriculum, STEAM would be a burden to science teaching, when STEAM is considered less multidisciplinary learning, and more of a new way of teaching science. Furthermore, the interdisciplinary nature of STEAM would be lost, failing to achieve the goal of ‘creative convergence’ in learning. Given the current discipline-based curriculum, STEAM should be carefully conceptualized, and strategies for teacher collaborations across different subjects should be carefully planned.

As for STEAM effects on student learning, a number of meta-analyses provided an overall picture of the effect. The studies reported that the STEAM initiative, to some degree, achieved intended learning outcomes. Meta-analysis showed that students’ experiences with STEAM were effective in cognitive and affective learning. In particular, the effect was higher in affective domains. Interviews with college students who had STEAM experiences in grade schools showed that the effects could be long-term. These students perceived that their earlier STEAM experience better prepared them for college, and improved competencies such as communication and teamwork skills. On the other hand, the meta-analysis studies showed that there were few significant mediating factors. For example, it was found that student grades, lesson medium, and so on did not have significant effects. Further in-depth research on how STEAM programs interact with students is necessary to understand how those variables function in the classroom.

This review demonstrated that the integrated STEAM initiative in South Korea somewhat achieved its goals, while revealing shortcomings in both research and practice. As STEAM has utilized PBL, the positive outcomes were consistent with those expected from PBL (Hmelo-Silver, 2004 ). However, there is a lack of research on the effect of the interdisciplinary nature of STEAM. The interdisciplinary aspect of STEAM should be further studied as a unique feature and goal in order to inform ways of designing meaningful interdisciplinary activities for STEAM. Given the various methods by which to make learning activities interdisciplinary (Banks & Barlex, 2014 ; National Research Council, 2012 ), further research on different effects from different ways of integration is necessary. Research on these topics should be accompanied by research on student learning process and its effects. Linking program designs and implementations with specific outcomes should further develop integrated STEAM programs and their effects.

Given the global emphasis on twenty-first century competencies (e.g., Organization for Economic Co-operation and Development, 2016 ; Partnership for 21st Century Learning, 2009 ), the integrated STEAM initiative in South Korea and similar initiatives in other countries would have continuing, if not increasing, momentum. Thus, this study provides a glimpse of what can be achieved through such efforts, and what should be further researched for better theory and practice.

Availability of data and materials

Not applicable.

Currently, teachers in South Korea are recommended to take 60 h (4 credits) of PD in every five years.

Abbreviations

Information and communications technology

International Technology Education Association

Korea Foundation for the Advancement and Creativity

Korean Studies Information Service System

US National Academy of Engineering

US Next Generation Science Standards includes engineering design and practices as primary elements of science education

US National Research Council

Organization for Economic Co-operation and Development

Problem-based learning

Pedagogical content knowledge

Research Information Sharing Service

Integrated science, technology, engineering, arts, and mathematics education

STEAM research group of teachers

Science, technology, engineering, and mathematics

Science, technology, and society

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Nam-Hwa Kang (Email: [email protected] ) is a professor at Korea National University of Education (KNUE), South Korea. Before she joined KNUE in 2012, she was an assistant professor at University of Nevada, Las Vegas, US, and an assistant and associate professor at Oregon State University, US. Her research centers on science teaching practices in relation to epistemic practices in science. She published papers that address connections between science teacher beliefs about science learning, science inquiry, modelling in science, and scientific argumentation and teaching practices. Her recent projects include defining and supporting science teaching competency development and assessing the impact of integrated STEAM (Science-Technology-Engineering-Arts-Mathematics) reform. She directed research and evaluation of national STEAM initiative for three years. Currently, she is the editor-in-chief of a journal, Innovation & Education published by BMC (part of Springer Nature) and an associate editor of Asia-Pacific Science Education published by Springer Open.

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Kang, NH. A review of the effect of integrated STEM or STEAM (science, technology, engineering, arts, and mathematics) education in South Korea. Asia Pac. Sci. Educ. 5 , 6 (2019). https://doi.org/10.1186/s41029-019-0034-y

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A novel spectral-spatial 3D auxiliary conditional GAN integrated convolutional LSTM for hyperspectral image classification

• Published: 23 August 2024

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• Pallavi Ranjan 1 , 2 ,
• Ashish Girdhar 3 ,
• Ankur 2 &
• Rajeev Kumar 2  

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Hyperspectral Imaging (HSI) has revolutionized earth observation through advanced remote sensing technology, providing rich spectral and spatial information across multiple bands. However, this wealth of data introduces significant challenges for classification, including high spectral correlation, the curse of dimensionality due to limited labeled data, the need to model long-term dependencies, and the impact of sample input on deep learning performance. These challenges are further exacerbated by the costly and complex acquisition of HSI data, resulting in limited availability of labeled samples and class imbalances. To address these critical issues, our study proposes a novel approach for generating high-quality synthetic hyperspectral data cubes using an advanced Generative Adversarial Network (GAN) integrated with the Wasserstein loss and gradient penalty phenomenon (WGAN-GP). This approach aims to augment real-world data, mitigating the scarcity of labeled samples that has long been a bottleneck in hyperspectral image analysis and classification. To fully leverage both the synthetic and real data, we introduce a novel Convolutional LSTM classifier designed to process the intricate spatial and spectral correlations inherent in hyperspectral data. This classifier excels in modeling multi-dimensional relationships within the data, effectively capturing long-term dependencies and improving feature extraction and classification accuracy. The performance of our proposed model, termed 3D-ACWGAN-ConvLSTM, is rigorously validated using benchmark hyperspectral datasets, demonstrating its effectiveness in augmenting real-world data and enhancing classification performance. This research contributes to addressing the critical need for robust data augmentation techniques in hyperspectral imaging, potentially opening new avenues for applications in areas constrained by limited data availability and complex spectral-spatial relationships.

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The data was collected from https://www.ehu.eus/ccwintco/index.php/Hyperspectral_Remote_Sensing_Scenes .

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Acknowledgements

Thanks to the Data Processing Teams who have shared data on the website https://www.ehu.eus/ccwintco/index.php/Hyperspectral_Remote_Sensing_Scenes .

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Pallavi Ranjan

Department of Computer Science and Engineering, Delhi Technological University, Delhi, India

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Communicated by: Hassan Babaie.

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Ranjan, P., Girdhar, A., Ankur et al. A novel spectral-spatial 3D auxiliary conditional GAN integrated convolutional LSTM for hyperspectral image classification. Earth Sci Inform (2024). https://doi.org/10.1007/s12145-024-01451-y

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Received : 20 June 2024

Accepted : 11 August 2024

Published : 23 August 2024

DOI : https://doi.org/10.1007/s12145-024-01451-y

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