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LS50: Integrated Science

What is ls 50: integrated science.

WHAT IS LS 50: INTEGRATED SCIENCE?

In addition to a curriculum of roughly 100 lectures in a wide variety of topics in biology (from structural biology, through cell biology, genetics, and biochemistry to neuroscience, evolution and the origin of life), statistical mechanics, chemistry, dynamical systems, network theory, bioinformatics, and stochastic processes, you will engage in original research projects in throughout the year. Early involvement in science will help you assess your interests in research while applying new analytical, experimental, and simulation-based approaches under real-world conditions.

You can explore the course's subject matter through the list of lecture titles . You can also learn more about the course instructors on the biography page . If you're a current LS 50 student looking for the page containing course materials, please  click here .

WHAT PREPARATION DO I NEED?

HOW BIG A COMMITMENT WILL I BE MAKING?

As a freshman, you take 8 classes distributed over two semesters. this course counts for four of those classes, so it's half your academic effort for your freshman year. we're not trying to mount a year-long hazing ritual, but we will expect you to work hard in return for the effort that the faculty and teaching fellows are investing to develop a new and ambitious course. you will have lectures five days a week..

You will work in small teams to perform original research, working on one project in the fall and another in the spring. If you join LS 50, you will likely be unable to take introductory physics sequences in mechanics and electromagnetism because of scheduling issues. You may also find it challenging to balance the LS 50 workload with additional math courses (although previous LS50 students have done this and survived!). Don't worry: delaying physics and math sequences until sophomore year will not prevent you from concentrating in math or physics if you later choose to do so. In fact, since LS 50 will expose you to quantitative approaches and demonstrate the value of math and physics in the life sciences, we hope you will be motivated to try a more challenging sequence (e.g., Ph 15abc rather than PS 2/3) than you would have attempted as a freshman.

WHAT WILL I LEARN AND HOW MANY FACTS WILL I HAVE TO REMEMBER?

ARE WE GOING TO BE COMPETING WITH OR COLLABORATING WITH EACH OTHER?

HOW HARD WILL I HAVE TO WORK AND WILL I STRUGGLE?

You can read about what previous students have said about LS50 in the CUE GUIDE . Their responses are remarkably uniform: LS50 is challenging and they had to work hard but they enjoyed the experience, learnt a lot, and valued the connections they made with each other and with the faculty, teaching fellows, and course assistants (current Harvard undergrads who were LS50 students last year or the year before).

IS THERE A LAB FOR THE COURSE AND WILL WE BE ABLE TO DO OUR OWN RESEARCH?

Yes, the course will have labs and our goal is to make sure that you never do an experiment whose outcome you can look up because someone else has done it before. You will do project research as follows; AY2024-2025 - Fall term: Molecular signal processing by the yeast mating pathway with Piyush Nanda, and Spring term: SUBJECT TBD with INSTRUCTOR TBD. After you've been trained in basic procedures and lab safety and have demonstrated that you're capable of working independently, you'll have access to the labs anytime when other courses aren't using them. We expect that you'll spend roughly four to six hours per week in lab.

WILL IT BE A PROBLEM IF I'VE NEVER DONE MY OWN RESEARCH BEFORE?

IS THIS COURSE A SMOOTH, WELL-OILED MACHINE?

WHAT NEXT? LIFE AFTER LS 50

HOW WILL I PROGRESS THROUGH MY GRADUATION/CONCENTRATION/PRE-MEDICINE REQUIREMENTS?

WANT TO KNOW MORE?

Check out the LS50 FAQ . If you are still unsure and want to hear more about this course, reach out to some students who have previously taken it. Send them an email   here  to ask your questions or ask to meet with someone. 

HAVE QUESTIONS?

We may  have a table at the   Academic Fair on DATE TBD, from TIME TBD   under the Science Center Plaza Tent   where you can ask questions and meet some staff.  Or, drop into one of the  two LS50 Informational Zoom Sessions  as follows:

Session 1: DAY, DATE & TIME TBD EDT - 

Topic: LS50 Info Session

Join Zoom meeting: Link To Be Provided

Password: TBD

● Prof attendees TBD and Course Assistants

Session 2: DAY, DATE & TIME TBD EDT -  

You can raise questions or concerns speaking with instructors and former students.

HOW DO I GET IN?

LS 50: Integrated Science has room for approximately 30-40 students (freshmen only, no exceptions). We encourage you to complete  our survey form   by 11:59 PM EDT on Monday, August 26th . You don't have to do this to take the course, but if you do and you want to talk to us about the course, it means we already have some information about you to help guide the conversation.

Initially, we held a lottery and then had a wait list for those who didn't lottery into the class. We have always been able to give everyone on the wait list a chance to take LS50, since then we have been doing things differently. Until registration, we may hold the class in a larger room, and everyone who is interested is welcome to come, but we ask you to email us ( [email protected] ) either to tell us that you want to take the class, or to tell us, if you later change your mind, that you don't . Whether or not you complete the survey, if you are sure you want to take this course,  YOU MUST 1) send an email expressing your interest/intent, 2) petition to enroll in my.Harvard.edu, 3) wait to see if we have to hold a lottery or if your petition is approved, and 4) remember to enroll once your petition has been approved in order to be considered and included if we have to hold a lottery. Completing the course survey to provide info so we have some background info on you is voluntary and not required, but very helpful to us .

If we have more than 40 students petition to take LS50, we'll hold a lottery to select no more than 40 students and notify you by email. Given that enrollment has ranged between 25 and 40 students, it is likely that we will have room for everyone who wants to take LS50. Classes begin on Tuesday, September 3rd .

If you would like to learn more about the course (beyond what you can find here and on the official course website ( https://canvas.harvard.edu/courses/136886 ) before the fall semester begins, contact us at  [email protected]  if you have any questions.

HOW TO PETITION FOR LS50 AND HOW A LOTTERY WILL WORK

LS50 has room for 40 students all of whom must be freshmen. If more than 40 students want to take the course, we will hold a lottery to determine who is allowed to enroll. To indicate your intention to enroll, you go to my.Harvard.edu and attempt to register for LS50. This will generate a petition to take the course and the petition will appear on the Work List of the course head.  You can make sure you have petitioned correctly by checking to see if you can see an orange clock next to the course name on my.Harvard after you start trying to enroll.

What will happen next depends on how many students petition:

1) If 40 or fewer students petition, we will approve all the petitions, thus allowing those students to enroll and take the course.

2) If more than 40 students petition by 11:59 PM EDT on Monday, August 26th, we will hold a lottery by 5:00 PM EDT on Tuesday, August 27th, approve the petitions of 40 students, and email those who will unable to enroll. All selected enrollees will be approved and accepted by Thursday, August 29th.

Some notes:

a) Please do not petition until you have decided you want to take the class; when you petition, it has no influence on the lottery, which is done using a random number generator.

b) If you petition and then decide you don’t want to take LS50, email [email protected] to tell us. If you don’t, you may keep someone else from enrolling.

c) If you are having trouble generating the petition, check that your freshman advisor has released the Hold that keeps you from registering for courses.

d) If we have a lottery and your petition is approved, you must then formally enroll to be part of the class.

e) If we have to lottery, we will notify the 5 people who came closest to being able to take LS50, asking if they want to audit the course for the first week in case some of the enrolled students decide to drop the course. Apart from this procedure, we do not allow students to audit LS50.

f) Because it’s a real lottery, you needn’t fill out anything for the petition text.

The petition to enroll in LS50a in my.Harvard should be by 11:59 PM on Monday, August 26th. This would give us Tuesday, August 27th, to hold the lottery if necessary and make notifications. Thus allowing students to formally enroll, or make alternate course selections, by the Registration Deadline.

WHAT IF I NEED TO DROP LS 50?

We recognize that LS 50 is an ambitious undertaking. We strive to support our students through office hours, recitation sections, collaborative work on problem sets in study groups, peer tutoring, and on-on-one discussions. However, we will do our best to ease the transition of students who choose to leave LS 50. Freshmen are required to enroll in three letter-graded courses per semester, so students leaving LS 50 will need to enroll in at least one additional class (we recommend LS 1a and/or an appropriate math course). Transferring to another course becomes more challenging as the term progresses, so please speak with us as your concerns arise.

• Open access
• 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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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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Integrative Biology: Science for the 21st Century

Marvalee H. Wake (e-mail: [email protected] ) is with the Department of Integrative Biology at the University of California–Berkeley.

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Marvalee H. Wake, Integrative Biology: Science for the 21st Century, BioScience , Volume 58, Issue 4, April 2008, Pages 349–353, https://doi.org/10.1641/B580410

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Integrative biology is a label frequently used to describe various forms of cross-disciplinary and multitaxon research. The term is ill defined, but in fact it does rely on principles that are transforming 21st-century science. Collaborative and integrative biology generates new information and new ideas by bringing diverse expertise to problems, so that individual and institutional expertise becomes broader and more exploratory as a consequence. Both research and education modes must change to facilitate new approaches to resolving complex questions.

Integrative biology, fundamentally integrative science, is an essential and effective approach to resolving many of the complex issues facing the 21st century. It is a way of perceiving and practicing science and of transforming science—its processes and its results—to deal with societal issues. It is both an attitude about the scientific process and a description of a way of doing science ( Wake 2000 , 2001 , 2003 , Lakhotia 2001 , Barbault et al. 2003 ). Many people and institutions calling themselves “integrative biologists” are not aware that a set of general principles has been articulated for the emerging synthetic process ( Pennisi 2000 , Lakhotia 2001 , Wake 2001 , 2003 , Paton 2002 , Liu 2005 ). Those principles emphasize not just multidisciplinary but also transdisciplinary research that incorporates the biological, physical, socioeconomic, mathematical, engineering, and humanities components appropriate for addressing complex questions and problems. The problems might be initially and perhaps fundamentally considered to be biological, but they are multidimensional and require input from many areas ( Wake 1995 , 2003 , Murray 2000 , Kumar and Feidler 2003 ). Integrative approaches include (a) bringing together researchers of diverse expertise to identify, articulate, and structure problems; (b) providing hierarchical explorations of the issue (observational, experimental, modeling, etc.); and (c) developing research, outreach, and educational frameworks that facilitate integration. Less-flexible sectoral and single-discipline models of communication and research touch each other only tangentially. However, not all who call themselves “integrative biologists” agree with these general principles. Consequently, many different definitions of “integrative biology” exist ( Ripoll et al. 1998 , Wake 2003 , NAS 2004 ), and they usually emphasize only one of the points mentioned above; moreover, the approach that an individual or institution adopts may depend on the nature of the person's or organization's expertise.

Why, then, is “integrative biology” becoming a label of choice for research programs in biology and medicine, universities and institutes, units in funding agencies, and programs in nongovernmental organizations (NGOs)? To some people, it is merely a label meant to replace taxon-based names now deemed “old-fashioned,” an unfortunate opinion of the value of taxa. In the more progressive units, though, the label has real meaning because it reflects an ongoing change in research and educational paradigms. Integrative biology—integrative science—bridges disciplines, and it works within and across levels of biological organization and across diverse taxa over time, short (ecological or physiological) and long (evolutionary). Examples are numerous, especially of the integration of the subdisciplines of biology and medicine (e.g., Wake 1990 , 1995 e.g., Wake 2004 , Wainwright and Reilly 1994 , Marden et al. 1998 , Williams and Wagner 2000 ), but also of more inclusive integration (e.g., Murray 2000 , Delneri et al. 2001 , Barbault et al. 2003 , Kafatos and Eisner 2004 , NAS 2004 , Liu 2005 ).

One example of integrative efforts that bears a different label is that of “systems biology.” Systems biology shares the problem of definition with integrative biology—as Henry (2003) noted, it too “means different things to different people.” She defines it as an “integrative approach in which scientists study pathways and networks [that] will touch all areas of biology, including drug discovery” ( Henry 2003 ). As the people she cites report, systems biology is not new, but the field is profiting from new experimental tools and from the recognition that “the analysis of networks, regulation, and how the thing works from a whole system point of view” can now be investigated with computational tools and computer-generated models. One scientist whom she cites states that systems biology “doesn't exist,” but rather is “what people have always done in biology, which is physiology of cells.” Diverse conceptions of systems biology are driving not just basic research but considerable research and funding in medicine and biotechnology as well (see, e.g., Kitano 2001 , Alberghina and Westerhoff 2005 , Klipp et al. 2005 , Alon 2006 , Palsson 2006 ). In my view, systems biology is a form of the more inclusive concept and practice of integrative biology, characterized by the “systems approach,” which is part of—but far from all of—integrative biology. Integrative biology, for the purposes of this discussion, includes systems biology.

Integrative approaches offer much that current practices do not. Integration facilitates the generation of new hypotheses and new questions because representatives with an array of expertise communicate with one another about general but complex issues. The ability of such research teams to generate data and resources faster, and with more dimensionality, than can practitioners of the single-focus model of research confers a “competitive advantage.” Most important, the new ideas, approaches, and insights of integrative approaches can make the science more innovative.

The kinds of questions and problems that benefit most from an integrative approach are those that cut across traditional disciplinary boundaries, as many issues of biological complexity currently require. Such questions, all of which have important societal implications, include the relationship of climate change and ecosystem function, genotype-phenotype interactions, the sustainability and conservation of biological diversity in seminatural environments, the evolution of hyper -communicable diseases and the prevention and eradication of them, the translation of how animals locomote to the development of miniature and giant robots, and many others.

Current methods of research and education limit the likelihood that many scientists will become integrative in the sense described here. Individual scientists propose most research agendas, and most research funding goes to support their work. At the same time, more scientists are recognizing the need for expertise beyond their own to deal with the complex problems that they are investigating. This recognition promotes the first integrative step—the gathering of diverse expertise, either individually or, more often, collectively—yet the research teams that thus coalesce usually disintegrate when the problem is solved or the funding period ends. A new stimulus for integrative approaches, however, comes from agencies and organizations, particularly foundations and NGOs, with interests in social issues that potentially can be solved by good science meshed with good management. These entities are calling for research teams with diverse expertise to attack hard questions and supply new ideas and solutions.

The critical second step in developing integrative approaches has to do with changing most models of education. Students are usually trained from the beginning of their education to be independent, even competitive. This is amplified in graduate school, when students are told that they must focus on a subdiscipline, on a few techniques and ideas. They are also informed that the literature explosion is such that no one can keep abreast of his or her own field, let alone any others. Wrong. Although a student or a scientist should be well centered in the part of the discipline that interests him or her the most and to which he or she can make significant contributions, those contributions will be even more significant if the student-scientist is aware of and able to use the literature, techniques, ideas, and especially the people of other disciplines pertinent to the scientific questions being tackled ( Wake 1998 , 2000 , 2001 , 2003 , NAS 2004 ).

The tools are available to facilitate this knowledge. Students should be trained to think independently, of course, but also to participate effectively in team-based scientific research and teaching. Educational models should be modified to facilitate interactive science. Furthermore, research agendas should be transformed to emphasize integrative approaches intellectually and at the bench and in the field. The professor who considers him- or herself an integrative biologist because he or she has a broad knowledge, uses several techniques in the lab, and examines several taxa or field sites, yet assigns each graduate student a single technique, taxon, or narrow problem, does not train future integrative biologists.

Research agendas should be modified so that they address the contribution of the research effort to the resolution of complex issues and an overall contribution to science, and at least consider the way that the research might contribute to resolution of societal problems. Educational curricula should be sure to include acquisition of function—techniques, ideas, and communication—in relevant areas outside students' central discipline. This would enhance a well-known but little-emphasized reciprocity. Research, education, and outreach are inextricably linked, and they must evolve together. Outreach, in its best forms, establishes a communication platform among the stakeholders in order to identify and structure problems, and to answer the questions the stakeholders associate with the solution to the problems. The communication that is integral to the development of integrative research approaches must influence the educational experience as well, and at all levels and throughout the careers of students and scientists.

How do we achieve the goals of modifying research agendas and educational policies so that integrative approaches are included and emphasized? First, we must acquaint scientific colleagues, educators, funding agencies, and policymakers with the advantages of integrative approaches relative to current methods of research and training. Second, we must elucidate what is integrative and what is not. (And not all approaches need to be—or even can be—integrative, at least at their outsets, but their practitioners should be aware of the model of activity that they have chosen and why they have chosen it relative to other models.) The advantages of integrative research science are, at the minimum, that it at once advances not only an individual's central disciplines but also other fields; it provides for the generation of new hypotheses, techniques, and ideas; and it establishes environments that promote the interactions that facilitate new syntheses and ideas.

How can we do integrative biology in research and education? In terms of curricula, we can make sure that students are introduced very early to broadly based science that is centered in biology by featuring organisms but has a scope that includes reference to all elements of the hierarchy of biological organization and the other sciences and humanities. For example, the kindergartner, learning about the plants and animals that live in the schoolyard pond, a rice paddy, or a garden near home, can participate in a discussion of the biology of the organisms and their interactions with one another, the effects of climate, the social dimensions of food and water supply and desiccation, and the aesthetics of a calling frog's song or a beautiful stand of plants. Education in following years can be more fine-grained, inclusive, and synthetic as different kinds of ideas, questions, and problems—and how to deal with them—are considered (which might make learning fundamentals and techniques more interesting). It is by doing science that students learn critical thinking and positive skepticism, and they should be engaged in hands-on science as early as possible, while they are still curious about the world around them. The maintenance of critical thinking and skepticism is important at all levels of the scientific enterprise—professionals should not lose that capacity.

Throughout the education and training period of the student, and then throughout the professional career of the scientist, the creation of environments that promote communication and collaboration should be a goal. The classroom and outside activities can do this for young students. For secondary, undergraduate, and graduate students, we should develop experiences that stress interaction. Particularly at the university level, we can create the common labs and other facilities that promote the assembly of diverse expertise for research purposes, and include students in them for their training. This can provide a centered educational experience, especially when supported by nontraditional course work—an experience that has extended students' exposure to other subdisciplines and fields of science and humanities (see box 1 ). Equally important to both the research and educational spheres, and their reciprocity, is the exchange of students and postdoctoral scholars among laboratory groups with different centers of expertise. These exchanges would promote communication and collaboration within the lab and across a whole series of institutions, resulting in wider knowledge of techniques, ideas, the literature, and the practitioners.

Why should we practice integrative biology? The answer to that question is that the times are changing rapidly, and our current methods are not advancing us as quickly as the more forward-looking integrative approaches seem to be. Yet we seem to be approaching integrative biology without changing our lab structures, curricula, or research agendas—that is, without modifying our scientific culture. This approach is not the best one. For several reasons, we need explicit and directed change in our overall research and educational methodologies: Perhaps the most significant reason for explicit and directed change in the 21st century, however, is our emerging understanding that science and scientists must address societal needs and questions in new, wide-ranging, and synthetic ways (see box 2 ). Professionals should include a concept of the contribution of their research to societal needs as part of their research design, and students should be trained throughout their education to include such a concept in their value systems (see box 3 ).

The rapid growth in the volume of information and in the kinds of resources available makes collaboration a more effective way to work.

Although we have acknowledged for many years that research and education are reciprocal, they need to be better linked.

We know that two-way feedback can be promoted within biology, and from biology to other disciplines, and vice versa.

We believe that doing is the way to double-check and expand concepts and examples of integrative biology and integrative science.

For integrative approaches to succeed, several changes must be made. The most difficult, but most important, is a change in attitude. The lone scientist must be prepared to set aside individual research at times to contribute to a collaboration that deals with broad issues and sorts them out in new and different ways to generate innovative ideas. Educational curricula, now so often driven by testing devices, the equipment available, and the need for perceived uniformity, must be modified to make training creative and participatory, and thereby more likely to generate the new ideas that will drive cutting-edge science. The way forward is to communicate the advantages of integrative approaches and to present examples of the ever-increasing number of successes achieved through integrative, collaborative, problem-driven science.

Integrative attitudes and approaches will lead to innovative, progressive, and enlightened scholars in the 21st century. Science and society will derive great benefits from their contributions to research, education, and humanity.

I thank the Steering Committee for the Integrative Biology Programs of the IUBS (International Union of Biological Sciences)—Allan Bittles, Robert J. Full, Motonori Hoshi, Jukka Jernvall, Subhash Lakhotia, Lily Rodriguez, Erwin Beck, Christoph Scheidegger, and Talal Younès—for their excellent efforts in promoting the principles and practices of integrative biology throughout the world, and for insisting that this contribution be written (I chaired the committee for several years). I am grateful to all those who have aided in developing those principles and practices and influenced my thinking about the concepts.

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Transformative biological research will require integration with physics, engineering, mathematics, chemistry, and computer science to a degree not yet seen. To facilitate this revolution, the very structure of academia must change. Development of expertise will most likely remain the domain of departments. Interdisciplinary problems requiring the integration of several disciplines will reside in agile centers that will continue to increase in number and resources. One such center has been created recently at UC Berkeley—CiBER, the Center for Interdisciplinary Bioinspiration in Education and Research. CiBER includes faculty from Integrative Biology, Bioengineering, Mechanical Engineering, Civil Engineering, Electrical Engineering, Computer Science, and Psychology. Stations in the common laboratory offer the opportunity for individuals in academy and industry to contribute to and benefit from those in diverse disciplines. The research goal is to extract principles and analogies from biology that inspire novel design in engineering and use ideas, approaches, and devices from engineering to generate new hypotheses and allow novel measurements in biology. The education goal is to train the next generation of scientists and engineers to collaborate in mutually beneficial relationships. Success in interdisciplinary research requires communicating and teaching fundamental concepts to those in other disciplines. Using an interdisciplinary approach to teaching can result in more effective teaching and, in turn, lead to better research.

ROBERT J. FULL, Cofounder, CiBER, Department of Integrative Biology, University of California, Berkeley

The mission of the National Science Foundation (NSF) is to ensure US leadership in scientific discovery and in the development of new technologies. We at the NSF often refer to the foundation as the place “where discoveries begin,” and take seriously our role to guide and advance the frontiers of science and engineering knowledge. It is within this context that the Division of Integrative Biology and Neuroscience (IBN) initiated a series of discussions in early 2003 to assess how we might best encourage and catalyze scientific research in the 21st century. The previous century had seen significant advances in fundamental research on all aspects of “life,” from molecules to ecosystems, with the promise of achieving in the 21st century a complete understanding of how organisms—from microbes to elephants—interact with each other, as well as how organisms interact with and ultimately shape the environment.

As a direct result of these discussions, IBN made dramatic changes in its organizational structure and intellectual focus in an effort to stimulate discovery in new ways. The goals were to advance understanding of the underlying principles, mechanisms, and processes essential to organisms; to promote synthetic, integrative research on a wide diversity of organisms; and to catalyze growth in important emerging areas by encouraging integrative research and education activities that crossed traditional boundaries. In the last six months, the division has reaffirmed its commitment to supporting projects that combine experimentation, computation, and modeling in the analysis of organisms across multiple levels of organization and lead to new conceptual and theoretical insights about the biology of organisms as complex interacting systems that are far more than simply the sum of their parts. It is clear that achievement of this level of understanding will require precisely the kind of transdisciplinary integrative thinking and approaches described in this article.

JUDITH A. VERBEKE, Acting Division Director, Integrative Organismal Systems, National Science Foundation, Washington, DC

Studies in our institute deal with major problems of behavioral biology: choice of mates and those most fit, choice of food and control of intake, memory of past experiences and correcting behavior.... Why is our approach to these problems integrative?

We seek simple and appropriate models to investigate each question: for example, rodents use their sensory systems to localize their food, discriminate among its qualities, and regulate its intake. They also have elaborate capacities to store information, compartmentalize its storage, and use it subsequently. We use multidisciplinary approaches in parallel to dissect the biological systems involved: we describe behaviors, localize anatomical centers, test the functioning of nervous circuits and their development and their plasticity, and we try to model them. We establish collaborations with researchers in other fields; for example, recently, physicists were invited to our institute to build sensitive, high-resolution imaging apparatus adapted to small brains, such as those of birds.

We learn much from comparisons among several animal models. We also make extensive use of all kinds of “variants”: those resulting from adaptations to different environments, such as fruit flies that have lived at different temperatures, birds that have lived in sympatry or allopatry, rats bred with different diets, transgenic mice with genes invalidated. Several genes involved in Drosophila memory have been characterized; they are conserved, so we manipulate homologous mouse genes. The parallel use of several models stimulates discussions about the evolution of physiological mechanisms and their biological functions.

Our interest is not limited to basic studies. We are also concerned with applications such as biological control of pests or human diseases. We have frequent interactions with clinicians involved in the treatment of pathologies such as specific anosmia, Alzheimer's disease, and obesity, making our work synthetic and reciprocal.

JEAN-MARC JALLON, Director of the Institute of Animal, Integrative and Cellular Biology, University of Paris–South, Orsay, France

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A conceptual framework for integrated STEM education

• Todd R. Kelley 1 &
• J. Geoff Knowles 2  

International Journal of STEM Education volume  3 , Article number:  11 ( 2016 ) Cite this article

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The global urgency to improve STEM education may be driven by environmental and social impacts of the twenty-first century which in turn jeopardizes global security and economic stability. The complexity of these global factors reach beyond just helping students achieve high scores in math and science assessments. Friedman (The world is flat: A brief history of the twenty-first century, 2005) helped illustrate the complexity of a global society, and educators must help students prepare for this global shift. In response to these challenges, the USA experienced massive STEM educational reforms in the last two decades. In practice, STEM educators lack cohesive understanding of STEM education. Therefore, they could benefit from a STEM education conceptual framework. The process of integrating science, technology, engineering, and mathematics in authentic contexts can be as complex as the global challenges that demand a new generation of STEM experts. Educational researchers indicate that teachers struggle to make connections across the STEM disciplines. Consequently, students are often disinterested in science and math when they learn in an isolated and disjoined manner missing connections to crosscutting concepts and real-world applications. The following paper will operationalize STEM education key concepts and blend learning theories to build an integrated STEM education framework to assist in further researching integrated STEM education.

Many global challenges including “climate change, overpopulation, resource management, agricultural production, health, biodiversity, and declining energy and water sources” need an international approach supported by further development in science and technology to adequately address these challenges (Thomas and Watters 2015 , p. 42). Yet numerous educational research studies have indicated that students’ interest and motivation toward STEM learning has declined especially in western countries and more prosperous Asian nations (Thomas and Watters). Concern for improving STEM education in many nations continues to grow as demand for STEM skills to meet economic challenges increasingly becomes acute (English 2016 ; Marginson et al. 2013 ; NAE and NRC 2014 ). Driven by genuine or perceived current and future shortages in the STEM workforce, many education systems and policy makers around the globe are preoccupied with advancing competencies in STEM domains. However, the views on the nature and development of proficiencies in STEM education are diverse, and increased focus on integration raises new concerns and needs for further research (English 2016 ; Marginson et al. 2013 ).

Although the idea of STEM education has been contemplated since the 1990s in the USA, few teachers seemed to know how to operationalize STEM education several decades later. Americans realized the country may fall behind in the global economy and began to heavily focus on STEM education and careers (Friedman 2005 ). STEM funding for research and education then increased significantly in the USA (Sanders 2009 ). The urgency to improve achievement in American Science, Technology, Engineering and Mathematics education is evident by the massive educational reforms that have occurred in the last two decades within these STEM education disciplines (AAAS 1989 , 1993 ; ABET 2004 ; ITEA 1996 , 2000, 2002, 2007 ; NCTM 1989 , 2000 ; NRC 1989 , 1994 , 1996 , 2012 ). Although these various documents seek to leverage best practices in education informed by research on how people learn (NRC 2000a , 2000b ), competing theories and agendas may have added confusion to the complexity of integrating STEM subjects. Recent reforms such as Next Generation Science Standards (NGSS) (NGSS Lead States 2013 ) and Common Core State Standards for Mathematics (CCSSM) (National Governors Association Center for Best Practices & Council of Chief State School Officers 2010 ) advocate for purposefully integrating STEM by providing deeper connections among the STEM domains. One of the most recent NAE and NRC ( 2014 ) documents, STEM Integration in K - 12 Education : Status , Prospects , and an Agenda for Research , recognize problems with competing agendas, lack of coherent effort, and locating and teaching intersections for STEM integration. The Committee on Integrated STEM Education was charged to assist STEM education stakeholders by (a) carefully identifying and characterizing existing approaches to integrated STEM education, (b) review evidence of impact on student learning, and (c) help determine priorities for research on integrated STEM education. This report was created as a way to move STEM educators forward by creating a common language of STEM integration for research and practice. This effort indicates that further work remains to improve STEM integration in practice and establishes a need to conduct more research on integrated STEM education (NAE and NRC 2014 ).

One outcome of improving achievement in STEM education in many countries is preparing a workforce that will improve national economies and sustain leadership within the constantly shifting and expanding globalized economy. Wang, Moore, Roehrig, and Park ( 2011 ) stated that:

Growing concern about developing America’s future scientists, technologists, engineers, and mathematicians to remain viable and competitive in the global economy has re-energized attention to STEM education. To remain competitive in a growing global economy, it is imperative that we raise student’s achievement in STEM subjects. (p. 1)

European STEM educators and industrialists have identified a widening STEM skills gap among the workforce. Improving STEM education is driven increasingly by economic concerns in developing and emerging countries as well (Kennedy and Odell 2014 ). While STEM student enrollment and motivation has declined in many western countries, various studies have shown an increased interest among young people in developing nations such as India and Malaysia (Thomas and Watters 2015 ).

Seeking coherency in STEM education

Much ambiguity still surrounds STEM education and how it is most effectively implemented (Breiner et al. 2012 ). STEM education is often used to imply something innovative and exciting yet it may, in reality, remain disconnected subjects (Abell and Lederman 2007 ; Sanders 2009 ; Wang et al. 2011 ). However, an integrated curricular approach could be applied to solve global challenges of the modern world concerning energy, health, and the environment (Bybee 2010 ; President’s Council of Advisors on Science and Technology (PCAST) 2010 ). Kennedy and Odell ( 2014 ) noted that the current state of STEM education:

has evolved into a meta-discipline, an integrated effort that removes the traditional barriers between these subjects, and instead focuses on innovation and the applied process of designing solution to complex contextual problems using current tools and technologies. Engaging students in high quality STEM education requires programs to include rigorous curriculum, instruction, and assessment, integrate technology and engineering into the science and mathematics curriculum, and also promotes scientific inquiry and the engineering design process. (p. 246)

STEM education can link scientific inquiry, by formulating questions answered through investigation to inform the student before they engage in the engineering design process to solve problems (Kennedy et al. 2014 ). Quality STEM education could sustain or increase the STEM pipeline of individuals preparing for careers in these fields (Stohlmann et al. 2012 ). Improving STEM education may also increase the literacy of all people across the population in technological and scientific areas (NAE and NRC 2009 ; NRC 2011 ).

As the USA and other countries work to build their capacity in STEM education, they will need to interact with each other in order to enhance their efforts in international scientific engagement and capacity building to provide quality education to all of their students (Clark 2014 , p. 6).

Defining integrated STEM education

Over the last few decades, STEM education was focused on improving science and mathematics as isolated disciplines (Breiner et al. 2012 ; Sanders 2009 ; Wang et al. 2011 ) with little integration and attention given to technology or engineering (Bybee 2010 ; Hoachlander and Yanofsky 2011 ). Furthermore, STEM subjects often are taught disconnected from the arts, creativity, and design (Hoachlander and Yanofsky 2011 ). Sanders ( 2009 ) described integrated STEM education as “approaches that explore teaching and learning between/among any two or more of the STEM subject areas, and/or between a STEM subject and one or more other school subjects” (p. 21). Sanders suggests that outcomes for learning at least one of the other STEM subjects should be purposely designed in a course—such as a math or science learning outcome in a technology or engineering class (Sanders 2009 ). Moore et al. ( 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). Integrated STEM curriculum models can contain STEM content learning objectives primarily focused on one subject, but contexts can come from other STEM subjects (Moore et al.). We, however, define integrated STEM education 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.

The authors acknowledge that there are limits to this approach to teaching integrated STEM education. Some might view this approach too focused on career pathways with emphasis on STEM practices and authentic application of STEM knowledge. The authors acknowledge that teaching STEM from the proposed approach is not possible in all circumstances and could limit the content taught from this approach. Some necessary knowledge in mathematics and sciences that are theoretically focused may not provide authentic engineering design applications as well as common STEM practices limited by current technology.

Limits of current integrated practices

Making crosscutting STEM connections is complex and requires that teachers teach STEM content in deliberate ways so that students understand how STEM knowledge is applied to real-world problems. Currently, crosscutting connections remain implicit or can be missing all together (NAE and NRC 2009 ). The Committee on Integrated STEM Education noted that:

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. (NAE and NRC 2014 , p. 5)

Increased integration of STEM subjects may not be more effective if there is not a strategic approach to implementation. However, well-integrated instruction provides opportunities for students to learn in more relevant and stimulating experiences, encourages the use of higher level critical thinking skills, improves problem solving skills, and increases retention (Stohlmann et al. 2012 ). Building a strategic approach to integrating STEM concepts requires strong conceptual and foundational understanding of how students learn and apply STEM content. The following theoretical framework for integrated STEM seeks to propose such an approach.

Conceptual framework for integrated STEM education

Research in integrated STEM can inform STEM education stakeholders to identify barriers as well as determine best practices. A conceptual framework is helpful to build a research agenda that will in turn inform STEM stakeholders to realize the full potential of integrated STEM education. We propose a conceptual framework around learning theories and pedagogies that will lead to achieving key learning outcomes. Developing a conceptual framework for STEM education requires a deep understanding of the complexities surrounding how people learn, specifically teaching and learning STEM content. Research shows STEM education teaching is enhanced when the teacher has sufficient content knowledge and domain pedagogical content knowledge (Nadelson et al. 2012 ). Instead of teaching content and skills and hoping students will see the connections to real-life application, an integrated approach seeks to locate connections between STEM subjects and provide a relevant context for learning the content. Educators should remain true to the nature in which science, technology, engineering, and mathematics are applied to real-world situations. The Next Generation Science Standards (NRC 2012 ) suggest closer study of practices may help to provide a framework for integrating STEM subjects.

The proposed framework as presented is intended for secondary education, specifically high school level educators and learners. The following graphic (Fig.  1 ) helps capture a conceptual framework for integrated STEM education and will also serve as a frame for the core concept of the paper. We will reference the graphic throughout the paper to further explain key concepts and make connections across STEM practices. The aim of this paper is to propose a conceptual framework to guide STEM educators and to build a research agenda for integrated STEM education.

Graphic of conceptual framework for STEM learning

Figure  1 illustrates the proposed conceptual framework for integrated STEM education. The image presents a block and tackle of four pulleys to lift a load, in this case “situated STEM learning.” Block and tackle is a pulley system that helps generate mechanical advantage to lift loads easier. The illustration connects situated learning, engineering design, scientific inquiry, technological literacy, and mathematical thinking as an integrated system. Each pulley in the system connects common practices within the four STEM disciplines and are bound by the rope of community of practice. A complex relationship of the pulley system must work in harmony to ensure the integrity of the entire system. The authors are not suggesting that all four domains of integrated STEM must occur during every STEM learning experience but STEM educators should have a strong understanding of the relationship that can be established across domains and by engaging a community of practice. Like any mental model, there are limits to looking at integrated STEM education using this approach. We will seek to provide support for this mental model while acknowledging the limits in viewing STEM education this way. Each part of the conceptual framework will be described in detail. We encourage readers to refer back to Fig.  1 to help better understand the various aspects of this proposed framework.

Situated STEM learning

The authors would advocate most content in STEM can be grounded within the situated cognition theory (Brown et al. 1989 ; Lave and Wenger 1991 ; Putnam and Borko 2000 ). Foundational to this theory is the concept that understanding how knowledge and skills can be applied is as important as learning the knowledge and skills itself. Situated cognition theory recognizes that the contexts, both physical and social elements of a learning activity, are critical to the learning process. When a student develops a knowledge and skill base around an activity, the context of that activity is essential to the learning process (Putnam and Borko 2000 ). Often when learning is grounded within a situated context, learning is authentic and relevant, therefore representative of an experience found in actual STEM practice. When considering integrating STEM content, engineering design can become the situated context and the platform for STEM learning.

Certainly, there is some STEM content that cannot be situated in authentic contexts, therefore limiting this model to only content that can be applied through situated learning approaches. Within Fig.  1 , the analogy of situated learning as a “load” to lift may present a limited perspective of this educational model.

Pulley #1: engineering design

Engineering design can provide the ideal STEM content integrator (NAE and NRC 2009 ; NRC 2012 ). Moreover, an engineering design approach to delivering STEM education creates an ideal entry point to include engineering practices into existing secondary curriculum. Using engineering design as a catalyst to STEM learning is vital to bring all four STEM disciplines on an equal platform. The very nature of engineering design provides students with a systematic approach to solving problems that often occur naturally in all of the STEM fields. Engineering design provides the opportunity to locate the intersections and build connections among the STEM disciplines, which has been identified as key to subject integration (Frykholm and Glasson 2005 ; Barnett and Hodson 2001 ).

Science education can be enhanced by infusing an engineering design approach because it creates opportunity to apply science knowledge and inquiry as well as provides an authentic context for learning mathematical reasoning for informed decisions during the design process. The Conceptual Frameworks for New Science Education Standards (NRC 2012 ) in the USA recommend that students are given opportunities to design and develop science investigations and engineering design projects across all K-12 grade levels (p. 9). The analytical element of the engineering design process allows students to use mathematics and science inquiry to create and conduct experiments that will inform the learner about the function and performance of potential design solutions before a final prototype is constructed. This approach to engineering design allows students to build upon their own experiences and provide opportunities to construct new science and math knowledge through design analysis and scientific investigation. According to Brown et al. ( 1989 ), these are necessary experiences for effective learning:

Engineering and technology provide a context in which students can test their own developing scientific knowledge and apply it to practical problems; doing so enhances their understanding of science—and, for many, their interest in science—as they recognize the interplay among science, engineering, and technology. We are convinced that the engagement in the practices of engineering design is as much a part of learning science as engagement in the practices of science. (p.12)

In engineering practice, engineering design and scientific inquiry are interwoven through an intricate process of design behaviors and scientific reasoning (Purzer et al. 2015 ). Though there is a notable difference between engineering design and scientific inquiry, two central ways they converge according to Purzer et al. ( 2015 ) are “(a) reasoning processes such as analogical reasoning as navigational devices to bridge the gap between problem and solution and (b) uncertainty as a starting condition that demands expenditure of cognitive resources…” (p. 2). Additionally, both engineering design and scientific inquiry accentuate learning by doing (Purzer et al. 2015 ). Similar to situated learning theory, approaching all STEM content through engineering design is not always possible. For example, some science content is currently theoretically based and cannot be taught by design-based instruction.

Pulley #2: scientific inquiry

Learning science in a relevant context and being able to transfer scientific knowledge to authentic situations is key to genuine understanding. An inquiry approach to instruction requires teachers to “encourage and model the skills of scientific inquiry, as well as the curiosity, openness to new ideas, and skepticism that characterize science” (National Research Council 1996 , p. 37). Scientific inquiry prepares students to think and act like real scientists, ask questions, hypothesize, and conduct investigations using standard science practices. However, an inquiry-based approach involves a high level of knowledge and engagement on the part of the teachers and students. Teachers often feel unprepared because they are lacking authentic scientific research and inquiry experiences themselves (Nadelson et al. 2012 ). They harbor misconceptions about hands-on instruction, viewing a series of tasks and lab activities as being equivalent to scientific inquiry. However, practical and procedurally based hands-on activities are not equivalent to true science inquiry but must include “minds-on” experiences embedded within constructivist approaches to science learning (National Research Council 1996 , p. 13). Students can become drivers of their learning when given the opportunity to construct their own questions related to the science content they are investigating. Key to effectively preparing teachers to teach through inquiry requires improving their pedagogical content knowledge while experiencing authentic science investigations and experimentation practices. Powell-Moman and Brown-Schild ( 2011 ) note that “in-service teachers see direct benefits when scientist-teacher partnerships associated with professional development are used to develop content knowledge, along with scientific process and research skill through collaboration on research projects” (p. 48).

Pulley #3: technological literacy

Fully understanding the “T” in STEM education seems to escape many educators who fail to move beyond merely the use of educational technology to enhance STEM learning experiences (Cavanagh 2008 ). STEM educators with only this view point fail to acknowledge that technology consists of a body of knowledge, skills, and practices. The term technology means so many different things to people rendering the term almost useless, and further study of technology definitions will not bring clarity to the subject (Barak 2012 ). Herschbach ( 2009 ) suggested there are two common views of technology; an engineering view of technology and a humanities perspective of technology. The engineering view , also referred to as the instrumental perspective (Mitcham 1994 ; Feenberg 2006 ), indicates that “Technology is equated with the making and using of material objects—that is, artifacts” (p. 128). However, the humanities view of technology focuses on the human purpose of technology as a response to a specific human endeavor; therefore, it is the human purpose that provides additional meaning for technology (Achterhuis 2001 ; Mitcham 1994 ). The humanities view of technology recognizes that technology is value-laden (Feenberg 2006 ) and thus, provides opportunities to explore technology impacts including cultural, social, economic, political, and environmental ( ITEA 2000 ).

Table  1 provides critical elements of distinction between these two views of technology.

Mitcham ( 1994 ) combines these two views together when he identified four different ways of conceptualizing technology. He identifies technology as (a) objects, (b) knowledge, (c) activities, and (d) volition. Often, people associate technology as artifacts or objects; unfortunately, many only view technology in this way and overcoming this limited view of technology may be critical for teaching STEM in an integrated approach. Mitcham also contends that technology consists of specific and distinct knowledge and therefore is a discipline. He views technology as a process with activities that include designing, making, and using technology. Technology as volition is the concept that technology is driven by the human will and as a result is embedded within our culture driven by human values. Herschbach ( 2009 ) contends that technology leverages knowledge from across multiple fields of study. DeVries ( 2011 ) in Barak ( 2012 ) writes:

Engineering can differ from technology in that engineering only comprises the profession of developing and producing technology, while the broader concept of technology also relates to the user dimension. Technologists, more than engineers, deal with human needs as well as economic, social, cultural or environmental aspects of problem solving and new product development. (in Barak 2012 , p. 318)

Barak ( 2012 ) suggests that both engineering and technology are so closely related that they should be taught in unison within technology education and suggests teaching them as one school subject called Engineering Technology Education (ETE).

In 2000, the International Technology Education Association (ITEA) drafted the Standards for Technological Literacy : Content for the Study of Technology (STL) to define the content necessary for K-12 students to become technologically literate citizens living in the twenty-first century. The STLs have been revised twice ( ITEA 2002, 2007 ) and also include student assessment and professional development standards (ITEA 2003 ). The Standards for Technological Literacy identify content standards for grades K-12 that provide students opportunities to think critically about technology beyond technology as an object and in doing so prepare students to become technologically literate. STEM educators should provide students opportunities to think through technology as a vehicle for change with both positive and negative impacts on culture, society, politics, economy, and the environment.

Pulley #4: mathematical thinking

Studies have shown that students are more motivated and perform better on math content assessment when teachers use an integrated STEM education approach. A recent study found that students performed better on post math content assessments and increased STEM attitudinal scores when engaging in learning activities that included engineering design and prototyping solutions using 3D printing technology (Tillman et al. 2014 ). Williams ( 2007 ) noted that contextual teaching can give meaning to mathematics because “students want to know not only how to complete a mathematical task but also why they need to learn the mathematics in the first place. They want to know how mathematics is relevant to their lives” (p. 572). Incorporating STEM practices that include mathematical analysis necessary for evaluating design solutions provide the necessary rational for students to learn mathematics and see the connections between what is learned in school with what is required in STEM career skills (Burghardt and Hacker 2004 ). The authors again acknowledge that not all secondary education math content can be applied to engineering design approaches. Similarly, secondary education students may not have the cognitive development necessary to connect mathematical thinking within all engineering design problems.

The rope: a community of practice

Additionally, the concept of learning as an activity not only leverages the context of the learning but also the social aspect of learning. Lave and Wenger ( 1991 ) describe this as legitimate peripheral participation when the learning takes place in a community of practitioners assisting the learner to move from a novice understanding of knowledge, skills, and practices toward mastery as they participate “in a social practice of a community” (p. 29).

In a community of practice, novices and experienced practitioners can learn from observing, asking questions, and actually participating alongside others with more or different experience. Learning is facilitated when novices and experienced practitioners organize their work in ways that allow all participants the opportunity to see, discuss, and engage in shared practices. (Levine and Marcus 2010 , p. 390)

Integrated STEM education can create an ideal platform to blend these complementary learning theories by providing a community of practice through social discourse. As educational leaders have wrestled with the concept of integrating STEM disciplines, key elements of situated learning have emerged. For example, Berlin and White ( 1995 ) argued that efforts to integrate mathematics and science should be founded, in part, on the idea that knowledge is organized around big ideas, concepts, or themes, and that knowledge is advanced through social discourse.

When engaging students into a community of practice, we suggest that the learning outcomes be grounded in common shared practices. Community of practice can provide opportunity to engage local community experts as STEM partners such as practicing scientists, engineers, and technologists who can help focus the learning around real-life STEM contexts regardless of the pedagogical approach.

Using a community of practice approach to integrated STEM can be challenging for teachers as they need to continually network with experts and be open to allowing members of the community of practice into their classroom. Additionally, not all students learn best in social settings so these students may struggle to fully engage in a community of practice and this may limit their ability to learn using this educational approach.

STEM community of practice

The Next Generation Science (NGS) Framework (NRC 2012 ) carefully uses language that describes common practices of scientist and engineers. These practices become science learning outcomes for students. Equally important to learning science concepts, scientific practices and skills are also emphasized as key outcomes (NRC 2012 ). Engineering practices are also identified within the NGS framework because some of the practices of scientists and engineers are shared. An integrated STEM approach can provide a platform through a community of practice to learn the similarities and differences of engineering and science. Table  2 shows descriptions of common science practices and engineering practices providing opportunity to compare similarities and differences (NRC 2012 ).

The study of STEM practices can provide a better understanding of each domain and help teachers identify key learning outcomes necessary to achieve STEM learning. Table  3 below identifies key practices that build the unique set of knowledge, skills, as well as a unique language to form common practices of science and technology while investigating and solving problems (Kolodner 2002 ).

Table  4 identifies the math standards for math practice located in the Common Core standards for mathematics identifying common practices necessary when solving mathematical problems. Understanding these mathematical practices can be critical for effective integrated STEM education because mathematical analysis can be found in all the other STEM domains.

Upon review of these practices across science, engineering, technology, and mathematics, the very nature of these disciplines as well as the context in which the practices occur provide the learner with authentic examples that could help to illustrate crosscutting STEM connections. Locating intersections and connections across the STEM disciplines will assist STEM educators who understand these practices and how they are uniquely similar and different. An integrated STEM approach should leverage the idea that STEM content should be taught alongside STEM practices. Both content and practices are equally important to providing the ideal context for learning and the rationale for doing so. Locating crosscutting practices will help students identify similarities in the nature of work conducted by scientists, technologists, engineers, and mathematicians and could help students make more informed decisions about STEM career pathways.

Integrated STEM research agenda

The proposed conceptual framework must be tested through educational research methods to determine if these concepts improve the teaching and learning of STEM content. A research agenda must be crafted to test theories under a variety of conditions to determine the best approach to integrated STEM. In the USA, the Committee on Integrated STEM Education developed several recommendations directed at multiple stakeholders in integrated STEM education including those designing initiatives for integrated STEM, those developing assessments, and lastly for educational researchers (NAE and NRC 2014 ). For further investigation in integrated STEM education, researchers need to document in more detail their interventions, curriculum, and programs implemented, especially how subjects are integrated and supported. More evidence needs to be collected on the nature of integration, scaffolding used, and instructional designs applied. Clear outcomes need to be identified and measured concerning how integrated STEM education promotes learning, thinking, interest, and other characteristics related to these objectives. Research focused on interest and teacher and student identity also needs to address diversity and equity, and include more design experiments and longitudinal studies (NAE and NRC 2014 ). Though these recommendations were made in the context of the American education system, they could prove helpful in many other countries’ educational systems as well.

One example: Teachers and Researchers Advancing Integrated Lessons in STEM (TRAILS)

A current National Science Foundation I-TEST project can serve as an example of research created to assess the proposed framework. Todd Kelley is the principal investigator of the TRAILS project that aims to improve STEM integration in high school biology or physics classes and technology education classes. TRAILS partners science and technology teachers during a 2-week summer professional development workshop to prepare the teachers to integrate STEM content through science inquiry and engineering design in the context of entomology. 3D printing technology is used to allow students to create engineering designed bio-mimicry solutions. Students’ use mathematical modeling to predict and assess design performance. Lessons are created to address technological literacy standards and well as math and science standards. The goals of the TRAILS project are as follows:

Goal 1: Engage in-service science and technology teachers in professional development building STEM knowledge and practices to enhance integrated STEM instruction.

Goal 2: Establish a sustainable community of practice of STEM teachers, researchers, industry partners, and college student “learning assistants.”

Goal 3: Engage grades 9–12 students in STEM learning through engineering design and 3D printing and scanning technology.

Goal 4: Generate strategies to overcome identified barriers for high school students in rural schools and underserved populations to pursue careers in STEM fields.

The TRAILS project research will be guided by assessing the following:

Science and technology education teacher’s self-efficacy in teaching STEM through an integrated STEM approach.

Assessing students and teacher’s awareness of STEM careers.

Assess students’ ability to use twenty-first century skills while creating engineering design solutions to TRAILS challenges.

Assess students’ growth in students’ STEM career interest, self-efficacy in learning STEM content, and growth in STEM content knowledge.

We theorize that teachers will increase self-efficacy teaching these subjects after participation in the TRAILS program, and this would indicate a stronger foundation for effective teaching (Stohlmann et al. 2012 ). Measurements of teacher self-efficacy parallels and extends the work of Nadelson et al. ( 2012 ), and additionally measures student self-efficacy in learning STEM. Self-efficacy is a good predictor of performance, behavior, and academic achievement (Bandura 1978 , 1997 ). Research projects like TRAILS provide researcher opportunities to explore the impact of an integrated STEM teacher professional development on teachers teaching practices as well as assess impact on students’ learning STEM content. TRAILS also focuses on how the project may impact students’ interest in STEM careers. This project serves as one example of how future research on integrated STEM teaching can assess teaching and learning of STEM content as well as help to identify barriers that exist in current educational systems. Projects like TRAILS are needed to help inform educational researchers and the greater STEM education community what works effectively and what does not when integrating STEM subjects in secondary education. The proposed theoretical models need to be tested and vetted within the STEM education greater community. The current TRAILS project provides an ideal platform to conduct research on this approach to integrated STEM to seek to identify the benefits as well as limitations.

Conclusion and implications

The recent STEM education literature provides rationale to teach STEM concepts in a context which is most often delivered in project, problem, and design-based approaches (Carlson and Sullivan 1999 ; Frykholm and Glasson 2005 ; Hmelo-Silver 2004 ; Kolodner 2006 ; Kolodner et al. 2003 ; Krajcik et al. 1998 ). It could prove helpful if integrated STEM educators learned the various “STEM languages” and STEM practices outlined above. The reality is secondary education in the US silo STEM subjects within a rigid structure with departmental agendas, requirements, content standards, and end-of-year examinations. If these barriers remain in education in the USA and in other nations, they may constrain the successful implementation of an integrated STEM program therefore jeopardizing the entire STEM movement.

The authors suggest that the key to preparing STEM educators is to first begin by grounding their conceptual understanding of integrated STEM education by teaching key learning theories, pedagogical approaches, and building awareness of research results of current secondary STEM educational initiatives. Furthermore, professional development experiences for in-service teachers could also provide a strong conceptual framework of an integrated STEM approach and build their confidence in teaching from an integrated STEM approach. Kennedy and Odell ( 2014 ) indicated that STEM education programs of high quality should include (a) integration of technology and engineering into science and math curriculum at a minimum; (b) promote scientific inquiry and engineering design, include rigorous mathematics and science instruction; (c) collaborative approaches to learning, connect students and educators with STEM fields and professionals; (d) provide global and multi-perspective viewpoints; (e) incorporate strategies such as project-based learning, provide formal and informal learning experiences; and (f) incorporate appropriate technologies to enhance learning.

Finally, further research and discussion is needed on integrated STEM education so that effective methodologies can be implemented by teachers in the classroom and further assess the strategies this overall framework proposes here (Stohlmann et al. 2012 ). The TRAILS project feature above is just one example of funded research that seeks to better identify the best conditions to teach STEM subjects in an integrated approach to teaching as well as learn what level of support students and teachers require to improve STEM education.

NSF disclaimer

Elements of this paper are supported by the National Science Foundation, award #DRL-1513248. Any opinions and findings expressed in this material are the authors and do not necessarily reflect the views of NSF.

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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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Okamura, K. Interdisciplinarity revisited: evidence for research impact and dynamism. Palgrave Commun 5 , 141 (2019). https://doi.org/10.1057/s41599-019-0352-4

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Integrated Studies Research Review: Evidence-Based Practices and Programs

Evidence points to seven key approaches to integrating curricula that have been shown to be effective.

In this section, we describe seven approaches to integrating subjects, along with recommended practices and programs that have been shown to benefit learning:

Science and Literacy

Science and the environment, science, technology, engineering, and math, financial literacy, arts integration across all subjects, internships and service learning, second-language learning and global competency.

It's not enough just to know about science; scientists also have to be able to describe their observations, explain what they know, and debate with others, using sound evidence and reasoning. When science and literacy lessons are integrated, students demonstrate greater skill in all of these areas ( Cervetti, Pearson, Barber, Hiebert, and Bravo, 2007 ).

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Programs and Outcomes

• Seeds of Science/Roots of Reading (Seeds/Roots) is an integrated science and literacy program that involves elementary students in researching and writing about scientific topics. In the Seeds/Roots unit on shoreline science, second and third graders learn about the properties of sand and other earth materials, as well as erosion, organisms' environments, and human impact on the environment. An independent study found that students participating in Seeds/Roots showed significant improvement in science vocabulary, content knowledge, and writing ( Goldschmidt and Jung, 2010 ). Teachers also reported that the Seeds/Roots program was usable, effective, and engaging (Goldschmidt and Jung, 2010).
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• Concept-Oriented Reading Instruction (CORI) is a model for relevant reading instruction that can be used in social studies and science. It is an instructional program for grades 3-8 that merges reading instruction with hands-on science activities. The program teaches students a wide range of skills, from reading about science topics to developing science inquiry skills like observation, data collecting, and drawing conclusions. A recent study of 1,159 sixth-grade students using both a correlational and a quasi-experimental approach found that students participating in a CORI program (who had had traditional reading lessons) showed higher motivation, engagement, and achievement compared to students in a traditional reading/language arts program alone ( Guthrie, Klauda, and Ho, 2013 ).

Edutopia Case Study

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• Situating science in society to help students learn to use their knowledge of scientific concepts and processes to make decisions, participate in civic and cultural affairs, and contribute to economic productivity
• Expeditionary learning is an EBE program that has had a positive impact on student learning across schools in multiple states ( Borman, Hewes, Overman, and Brown, 2003 ). Expeditionary learning programs incorporate local communities and environments to enhance student learning through interdisciplinary, collaborative, project-based learning activities. An analysis of six studies found that expeditionary learning programs have a significantly positive effect on student achievement (Borman et al., 2003).
• Students who participated in garden-based learning programs showed higher test scores in science and increased food knowledge ( Blair, 2009 ; Klemmer, Waliczek, and Zajicek, 2005 ; Ratcliffe, Merrigan, Rogers, and Goldberg, 2009 ; Smith and Motsenbocker, 2005 ). Garden-based learning has been linked with higher levels of science achievement (Blair, 2009; Klemmer et al., 2005; Smith and Motsenbocker, 2005) and an increased willingness to try a variety of vegetables (Ratcliffe et al., 2009).

Edutopia Case Studies

• King Middle School , in Portland, Maine, has students engage in expeditionary learning activities throughout the school year. In their " Soil Superheroes " activity, students met with local community members, scientists, and a comic book artist to learn how to produce a pamphlet on the role of bacteria in the health of soil. They approached the project as a real-world issue that required the integration of science, art, multimedia, math, and language arts to develop the pamphlet.
• The Edible Schoolyard Project at Martin Luther King Junior Middle School , in Berkeley, California, helps students learn various subjects through weekly activities at the school garden.
• The Wetland Watchers program at Hurst Middle School in Destrehan, Louisiana, is part of a schoolwide emphasis on service learning, combining activities designed to serve the community (from environmental-protection measures to volunteering at nursing homes) with specific learning objectives based on grade-level standards.
• School of Environmental Studies in the Minneapolis-St. Paul suburb of Apple Valley embraces project learning with an environmental theme. Learning is about becoming an expert and solving real problems. Students are expected to do in-depth, interdisciplinary research using innovative technology that results in practical applications.
• Hood River Middle School , in Hood River, Oregon, makes learning relevant and engaging by turning the school’s local geography, culture, history, and economy into classroom lessons. Using place-based learning, students get to see the results of their work in their community and gain a better understanding of themselves, as well as their place in the world.
• Walter Bracken STEAM Academy Elementary School , in Las Vegas, Nevada, transformed 32,000 square feet of dry grass into a student-centered, garden-learning wonderland. In addition to tending to the garden, students also learn how to create a business from their vegetable gardens. Within a 12-week period of running the farmers’ market, they learn how to write a business plan, create profit-and-loss sheets, and run advertising campaigns.

Specialty schools devoted to the integration of science, technology, engineering, and math (STEM) have existed in the United States since the 1930s ( Means, Confrey, House, and Bhanot, 2008 ). They generally focus on middle school and high school curricula that provide hands-on, project-based activities, as well as internship and mentorship opportunities and career and technical training (Means et al., 2008). STEM schools aim to promote a future STEM workforce and maintain the U.S. position as a leader in innovation. According to the National Research Council (2011) , U.S. advances in science and technology account for "more than half of the tremendous growth to per capita income in the 20th century."

• Connecting science, technology, engineering, and math subjects to real-world projects and careers
• Hands-on, project-based activities
• Independent research projects
• Internship and mentorship opportunities
• Middle school and high school students participating in an integrated science, technology, and math curriculum showed improved attendance and improved math and science achievement on assessment tests ( Satchwell and Loepp, 2002 ; Wicklein and Schell, 1995 ).
• Studies have shown that integrating science, technology, and math can enhance learning and instructional quality over traditional methods by using hands-on inquiry-science activities and projects and by providing sustained professional learning supports (Satchwell and Loepp, 2002; Wicklein and Schell, 1995).
• Science investigations that involve active thinking and drawing conclusions from data are more likely to increase conceptual understanding as compared to more passive learning methods ( Minner, Levy, and Century, 2010 ).
• Activity-based science allows students to develop stronger process skills and achieve gains in creativity, intelligence, language, and math ( Bredderman, 1983 ).
• MC 2 STEM High School , in Cleveland, Ohio, demonstrates how a successful high school integrates internships, service learning, college credit, and project-based learning. Community partnerships provide tutoring and mentoring, increasing the social support for student learning. Their capstone projects are developed using a field-tested process model for designing project-based learning curricula that integrate multiple subjects and industry standards.
• High Tech High , in San Diego, California, demonstrates how integrated studies, project-based learning, and technology integration promote engagement and learning. Hands-on projects at this textbook-free STEM school incorporate multiple subjects and span several weeks. For example, in a team-taught biology/multimedia art course, students created informational videos about blood-related health issues, and then displayed their videos on laptops as art pieces at a local gallery to raise health awareness and to benefit the local blood bank.
• Charles R. Drew Charter School , in Atlanta, Georgia, uses design thinking to teach engineering concepts to elementary students. Watch the school’s engineering lab and Tinker Yard in action, where students do design-and-build projects to learn lifelong critical thinking and problem-solving skills.

For research findings on ways to integrate technology in science contexts, don't miss Edutopia's research review of technology integration practices for inquiry science .

Adults appear to learn best when financial education is personalized and can be applied to real-life situations, for example, when individuals need to accomplish a personal goal such as purchasing a home or saving for retirement ( Hirad and Zorn, 2001 ; McCormick, 2009 ). Since K-12 students tend to lack such financial goals, getting them familiar and interested in finance is key. Teaching financial literacy in schools from the earliest grades can help establish a foundation to build upon (McCormick, 2009).

• Curriculum linked to analysis and critical thinking
• Stock market game in middle school or high school
• People learn financial concepts best when they're motivated and taught through activities such as a stock market game or other simulation ( Mandell and Klein, 2007 ).
• Students who play a stock market game in class outperform average levels on financial-literacy survey measures ( Mandell, 2008 ).
• Understanding of financial concepts is maximized when financial education is personalized and applied to real-life learning situations (Hirad and Zorn, 2001; McCormick, 2009).
• Ariel Community Academy , in Chicago, Illinois, shows how financial literacy can be integrated across subjects by teaching decision-making skills in real-world financial contexts and by having upper-elementary and middle school students invest in the stock market and create an investment portfolio that reflects their values as a final project.
• Walter Bracken STEAM Academy Elementary School, in Las Vegas, Nevada, created the “Piggy-Bank Friday” program to help students learn how to manage money. Students set up a real bank account, make weekly deposits with bankers at their school, track their balances, and receive monthly financial literacy lessons. Through the program, students have saved over $30,000 in one year.

Music, drama, dance, and visual arts can be integrated with any subject. Research has shown that arts integration engages students in learning, reduces misbehavior, strengthens community, and can improve test scores, particularly among at-risk youth, ( Catterall, Dumais, and Hampden-Thompson, 2012 ; Upitis, 2011 ; Smithrim and Upitis, 2005 ; Walker, McFadden, Tabone, and Finkelstein, 2011 ). Numerous arts integration programs provide professional-development training and support, including several with evidence of success such as those below.

• Integrating arts such as music, dance, art, or theater into social studies, math, science, and English classes
• Specialized tutoring focused on transferring art skills to other academic subjects
• Arts integration may improve learning by leveraging mental activities shown to help long-term memory, such as rehearsal of meaning, pictorial representation, and information generation ( Rinne, Gregory, Yarmolinskaya, and Hardiman, 2011 ).
• Students participating in arts-integrated lessons show increased language and math scores on standardized tests and improved engagement, motivation, and sense of community (Smithrim and Upitis, 2005).
• Students participating in arts-integrated curricula reported enjoyment and interest in their schoolwork ( Barry, 2010 ; Hendrickson and Oklahoma A+ Schools, 2010 ; A+ Research and Results page ).
• Arts integration is effective for students at risk of school failure ( Oreck, 2004 ).
• A four-year study paired teaching artists with 4th, 5th, and 6th grade teachers in six schools to example the impact it would have on student academic performance. These arts-integrated schools had higher test scores and a narrowing of the achievement gap, when compared to similar schools ( Burnaford and Scripp, 2012 ).
• A study of nearly 900 4th and 5th grade students in 32 schools found that students who participated in arts-integrated classrooms were more creative, engaged, and effective at problem solving than students who didn’t participate in arts-integrated classrooms ( Chand O’Neal, 2014 ).
• A literature review examined 18 empirical studied published between 2000-2015 and found that arts participation helped young children develop social skills (such as helping, sharing, caring, and empathizing with others) and emotional self-regulation ( Menzer, 2015 ).
• Learning Through the Arts (LTTA) pairs specially trained artists with teachers to create innovative, arts-based lessons that are exciting and relevant to students. LTTA is one of the largest school programs, having reached over 377,000 students. A rigorous three-year study on LTTA found several positive outcomes for students, including increased engagement and motivation to learn, increased sense of community, increased math computation and estimation performance for sixth graders, and increased happiness with coming to school among sixth-grade girls (Smithrim and Upitis, 2005). An example lesson plan uses dance to explore how animals live, hunt, and survive in their environment.
• A+ Schools Program is a large whole-school reform model bringing arts integration to schools. A+ programs integrate arts (e.g., dance, drama, music, visual art, and creative writing) in daily instructional practices, focusing on alignment with state standards, while providing teacher-created lessons and professional learning support. A five-year longitudinal evaluation of Oklahoma schools found improved student achievement, as well as better attendance, in the A+ schools as compared to traditional schools (Hendrickson and Oklahoma A+ Schools, 2010; Barry, 2010). Research on A+ schools in North Carolina and elsewhere also shows consistent gains in statewide reading and math test scores (Nelson, 2001; Barry, 2010; A+ Research and Results page).
• Opening Minds Through the Arts (OMA) supports arts instruction in grades K-3, providing opportunities for students to create, perform, and respond to the arts. WestEd conducted a three-year longitudinal, quasi-experimental study of three OMA schools and two comparison schools. After three years of participation in OMA, third-grade students scored significantly higher on reading, language arts, and mathematics standardized tests as compared to their counterparts in comparison schools (WestEd).
• Project START ID (Statewide Arts Talent Identification and Development) integrated dance, music, theater, and art in Ohio elementary schools. In the program, artists worked with teachers to develop arts-infused lessons that allowed students to use their artistic strengths and skills to learn and express their knowledge in the classroom. A three-year study on Project START ID found that the teaching methods successfully reached students who were at risk for school failure and that students were able to develop and use their effective learning behaviors in the academic classroom ( Oreck, 2004 ).
• Wiley H. Bates Middle School , in Annapolis, Maryland, is a fully arts-integrated middle school that has shown strong improvements in student achievement. Every teacher is trained in arts integration, and they track student performance in lessons taught through arts integration. Check out the Lesson Plans and Resources for Arts Integration provided by the educators at Bates.
• Charles R. Drew Charter School, in Atlanta, Georgia, is a STEAM (science, technology, engineering, arts, and math) school, and project-based learning is their instructional delivery method. By integrating PBL and STEAM, they empower students to take ownership of their education. In this case study, learn how students integrate multiple subjects to answer the question, "How can we better prepare for Atlanta's changing weather?"
• Walter Bracken STEAM Academy Elementary School , in Las Vegas, Nevada, engages students by letting them choose outside-the-box enrichment classes, like toy making, drones, and candy chemistry. These classes, called Explos (short for explorations), allow teachers to get creative with developing Science, Technology, Engineering, Art, and Math (STEAM) lessons.

The dropout-prevention literature emphasizes the importance of making school relevant to students' lives and ensuring that school is engaging and challenging. In a 2006 survey of students who dropped out of high school, 81 percent said that if schools provided opportunities for real-world learning, including internships and service learning, their chances of graduating from high school would have been greater ( Bridgeland, Dilulio, and Morison, 2006 ). The study also found that clarifying the links between finishing school and getting a job may convince more students to stay in school (Bridgeland et al., 2006).

• Providing a context for learning and promoting college and career training by placing students in internships in local organizations and businesses
• Allowing students to explore careers and connect with adults who can serve as role models and mentors through internships and work-based learning programs
• Integrating community service with academic study through service learning; students typically identify community needs (such as recycling, health awareness, or pollution) and develop services to address those needs
• Aligning service activity with academic goals and providing an opportunity for student reflection and celebration
• Creating opportunities for authentic learning through service learning, challenging students to study real problems in real time for real people, with real goals and consequences ( Furco, 2010 )
• Graduates of career-themed high schools that emphasized the connection between school and getting a good job earned on average about 11 percent more per year eight years after graduating as compared to graduates of traditional high schools ( Stern, Dayton, and Raby, 2010 ).
• Students participating in workplace mentoring and internships have improved grades, comparable or better attendance, and higher graduation rates than students in comparison groups, as well as increased motivation, self-confidence, and career-planning skills ( Hughes, Bailey, and Karp, 2002 ).
• Nearly 70 studies on service learning indicate that service-learning programs have a positive impact on students' academic, civic, personal, social, ethical, and vocational development ( Furco and Root, 2010 ).
• Students participating in service learning show increased academic performance, attendance, motivation, and self-esteem and reduced disciplinary problems and likeliness to drop out ( Billig, 2010 ; Furco, 2010; Furco and Root, 2010).
• Students participating in civic-learning opportunities such as learning about current events or participating in service-learning projects showed increased commitment to volunteering and willingness to learn about state and local issues ( Kahne and Sporte, 2008 ).
• Service learning engages students in local community issues, provides students with autonomy and opportunities for self-expression, encourages teamwork, teaches time management, and rewards students for goal attainment (Billig, 2010).
• Service learning increases student motivation by focusing on problem-solving skills, active learning, and student choices in instructional settings (Billig, 2010).
• Kids Voting USA is a program that includes classroom activities such as constructing an election bulletin board where students share election news, mapping out government services provided to households (such as public parks, libraries, transportation, and police), and discussing potential voting barriers such as polling hours, location, and voter registration. Students who participated in Kids Voting USA increased their political knowledge and reported that they felt better equipped to make political decisions that reflected their attitudes ( Meirick and Wackman, 2004 ).
• Francisco Bravo Medical Magnet High School , in Los Angeles, California, has medical internships at local organizations. Some students volunteer at the University of Southern California's University Hospital, some intern at local dentists' offices, while others collaborate side by side with researchers at USC's Keck School of Medicine, working on research projects like developing new cancer drugs and prosthetic retinas.
• Fowler Unified School District , in California's Central Valley, raised trout to protect local habitats, grew fruits and vegetables in an outdoor garden, collected sunscreen and lip balm to protect field workers from overexposure to the sun, and built construction projects to benefit the district and town. In each case, teachers connected service learning to academics, giving students an opportunity to apply math, science, English language arts, and social studies to their service-learning projects.
• Montpelier High School , in Montpelier, Vermont, focuses on student interest by creating internship opportunities that are designed to connect academic learning to the real world. Students work with local organizations, businesses, and individuals to craft an internship that allows them to explore their interests, learn skills, and work collaboratively with the organization.
• High Tech High School , in North Bergen, New Jersey, offers students several vocational majors including architecture, engineering, culinary arts, graphic design, film/video, science research, theater, and dance. For any project within a vocational major, teachers and students include relevant content from other subject areas to enhance real-world connections.
• Language immersion for 50 percent of school time throughout the duration of the program
• Global competency curriculum focusing on preparing students for a globalized future and emphasizing creativity, life skills, and higher-order thinking skills such as reasoning and problem solving
• Research suggests that learning languages at earlier ages and over longer periods of time support second-language acquisition ( Tochon, 2009 ).
• According to a meta-analysis of 63 studies, bilingualism produces a range of benefits, including increased ability to control attention and keep information in memory, better awareness of language structure and vocabulary in language, and improved skills in creative thinking and problem solving ( Adesope, Lavin, Thompson, and Ungerleider, 2010 ).
• Bilingual students also attain higher levels of achievement on standardized tests in reading, writing, social studies, and math and report higher levels of self-confidence (Tochon, 2009).
• Students in language-immersion schools demonstrate high levels of academic achievement and do as well as or better than English-only learners on standardized tests. These benefits extend to English-language learners as well as native English speakers ( Gómez, Freeman, and Freeman, 2005 ; Palmer, 2009 ; Thomas and Collier, 2002 ).
• Asia Society's International Studies Schools Network (ISSN) currently includes 34 schools that integrate global perspectives and give students the opportunity to study one or more languages. Across the ISSN network, which predominantly serves students from economically disadvantaged backgrounds, approximately 92 percent of students graduate from high school on time, and among those, more than 90 percent go on to college ( Wiley, 2012 ).
• John Stanford International School , in Seattle, Washington, shows how an internationally themed immersion curriculum is producing high levels of student learning and achievement. John Stanford International School's curriculum involves learning not just a second language but also about as many cultures as possible. The school's emphasis on global competency was inspired by the book Educating for Global Competence , which describes curricular components of Asia Society's ISSN.

Continue to the next section of the Integrated Studies Research Review, Avoiding Pitfalls .

Integrated Studies Research Table of Contents:

• Definition and Outcomes
• -->Evidence-Based Practices and Programs -->
• Table of Evidence-Based Practices and Programs
• Avoiding Pitfalls
• Annotated Bibliography

Research Integrated Science Education

SENS Research Foundation recognizes the challenges that will face high school biology teachers in the upcoming academic year. Through a generous grant from Dalio Philanthropies, SRF has launched the Research Integrated Science Education (RISE) Program, which will provide distance-friendly lessons supported by high quality video explanations, interactive student activities, and discussion-based slides.

The RISE Program will focus on integrating experimental design and data interpretation concepts into high school biology curriculum. The first set of lessons has been designed around one overarching module phenomenon but they have also been created with an eye to flexibility of use as well. All of the content has been developed to make it simple to incorporate specific videos, slides, and activities into your existing biology curriculum without needing to utilize the entire module. We envision the content being immediately adaptable to distance learning and hybrid learning paradigms and ultimately as a complement to hands-on laboratory exercises when full access to classrooms resumes.

The first module will introduce students to COVID-19 and explore how the seemingly disparate clinical manifestations of the disease can be explained by a single mechanism at a molecular level. A series of background videos, interactive activities, and discussion slides will prepare students to evaluate published COVID-19-related research publications.

The second module will explore the phenomenon of cellular senescence and its proposed role in aging and disease. The series of background videos, interactive activities, and discussion slides will help students to evaluate published senescence-related research publications.

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U.S. Geological Survey Climate Science Plan—Future Research Directions

• Document: Report (6.56 MB pdf)
• Download citation as: RIS | Dublin Core

Executive Summary 

Climate is the primary driver of environmental change and is a key consideration in defining science priorities conducted across all mission areas in the U.S. Geological Survey (USGS). Recognizing the importance of climate change to its future research agenda, the USGS’s Climate Science Steering Committee requested the development of a Climate Science Plan to identify future research directions. Subject matter experts from across the Bureau formed the USGS Climate Science Plan Writing Team, which convened in September 2022 to identify and outline the major climate science topics of future concern and develop an integrated approach to conducting climate science in support of the USGS and U.S. Department of the Interior missions. The resulting USGS Climate Science Plan identifies three major priorities under which USGS climate science proceeds: (1) characterize climate change and associated impacts, (2) assess climate change risks and develop approaches to mitigate climate change, and (3) provide climate science tools and support. The Climate Science Plan identifies 12 specific goals to achieve the outcomes of the three priorities.

• Conduct long-term, broad-scale, and multidisciplinary measurements and monitoring and research activities to define, quantify, and predict the impacts of climate change on natural and human systems;
• Provide leadership to standardize measuring, monitoring, reporting, and verifying greenhouse gas emissions, lateral carbon fluxes, and carbon sinks across lands managed by the U.S. Department of the Interior (DOI);
• Provide science capacity, training, tools, and infrastructure to Tribal partners; support Tribal-led science initiatives;
• Conduct climate change research in partnership with the broader climate science community;
• Develop improved data synthesis methods through collaborative and open science across mission areas and between the USGS and agency partners;
• Translate climate change impacts into risk assessments in support of risk management strategies;
• Develop new and improved risk assessments, models, and approaches for mitigating climate change, adapting to its impacts, and reducing uncertainties; design early warning systems for risk mitigation;
• Investigate climate change mitigation strategies and create decision science support tools to inform climate change mitigation and adaptation;
• Provide a framework that facilitates knowledge co-production needed to inform policy decisions;
• Provide access to USGS data and information through novel integration and visualization approaches;
• Build capacity within USGS and DOI through development of scientific training curricula; and
• Coordinate science and capacity building efforts broadly across the Federal Government.

To achieve these goals, the USGS Climate Science Plan also outlines climate science guidelines—key elements for conducting climate-based research—as well as emerging opportunities to support successful climate science. The USGS Climate Science Plan provided in this circular will guide future research priorities and science-support investments, as well as continued development of the climate workforce for decades to come, ensuring that the USGS continues to serve as one of the Nation’s leading climate science agencies.

Suggested Citation

Wilson, T., Boyles, R.P., DeCrappeo, N., Drexler, J.Z., Kroeger, K.D., Loehman, R.A., Pearce, J.M., Waldrop, M.P., Warwick, P.D., Wein, A.M., Zeigler, S.L., and Beard, T.D., Jr., 2024, U.S. Geological Survey climate science plan—Future research directions: U.S. Geological Survey Circular 1526, 30 p., https://doi.org/10.3133/cir1526.

ISSN: 2330-5703 (online)

Table of Contents

• Executive Summary
• Introduction
• The USGS Leadership Role in Climate Science
• U.S. Geological Survey Climate Science Plan
• Acknowledgments
• References Cited
• Recommended Reading
• Appendix 1. Current Climate Science Activities in the U.S. Geological Survey
• Appendix 2. Goals, Strategies, Impacts, and Outcomes of the U.S. Geological Survey Climate Science Plan

A comprehensive review of energy harvesting technologies for sustainable electric vehicles

• Sustainable Technologies for Environmental Health and Safety
• Published: 06 September 2024

Cite this article

• Abhidnya Sunil Mhatre 1 &
• Prashant Shukla   ORCID: orcid.org/0000-0003-2271-818X 1  

This review paper provides a comprehensive examination of energy harvesting technologies tailored for electric vehicles (EVs). Against the backdrop of the automotive industry’s rapid evolution towards electrification and sustainability, the paper explores a diverse range of techniques. The analysis encompasses the strengths, weaknesses, applicability in various scenarios, and potential implications for the future of EVs. A key finding of the review highlights regenerative braking as a pivotal and highly efficient method for energy recovery, particularly in urban settings. In addition to extending battery life, regenerative braking significantly boosts energy efficiency of EVs. The paper also delves into the challenges associated with integrated solar energy systems, emphasizing issues related to efficiency and weather dependency. Kinetic energy recovery systems (KERS) are discussed for their substantial power boost during acceleration in both motorsports and road cars. Additionally, the review explores regenerative shock absorbers, which capture energy from suspension movement, enhancing ride comfort and increasing vehicle energy economy, especially on uneven terrain. The piezoelectric system, though intriguing, is found to have low power output from mechanical vibration, prompting further exploration for integration into EVs. However, complexities and cost considerations arise in their integration with the vehicle’s suspension system.

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Abhidnya Sunil Mhatre & Prashant Shukla

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Mhatre, A.S., Shukla, P. A comprehensive review of energy harvesting technologies for sustainable electric vehicles. Environ Sci Pollut Res (2024). https://doi.org/10.1007/s11356-024-34865-8

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