Abstract
Increasing calls for greater STEM-integrated experiences in K–12 education have spawned numerous studies on teacher beliefs, educational goals, and practices for teaching and learning. However, how the field proposes to support the development of teachers’ STEM-integrated disciplinary knowledge appears to be underresearched. In this systematic review, we analyzed 110 articles to determine (a) in what ways has the literature focused on teacher learning, (b) to what extent the literature addressed the development of teachers’ STEM-integrated disciplinary knowledge, and (c) to what extent the literature identified mechanisms for developing teachers’ STEM-integrated disciplinary knowledge. Results reveal needs that include, among others, more studies focused on developing teacher disciplinary knowledge; studies that differentiate teacher needs at different grade levels; studies that differentiate mechanisms aimed at developing teachers’ pedagogical knowledge, pedagogical content knowledge, and disciplinary knowledge; and studies that explicitly examine the mechanisms being used to support the development of teachers’ STEM-integrated disciplinary knowledge.
For more than two decades, the call for STEM (science, technology, engineering, and mathematics)–integrated experiences in K–12 education has spawned numerous studies and reviews to identify goals, practices, and potential outcomes for teaching and learning. Earlier efforts were motivated by arguments to increase global competitiveness and workforce capacities, as it became clear that innovation and economic development in the real world requires STEM-integrated knowledge (English, 2016; Martin-Paez et al., 2019; Zollman, 2012). More recent foci have included developing opportunities for all citizens to build competencies in STEM literacy that promote informed decision-making in our increasingly information-saturated world (Thibaut et al., 2018). Although what constitutes STEM-integrated learning has been somewhat contested (e.g., English, 2016; Martin-Paez et al., 2019), we use a definition of STEM integration proposed by Nadelson and Seifert (2017) for the K–12 context as an approach involving “conditions that require the application of knowledge and practices from multiple STEM disciplines to learn about or solve transdisciplinary problems” (p. 221). When implemented well, STEM-integrated experiences can improve student motivation, interest, and identity in STEM learning (National Academy of Sciences [NAS], 2014). Furthermore, students tend to demonstrate improved analytical, problem-solving, and transfer skills when learning through authentic STEM-integrated curricula (e.g., Zeng et al., 2018). These needs, along with the potential for improved learning, have compelled policy makers to set research agendas to focus on how to scale up efforts to reach broader educational audiences. For example, the NAS commissioned the 2014 report, STEM Integration in K-12 Education: Status, Prospects, and an Agenda for Research, that summarized the state of the field for this purpose.
The appearance of this report, a year after the release of the Next Generation Science Standards (NGSS) (NGSS Lead States, 2013), marked a pivotal moment in the history of U.S. science education standards. Although previous policy documents, for example, Science for All Americans and Benchmarks for Scientific Literacy (American Association for the Advancement of Science, 1989, 1993) included chapters on the integration of technology and engineering into science content, the NGSS made deliberate and explicit connections between science, technology, and engineering for all performance indicators. As written in the NGSS document, this heightened the centrality of integrating disciplinary knowledge:
A significant difference in the NGSS is the integration of engineering and technology into the structure of science education. From a practical standpoint, the Framework notes that engineering and technology provide opportunities for students to deepen their understanding of science by applying their developing scientific knowledge to the solution of practical problems. . . .[This converges] on the powerful idea that by integrating technology and engineering into the science curriculum, teachers can empower their students to use what they learn in their everyday lives. (NGSS Lead States, 2013, p. 3)
The ushering in of these new standards created opportunities (and constraints) for the corpus of science teachers in the United States who now had to develop disciplinary expertise in multiple domains. Writing around the same time, Wilson (2013) warned that professional development (PD) activities did little more than offer general instructional approaches to take back to the classroom. Ensuring high-quality teaching with the new NGSS standards would require significant investment in PD resources. Wilson further noted that researchers needed to develop a clear theory that could explain and measure teacher learning, citing research on the learning of content knowledge to increase teachers’ self-efficacy. She wrote,
Researchers have argued that teachers’ increased CK [content knowledge] leads to better self-efficacy. In turn, this increased efficacy leads to higher levels of persistence. Thus, teachers who increase their CK also improve their confidence, which leads to more motivation and perseverance as teachers learn to educate in fundamentally different ways. (p. 311)
The same issues would be true for mathematics teachers who were also explicitly challenged to integrate more STEM-oriented content into their curricula through the Common Core State Standards, which also spawned numerous studies (e.g., Coxon et al., 2018). But how easy would it be for science and math teachers to develop the knowledge and practices in several new disciplines for true STEM integration to take place in classrooms? If we consider the often-quoted claim by Ericsson (1993) that it takes many hours of deliberate practice to become an expert at anything, one might think that developing new disciplinary knowledge and practices is not so easy. If we further consider the need for developing teacher’s content knowledge and the knowledge for teaching raised by Shulman (1987) and other notable scholars since then, for exampel, Ball et al. (2008), we know that possessing deep understanding of disciplinary knowledge is critical for learning, and yet difficult to cultivate. Indeed, teacher knowledge of multiple STEM disciplines has been signaled as a challenge in enacting STEM-integrated curricula (Eckman, 2016; Nadelson & Seifert, 2017) due to the complexity involved in disciplinary knowledge integration. However, since the publication of the NAS report, it seems that little research has been conducted on how to support teacher disciplinary knowledge development.
Through a systematic review of empirical studies published from 2012 to 2021, our goal in this article is to investigate the state-of-the-art of teacher disciplinary knowledge development for STEM integration. By referring to disciplinary knowledge, we are focused on the knowledge base that Shulman (1987) and various scholars have referred to as content knowledge or subject-matter knowledge (e.g., Ball et al., 2008). These are the skills and concepts generated in disciplinary investigations of theories and practices that members of a discipline would undertake, for example, biologists or mathematicians. We are interested in the multiple ways that understanding of a discipline is developed using inquiry approaches (e.g., experimentation in science) in addition to the disciplinary concepts (e.g., evolution). We have selected disciplinary knowledge as the main focus of this review because STEM-integrated knowledge, as it is practiced in emerging real-world fields such as bioinformatics, does not have a canonical base of concepts and practices that may be readily understood by teachers. It would therefore be even more critical to develop disciplinary knowledge as a foundational knowledge base from which pedagogical content knowledge (how teachers translate disciplinary knowledge into instruction) and pedagogical knowledge (e.g., strategies for teaching such as curricular or classroom organization) is acquired and implemented. We are centrally interested in investigating the extent to which studies of STEM-integration have focused on disciplinary knowledge. This is the challenge that Shulman (1987) advocated for which was to identify a set of competencies that teachers would need to possess for high-quality instruction in the content areas that goes beyond pedagogical knowledge (Ball et al., 2008). In this review, we also investigate high school or secondary-level STEM teachers and studies because the siloed nature of classes at this level makes integration of another discipline even more challenging. Related to this point, we define STEM teachers as those who teach one or more of the science (e.g., biology, chemistry, physics), technology, engineering, or mathematics subjects (e.g., calculus, statistics) and define STEM studies as those that purport to integrate more than one of these subjects.
We begin this article by reviewing what the current research has focused on regarding elements of teachers’ knowledge and beliefs for STEM-integrated instruction and learning. The section that follows argues for the need for more research on how to support teachers’ disciplinary knowledge of STEM-integrated content and practices. Next, we describe the methods for narrowing down and reviewing empirical studies on teacher research in STEM-integrated teaching, and then we review the empirical studies. We conclude with recommendations for future research on how to improve teachers’ STEM-integrated disciplinary knowledge development.
Where Is the Research on STEM Integration and Developing Teachers’ Disciplinary Knowledge?
Despite the aforementioned promise of STEM-integrated learning, the NAS (2014) report outlined issues that constrain scale-up efforts and provided 10 recommendations for future research. These recommendations include greater attention to and documentation of the nature of integration and how it is supported in curricular programming; studies using rigorous research methods focused on student outcomes, including learning and access; developing a common definition and language for STEM education; and improving the delivery of STEM-integrated instruction. Numerous studies have focused on addressing these recommendations, including several literature reviews and commentaries of the field. English (2016), for example, argued for more balanced inclusion of each of the disciplines, suggesting that mathematics and engineering are underrepresented in studies of STEM-integrated approaches. Similar to the NAS report, she further highlighted the need for a stronger research base that offers substantive evidence of student improvement in desired learning outcomes. Martin-Paez et al. (2019) conducted a systematic review to investigate how the field defines STEM education and how integration has or has not been conducted in practice based on different definitions. Likewise, Thibaut et al. (2018) reviewed the literature on current instructional practices in secondary education, concluding with a summary of five key pedagogical principles to support classroom enactments (i.e., integration of STEM content, problem-centered learning, inquiry-based learning, design-based learning, and cooperative learning). These perspectives on the field appear to reflect a global trend, as Ritz and Fan (2015) pointed out that the development of a STEM agenda for K–12 has been a mission of many countries.
What appears to be conspicuously missing from the literature, in any discernable quantity, is how the field proposes to support the development of teachers’ STEM-integrated disciplinary knowledge. While most of the literature reviews acknowledge the importance and challenge of increasing competence and confidence in teachers’ STEM-integrated delivery of content and practices, there are seemingly few recommendations on how to achieve this goal. For example, the NAS (2014) report summarized well-known findings about the lack of STEM majors among the elementary and middle school teaching population but then simply recommended that teachers take more undergraduate coursework in STEM content areas. Although the focus of this review is on studies conducted at the high school level, we highlight this point because taking more undergraduate courses in STEM content areas (e.g., biology or engineering) does not address the problem of STEM-integrated knowledge. The report also discussed, at length, the importance of developing teachers’ pedagogical strategies that favor STEM-integrated learning, such as project-based learning and design-based approaches, for both pre-service and in-service teachers. Again, while the report acknowledged the critical influence of subject matter knowledge on the quality of STEM-integrated teaching, the authors devoted most of the space to highlighting successful studies that develop teachers’ pedagogies. They wrote, for example,
In one fairly representative study, Basista and Mathews (2002) describe a small-scale (22 teachers of grades 4–12) university-based professional development program on integrating mathematics and science. The authors report that a minimum duration of 3 weeks (contact time of 72 hours) was necessary to bring about significant shifts in teachers’ beliefs, pedagogical preparation, and subject content knowledge. Institute courses were team taught by science and mathematics educators, and teachers were “immersed” in inquiry-based learning environments where they worked on integrated science and mathematics units in cooperative groups of three or four. (p. 124)
It is clear from this description that the authors believe that working in collaborative inquiry-based PD can improve content knowledge. But rather than detailing how this knowledge was developed in the study, they focused only on pedagogy. This is problematic given that we know that lack of training in more than one scientific knowledge domain, and few examples of how to teach in an integrated way (Brand, 2020; Dare et al., 2018), both contribute to low teaching confidence outside of teachers’ core content areas (Kelley et al., 2016).
Other Reasons to Focus on Developing Teachers’ Disciplinary Knowledge?
Beyond STEM integration, there are broader reasons for why a focus on developing teacher disciplinary knowledge is critical in educating students who can participate either in STEM-integrated careers or as STEM-literate citizens. Goldman et al. (2016) made clear that to become disciplinarily literate in core K–12 content areas, educational experiences must reflect the multiple epistemological constructs of the discipline. These include beliefs about the nature of knowledge, inquiry practices and reasoning strategies, concepts and principles, representational forms, and discourse structures. They suggested that the nature of knowledge claims that are based in these epistemological constructs reflect deep disciplinary differences. If we consider the field of engineering, where the epistemic practice of design is at the center of the discipline, one must attend to the practical design of technologies as well as their internal workings, implementation, and use in social environments (Cunningham & Kelly, 2017; Pleasants & Olson, 2019). These ideas and skills are not trivial; engineers normally attend college for 4 years to acquire this type of understanding. How, then, do we expect science or math teachers to integrate engineering processes into their classrooms without a concerted effort to develop their disciplinary knowledge of engineering? This is true for all individual STEM fields that each represent rich, complex, and bounded disciplinary knowledge and practices (Goldman et al., 2016) that may not easily translate across disciplines.
Becoming disciplinarily literate and understanding the inquiry methods that produce reliable science claims has also been identified as vital to addressing posttruth beliefs spawned by antiscience rhetoric. One way to approach this conundrum in the classroom is to design and teach through authentic learning environments that make use of authentic information sources (Chinn et al., 2021). However, as previously noted, most science being conducted in the real world, such as disease epidemics or climate change research, requires STEM-integrated knowledge. To be able to evaluate the veracity of claims being made, for example, about the efficacy of a particular vaccine, or the exponential impact of human activity on global warming, one must have a decent understanding of data. This again presents a challenge for teachers who may never have taken a statistics course in their educational career (statistics and data literacy representing an example of a rapidly growing STEM-integrated field; see https://www.nsf.gov/news/special_reports/big_ideas/harnessing.jsp). We hypothesize that being able to accurately evaluate knowledge claims for many of our pressing socioscientific issues requires an added level of STEM-integrated understanding that teachers must have before they can confidently and competently work with their students. But this is not an easy task. Gorman and Gorman (2017) discussed the natural tendency for all of us to want to avoid complexity in learning something new, mainly because of the time and effort needed. They also discuss the fact that scientists and public health experts are largely unable to explain their findings in clear and convincing ways, leaving us susceptible to believing deliberately crafted misinformation. For teachers, these findings mean that it is even more important to develop disciplinary knowledge so that they can deliver curriculum knowing what is true and accurate about a topic.
With this increasing need to teach STEM content and practices in new, more complex, and more accurate ways, teachers must be able to adapt their routine expertise in teaching their standard curricula. Hatano and Oura (2003) discussed several essential characteristics of adaptive experts, chief of which is that they possess rich and well-structured domain knowledge that can be readily applied in unfamiliar tasks or contexts. They state that becoming an adaptive expert often takes years of experience in solving problems in the domain, with deliberate and intentional examination of practice. The research on developing adaptive expertise with teachers indicates that the complex nature of teaching requires orchestration of multiple classroom and student variables (e.g., Fairbanks, 2010; Tsui, 2009). Having deep disciplinary expertise can aid in this orchestration by freeing up teachers’ precious cognitive resources (needed to attend to content in the case of novices) to flexibly respond to emergent challenges in the classroom (Berliner, 2001). In our own research, we have investigated the extent to which teachers were able to demonstrate adaptive expertise teaching with STEM-integrated curricula in two different projects. In studies on instruction on integrating agent-based computational models to simulate complex biological systems, teachers’ varying levels of knowledge and practices pertaining to modeling did impact their instructional quality (Yoon et al., 2015). In a subsequent study, these varying levels of adaptive expertise were found to significantly influence student learning and participation outcomes (Yoon et al., 2019). In another set of studies investigating teachers’ adaptive expertise characteristics, in this case when integrating bioinformatics curricula into high school biology classrooms, we saw similar results except that the need for teachers to develop disciplinary expertise in the area of data literacy was even more pronounced (Yoon, Shim, et al., 2023). Finally, it is also well known that the STEM knowledge base of practicing teachers differs for different grade levels, with elementary school teachers needing the most support in classroom practice (National Academy of Science, 2014).
Given the importance of developing teachers’ disciplinary knowledge to enact STEM-integrated teaching and learning, it is clear that the field would benefit from a thorough review of the literature on the extent to which research has supported teachers and how best to support them.
Purpose of the Review
The purpose of this review is to examine the research that was conducted between January 2012 and April 2021 (when our team began the search for articles). We chose 2012 as a starting point because it was the year before the NGSS was launched, and around the time that both the NGSS Lead States (2013) and the NAS (2014) documents were being conceptualized. As previously noted, both documents include robust recommendations for STEM-integrated curriculum and instruction in the science classroom. Through a systematic review of the teacher learning and PD literature for STEM-integrated teaching at the high school level, we sought to investigate the following research questions:
In what ways has the literature focused on teacher learning (i.e., where has the main emphasis been placed for learning about and supporting teacher learning)?
To what extent has the literature addressed the development of teacher disciplinary knowledge for STEM integration?
To what extent does the literature provide guidance on mechanisms for developing teacher disciplinary knowledge for STEM integration?
We highlight themes that emerge from this group of studies that illustrate central areas of research focus. We also examine whether teachers’ disciplinary knowledge has been a focus of PD or classroom implementation, and how researchers have worked with teachers to develop their disciplinary knowledge.
Method
Literature Search Procedure
This systematic review drew from peer-reviewed journal articles of empirical studies in three databases: Education Resources Information Center (ERIC), Education Full Text, and PsycINFO. We selected these databases because they are the most common repositories for educational studies and previously published review articles with similar content have used them (e.g., Gerard et al., 2011; Yoon et al., 2018). For each database, a series of keyword searches was conducted. The first set of keyword searches began with the primary-level keyword STEM combined with each of the secondary-level keywords: (a) integrat*; (b) scien*; (c) math*; (d) tech*; (e) engineer*; (f) *disciplinary; (g) multidisciplin*; (h) interdisciplin*; and (i) transdisciplin*. A second set of keyword searches was conducted combining the primary keyword scien* with each of the secondary-level keywords: (a) math* AND integrat*; (b) tech* AND integrat*; (c) engineer* AND integrat*; (d) *disciplinary; (e) multidisciplin*; (f) interdisciplin*; and (g) transdisciplin*. This resulted in 16 keyword searches in each of the three databases.
Each keyword search was conducted in late April 2021, applying the inclusion criteria of (a) peer-reviewed and (b) published after January 1, 2012. The results of these searches can be found in Table 1. After the 48 searches were combined, placed into a spreadsheet software, and duplicates and non-English articles were removed, we were left with 46,104 articles. Next, to remove the significant portion of articles that came from journals in the medical and health fields, a search and removal was conducted on the journal titles for medical terms, including neuro*, brain, nurs*, medic*, health, oncolog*, psych*. All articles appearing in journals with any of those keywords in their title were removed from the sample, leaving 22,861 articles.
Literature search results
Three searches in PsycInfo included NOT “stem cell.”
Inclusion Criteria and Exclusion Criteria
To ensure that the articles were applicable to our goals and research questions, criteria were used to narrow the pool of articles. As our understanding of the field evolved, so too did the inclusion and exclusion criteria. This is mainly because STEM integration is a relatively new field with multiple perspectives on the idea of integration. For example, it is common to refer to the integration of instructional technologies or the integration of computers in the classroom, but these topics do not fit our goals. Thus, multiple rounds of exclusion criteria were applied.
Round 1: STEM Integration Across Ages and Context
The following inclusion criteria were initially applied: (a) at least two or more integrated STEM disciplines; (b) empirical research; (c) measuring student or teacher learning, knowledge, or beliefs; (d) K–12 context, formal or informal; and (e) intentional integration. To clarify these inclusion criteria, exclusion criteria were also identified: theoretical or conceptual articles, reviews, not articles (i.e., book chapters), postsecondary higher education or preschool, and including other disciplines outside the STEM disciplines (i.e., STEAM or literacy). These criteria were applied through manual search (by one of the authors) of the article titles and abstracts. After this vetting, 7,411 articles remained.
Round 2: Focus on Formal High School STEM-Integrated Education
We were primarily interested in how STEM integration occurs in settings where the learning environment structure may not support integration, and so we decided to focus on formal high school classrooms, where the disciplines are often taught in silos. Additionally, as many of the articles focused on technology integration, an already well-studied field (e.g., Ertmer et al., 2012), we limited the educational technology scope to include only technology that integrated the learning of content and excluded technology for the purpose of communication or learning management (e.g., Zoom or Canvas). Thus, new inclusion criteria were developed: (a) high school students and teachers, (b) formal classrooms, and (c) educational technology. Again, exclusion criteria were developed to clarify the inclusion criteria (i.e., kindergarten, elementary school, or middle school only; informal environments; and information and communication technology [ICT] or instructional technology). However, as several studies included multiple grade levels and we wanted a full picture of research in high school, we included all studies that worked with at least one high school teacher even if other grade levels were also present. These criteria were manually applied by four of the authors, first through a title and abstract review (that narrowed the pool to 806 articles) and then through a review of the rest of the article. This narrowed the pool to 426 articles.
Round 3: Focus on Teacher Learning and Beliefs
Further discussion by the first two authors led to a focus on only teacher knowledge and beliefs. We applied inclusion criteria focused on teacher outcomes, which was completed through a manual search by the second author. Teacher outcomes included any measurement of teachers’ knowledge or beliefs reported in results (e.g., teacher knowledge about STEM topics, or teachers’ confidence in teaching with STEM-integrated curricula). This reduced the sample to 275. These articles were read fully by the research team to ensure that all inclusion and exclusion criteria were met. Upon deeper reading, many of the articles did not fit the inclusion criteria. For example, some articles incorporated technology that did not require engagement with content such, as the integration of digital games. Other articles measured teachers’ technological pedagogical content knowledge, which is a well-studied topic (e.g., Herring et al., 2016). Still others were excluded because they reported only student outcomes. After the final application of these criteria, 110 research articles remained in the pool.
Data Analysis of the Research Landscape
To investigate the first research question, we examined variables that could shed light on teacher demographics, such as where the study took place, studies on pre-service or in-service teachers, and subjects of integration. We also investigated how researchers conceptualized and carried out their research, such as what research questions were asked and what findings and implications were reported, particularly those focused on teacher disciplinary knowledge. Thus, the following five primary categories were coded: publication information and participant demographics, research design, STEM integration details, intervention design, and challenges and barriers to implementation. The coding results of each of the 110 research articles are available in the appendix in the online version of the journal (Tables S1 and S2). Below, we provide more details of the analysis conducted for each of the categories.
Publication Information and Participant Demographics
The publication information recorded includes the publication reference (e.g., author[s]), year of publication, and title). Demographic information includes the country in which the study took place, the study participants’ professional level(s), subject(s) taught, and grade level(s) investigated in the study. As noted in a previous section, high school was an inclusion criterion, and because it was occasionally combined with other grades, we included studies that focused on combined grade levels as long as at least one high school teacher was a participant (see Table 2 for demographics coding details).
Coding manual for participant demographics category
Research Design
To understand the research design, we coded for five study types (see Table 3). PD interventions were opportunities for teachers to learn outside of formal education like college courses (e.g., Ring et al., 2017), while a college course was an intervention that was part of a degree program (e.g., French & Burrows, 2018). Surveys were studies that measured what teachers knew through a survey without an intervention. Likewise, the category of implementation study included research that described what teachers were doing in the classroom without participating in any interventions a priori. To examine how teacher knowledge was developed rather than observed, the study types were sorted into two groups: with intervention and without intervention. Codes 1 and 2 were studies with intervention that focused on developing teacher knowledge, while Codes 3 and 4 were studies without an intervention that measured teacher knowledge without seeking to influence it. The five studies coded as other were all nonintervention studies.
Coding manual for research design category
STEM Integration Details
This category examined how STEM-integration teaching and research were conceptualized in the studies. Three STEM integration details were coded: disciplines covered in the study; type of STEM integration; and focus of research questions. Table 4 depicts the coding manual for this category. The discipline list focused on subjects typically offered in high schools plus STEM general, a common description among studies that did not specify disciplines (e.g., Aydogan Yenmez et al., 2021). Type of STEM integration was coded based on three levels of integration. The first level was integration through a field or topic of study that requires knowledge and skills from multiple STEM disciplines. These were usually fields or topics that are not typically taught in formal high school classrooms, such as bioinformatics (Kovarik et al., 2013), astrophysics (Odenwald et al., 2020), or earthquake engineering (Cavlazoglu & Stuessy, 2017). The second level was integration through existing school disciplines, such as integrating mathematics into a biology class (Weinberg & Sample McMeeking, 2017) or engineering into a chemistry class (Boesdorfer, 2017). The final level of integration was general STEM integration that did not identify specific disciplines or fields of study but demonstrated a more generalized approach to integrating pedagogies and activities into existing classes (e.g., Nadelson & Seifert, 2017).
Coding manual for STEM integration category
We also categorized the focus of each study’s research questions. Questions that asked what teachers believed about STEM integration were given the code Teacher Beliefs (e.g., What are the relationships of teachers’ attitudes, perceptions, and knowledge towards STEM integration?; Shidiq & Faikhamta, 2020). Teacher pedagogical knowledge was coded as questions that sought to understand teachers’ knowledge or learning of strategies such as problem-based learning (PBL) or scientific inquiry (e.g., How did teachers’ perceptions and conceptions of PBL in STEM education evolve as a result of their participation in this PD?; Asghar et al., 2012). Teacher pedagogical content knowledge (PCK) was coded as research questions that explicitly mentioned PCK (e.g., How can the development of teachers’ personal PCK and beliefs about connecting research and design be characterized before and after a PLC [Professional Learning Community]?; Vossen et al., 2020). Finally, teacher disciplinary knowledge was coded as research questions on teachers’ disciplinary content and practices (e.g., What changes occurred in teacher-participants’ knowledge representations of earthquake engineering before and after workshop participation?; Cavlazoglu & Stuessy, 2017).
Intervention Design
The intervention design category was applied only to those studies that included an intervention (see Table 3). This category included two characteristics pertaining to our study goals: whether and how disciplinary knowledge was a focus of the intervention design, and the mechanisms used to address teacher learning within the intervention. The coding manual for this category can be found in Table 5.
Coding manual for intervention design category
For the disciplinary knowledge focus, we sought to answer the question: Does the publication state that the strategies and mechanisms included in the intervention design were designed to address disciplinary knowledge learning? To answer that question, three general levels were coded. The first level included studies that clearly explained how disciplinary knowledge was addressed in the intervention (e.g., Roehrig et al., 2012). The second level included studies where disciplinary knowledge development was mentioned as a goal, but the strategies used to address it were not explained (e.g., Araujo et al., 2019). Finally, the third level included studies that did not highlight disciplinary knowledge development as a goal of the intervention but instead focused on other types of knowledge development, such as pedagogical strategies (e.g., Bozkurt Altan & Ercan, 2016).
The list of strategies and mechanisms for addressing teacher learning was developed during the initial coding phase, when the coding manual was developed, and was subsequently added to throughout the coding process to capture the full spectrum of strategies used within the intervention studies.
Challenges and Barriers
In this category, we were interested in determining what challenges and barriers to implementation of STEM-integrated resources were identified and how often they were identified. Table 6 specifies the codes that were constructed from a constant comparative analysis of a quarter of the articles and then later formally organized into codes.
Coding manual for findings and implications category
The categories and codes in Tables 2 through 6 allowed us to map the research landscape of teacher learning for STEM integration, our first research question. To answer our second and third research questions, a deeper analysis of the research focus (Table 4) and mechanisms for learning (Table 5) was necessary. A description of those analyses follows.
Data Analysis of Teacher Learning and Development of Teacher Knowledge
To explore the extent to which the research field has addressed teacher disciplinary knowledge development for STEM integration, we examined the full set of publications in three groups according to the study’s stated research questions. The first group consisted of studies that included a research question about teacher beliefs. The second group consisted of studies that included a research question about teacher pedagogical knowledge or PCK. The final group consisted of studies that included a question focused on developing teachers’ disciplinary knowledge.
Analyzing Research on Teacher Beliefs
Because Teacher Beliefs was by far the most common code for research questions (n = 78), we conducted a second-level analysis on these studies. Three of the authors on this paper applied a constant comparative method to qualitatively code and analyze the studies (Glaser, 2008). Following several exploratory rounds using a subset of studies, the authors met to discuss and arrive at consensus on a set of thematic codes. Once these themes were established, all 78 papers were collectively coded by the authors. These codes were not exclusive, meaning that individual papers could be coded for multiple themes at once. Following the final round of coding, exemplary papers were identified for each category as illustrations to be discussed in the Results section.
Analyzing Research on Teachers’ Pedagogical Knowledge and PCK
Additional analysis was also conducted on the subgroup of studies that included research questions about teachers’ pedagogical knowledge or PCK. One of the authors examined the research questions for the 34 articles that comprised this group of studies (30 focused on pedagogical knowledge, 3 on PCK, and 1 on both). This analysis was qualitative, focusing on both how teachers were studied and the study’s impact on teacher learning. The themes that emerged were shared and discussed at length with the other authors. We highlight the themes in the findings section with exemplar papers.
Analyzing Research on Teachers’ Disciplinary Knowledge
Given the importance of teacher disciplinary knowledge for effective implementation of novel science teaching practices, we conducted an additional analysis of the studies that were coded for having both a research question focused on teacher disciplinary knowledge and clear mechanisms for addressing teacher learning (n = 21). The aim of this analysis was to better understand (a) what mechanisms for teacher disciplinary learning are most commonly applied and (b) what mechanisms for teacher disciplinary learning are most promising. Two authors applied a constant comparative method to qualitatively analyze the subset of studies (Glaser, 2008). Exemplar papers are again highlighted and described in detail in the findings section.
Results
We present the findings in three sections aimed at addressing the research questions. In the first section, we examine the research landscape on STEM integration and teacher learning. We first discuss publication details including the participant demographics represented in the collective group of studies, research design, STEM integration details, research focus pertaining to teachers and teaching, and reported challenges related to STEM-integrated instruction in the classroom. In the following sections, we outline the relative focus on teacher disciplinary knowledge compared to teacher beliefs and pedagogical practices, as well as the mechanisms for developing teacher disciplinary knowledge.
STEM Integration Research Landscape on Teacher Learning
We present general statistics on the 110 articles analyzed for this study. Full details can be found in the appendix in the online version of the journal.
Publication Information and Participant Demographics
Other than an outlying spike in 2013, the number of articles published on STEM integration has been steadily rising since the publication of the National Academies report in 2014. Figure 1 shows the full number of articles published each year. The articles derived from 66 different journals, 3 of which published more than five articles (i.e., Journal of Agricultural Education, International Journal of Technology and Design Education, and the International Journal of STEM Education). About 40% of studies came from journals with an impact factor of 1.5 and above, with the International Journal of STEM Education having the highest at 6.42. Additionally, the studies were conducted in 19 different countries, with over half (59%) in the United States.
Publication by year. Publications were reviewed through April of 2021.
The majority of articles provided some demographic information, such as the professional stage of the participating teachers, and the subjects and grade levels taught. However, other demographic determinants that are useful for understanding teachers’ background and context—such as years of experience, ethnic or racial identity, and school context—were not included in a majority of studies. Table 7 lists the frequency of demographics reported in the studies.
Demographics provided by articles
The studies included participants who taught a range of subjects, as shown in Table 8. While mathematics was the most common subject taught by teachers, when the science subjects were combined, 79 publications (72%) included science teachers in their participant group. The most common category among those coded as “other” was agriculture. The subjects of environmental science, computer science, and engineering were comparatively less represented. We noted that engineering is beginning to appear as a separate discipline in high schools; however, the majority of those teachers were identified as engineering and technology teachers.
Studies that included teachers of each subject
Eighty-eight studies reported grade levels taught, of which 34 (39%) included middle school teachers as well as high school teachers and 20 (23%) included elementary school teachers as well as high school teachers. Additionally, a number of the studies from outside the United States did not report grade levels that corresponded with how we delineated grade bands. Among the remaining 22 that did not report grade levels, a number of these studies were of pre-service teachers who were being trained in a specific discipline and, therefore, were likely to teach high school.
Research Design
Table 9 presents a breakdown of the types of research designs used in the set of studies. Of the 110 total articles, 71 (65%) included an intervention, with 53 of those intervention studies including at least some in-service teachers, while the remaining 18 were focused only on pre-service teachers and were primarily studies of college or university courses. Among the 40 studies that did not include an intervention, most (25; 67%) were survey studies that collected self-reported data from teachers.
Types of studies
STEM Integration Details
As shown in Table 10, the largest percentage of studies fell into the third category, which means that nearly half of all studies treated STEM integration as a generalized strategy without grounding it in specific subjects or fields of study.
Type of STEM integration
Note. The total n is 109 because 1 included article was a study comparison of multiple programs that used different methods of STEM integration, so it was not possible to assign that article a single code for this category.
The 17 studies that specified a specific STEM-integrated field all focused on a different field or subfield. They were aerospace engineering, astronomy, astrophysics, bioinformatics, biomedical engineering, biomimicry, climate change, construction, cybersecurity, earthquake engineering, foundations and history of technology, hazard mitigation, materials and manufacturing, mechatronics, renewable energy, robotics, and vegetation index measurement. Due to the siloed nature of high school courses, each topic was ultimately grounded in one or more traditional STEM disciplines.
Approximately a third of the studies focused on integration between existing high school subjects. Table 11 shows a breakdown of how the subjects were combined, with the “base subject” or the class in which the teacher participants taught listed across the top. “All STEM subjects” refers to studies in which high school teachers from multiple disciplines participated. Along the left side of the table are the subjects that were the focus of the integration. “Integrated STEM” refers to studies that attempted to bring a general conception of STEM into a specific existing high school class such, as science or technology (e.g., Kubat, 2018). Science class as the base subject was most frequently used as the site of integration, while engineering was the subject most integrated into base subjects, with about a third of all studies focusing on this.
Integration of existing school STEM subjects
Note. This table examines the 40 articles coded as “Integrates another STEM content area into an existing school subject” in Table 10. Some of these articles were double coded due to integration into multiple subjects.
Research Focus Within the Articles
Because most studies asked multiple research questions, many of the articles were double or triple coded to represent the full range of research foci. As shown in Table 12, a majority of studies (71%) had at least one research question focused on teachers’ beliefs. In contrast, less than a quarter (24%) of the articles had a research question focused on teachers’ disciplinary knowledge, while slightly more (27%) focused on teachers’ pedagogical knowledge or PCK.
Coded focus of research questions
State of Reporting on Intervention Design
Since we are focused primarily on how to support teachers’ implementation of STEM integration, we delved more deeply into the 71 studies that included an intervention for teachers. These studies were coded into three categories based on how they described the disciplinary knowledge focus of their interventions (see Table 5 codes). In this set of studies, 21 (34%) addressed teachers’ disciplinary knowledge clearly, 28 (42%) expressed disciplinary knowledge as a goal but did not specifically address it in the intervention, and 22 (24%) provided no focus on disciplinary knowledge development.
Studies that clearly described mechanisms for addressing disciplinary knowledge stated that disciplinary learning was a goal and described, in the context of the intervention, how disciplinary knowledge was developed. For example, Boesdorfer (2017) provided a detailed description of how chemistry teachers in their study were introduced to engineering processes that connected to the chemistry curriculum. They wrote,
The teachers experienced the engineering design process as students, then aspects of the engineering design process were discussed along with the teaching aspects of the activity. The teachers then engaged in a second engineering design activity as student learners before a discussion of the activity and how engineering design might be incorporated into their classrooms. To help the teachers transfer their learning to their classroom, the activities chosen were novel to the teachers but ones that readily fit into a high school chemistry curriculum so there would be similarities in the knowledge domains. (p. 615)
Boesdorfer then provided a table with descriptions of each of the activities and the components of engineering design that were highlighted. In this example, the mechanisms for disciplinary learning were described and clearly connected to the curriculum being taught.
In a counterexample, in which the mechanisms for disciplinary learning were unclear but the researchers were ostensibly interested in addressing disciplinary learning, Ferand et al. (2020) provided little information about the mechanisms used to develop this knowledge. They wrote, for example, “The content focus included: laboratory investigations, unit plans, and curricular resources specifically related to the STEM concepts present in the floriculture industry” (p. 191). Although the mechanisms were listed, no details were provided on how they were to be integrated into the curriculum. Later in the article they wrote,
Curricula were delivered through an inquiry-based, hands-on approach and modeled by the instructors as recommended by Bybee (1993), to allow participants to gain full knowledge and complete the lessons as a student and thus have a deeper understanding of the content, context, and pedagogy. (p. 195)
We can see from this excerpt that although disciplinary learning was a stated goal, the mechanisms for developing it were unclear.
Mechanisms for teacher learning described in the set of studies were additionally coded and analyzed (Table 13). The three most common mechanisms for addressing teacher learning were (a) developing or modifying lesson or unit plans for classroom implementation (65%); (b) experiencing STEM activities, or full lessons or units, as learners (52%); and (c) collaborating with disciplinary experts (i.e., researchers, university professors) who either led or supported the intervention (38%).
Mechanisms for addressing teacher knowledge development in interventions
In general, across the studies, we noted that the lack of clarity for most (two thirds) of the studies, with respect to intervention descriptions, made it difficult to replicate the mechanisms used. If the mechanisms for developing teachers’ disciplinary learning are not clearly described, it is impossible for others to use those mechanisms to guide teacher learning in future interventions.
Reporting of Findings and Implications: Challenges to STEM Integration
In this analysis, we were interested in what the field identified as common challenges to STEM integration in high school settings. The majority of articles (61%) did not report findings in this area; of the 43 articles that did, 31 (72%) reported that teacher knowledge was one of the major challenges to implementation in addition to issues that we would expect, such as time and resource constraints (see Table 14 for a full list of challenges reported). Notably, even though teacher knowledge challenges was ranked as the most common challenge, it was investigated as a research question in a minority of studies as revealed in a previous section.
Reported challenges and barriers to implementing STEM integration
Thus far, we have presented an overview of the landscape of research on teacher learning for STEM integration. While few studies focused explicitly on developing teacher knowledge, some mechanisms for doing so were reported. To answer our second and third research questions, in the following sections we examine how teacher learning has been addressed, what mechanisms have been shown to be successful, and what guidance the field has provided to support the development of teacher disciplinary knowledge.
Teacher Beliefs Regarding STEM Integration
The large majority of the studies in this review (71%) included at least one research question examining teacher beliefs. Of these 78 studies, 32 (41%) solely examined teacher beliefs. The remaining 46 studies examined teacher beliefs in conjunction with other topics, such as teacher disciplinary learning (6 studies), teacher pedagogical knowledge or PCK (6 studies), and teacher implementation experiences (18 studies). In the following sections, we discuss themes that emerged from an analysis of the teacher beliefs studies through specific cases in the literature.
The most common theme represented in the teacher beliefs literature was teacher perspectives and dispositions towards STEM integration and its role in schools (38 out of 78 studies; 49%). Many of these studies found that participants held positive dispositions towards STEM integration. For example, Stubbs and Myers (2016) found that teachers held a positive and interdisciplinary perspective on STEM, and Berlin and White (2012) found that teachers clearly valued integration. However, even with these positive dispositions, concerns about efficacious implementation still arose. For example, Asunda and Walker (2018) reported that teachers’ understanding may need improvement to increase effectiveness for teaching STEM integration. Braskén et al. (2020) found that teachers wanted to create a concrete path that would allow them to teach more interdisciplinarily; however, little support was provided. In studies where negative teacher beliefs were found, teachers noted insufficient support or preparation (e.g., Geng et al., 2019; Johnston et al., 2014). Sixteen of the 38 studies found that an intervention was successful in improving teachers’ dispositions towards STEM integration. Page et al. (2013) and Ring et al. (2017), for example, found that equipping teachers with a more interdisciplinary and sophisticated understanding of the subjects being integrated was helpful.
Aside from examining teacher perspectives and dispositions towards STEM integration and its role in schools, several other common themes were identified in the studies exploring teacher beliefs. We do not delve specifically into the findings because they are quite varied across the themes but present the themes here as an illustration of where the emphasis on teacher learning has been placed in teacher beliefs research. Fifteen studies examined the relationship between teacher beliefs and teacher identity. For example, Dong et al. (2020) explored whether teachers’ perspectives about the requirements of using a STEM approach and their attitudes toward it differed according to gender, specialization, and grade level. Fourteen studies explored teachers’ overall perspectives about implementing STEM integration in classrooms and perceived challenges. These studies tended to explore teacher perspectives on implementing STEM integration from a broad perspective. For example, Acar and Büyükşahin (2021) examined teachers’ general beliefs about the benefits and potential challenges involved in implementing STEM integration into their own classrooms following participation in a training program. Fifteen studies explored teacher perspectives on specific pedagogical strategies, curricular units, or resources connected to the implementation of STEM integration in the classroom. For example, Dyehouse et al. (2019) examined teacher perceptions of STEM integration activities connected to the implementation of modeling tasks using 3D technologies. Other themes that were identified were attitudes about a specific PD intervention (nine studies), connections between teacher beliefs and larger contextual factors (eight studies), and teacher perceptions about student learning (four studies).
Pedagogical Learning for STEM Integration
The majority (30 out of 47 studies) in our review that included research questions about teachers’ knowledge (including disciplinary knowledge, pedagogical knowledge, or PCK) focused only on pedagogical knowledge (Table 4 codes; Table S2 appendices in the online version of the journal) and only 4 explicitly asked questions about PCK. Among the studies on pedagogical knowledge, three major themes emerged: studies that sought to understand existing pedagogical practices and knowledge for STEM integration, studies that sought to build knowledge for a specific pedagogical practice (e.g., problem-based learning), and studies that sought to develop general STEM integration knowledge.
Several studies in this set examined teachers’ existing knowledge through a combination of surveys, interviews, and classroom observations without providing an intervention. For example, deChambeau and Ramlo (2017) examined the extent to which teachers successfully used PBL as a pedagogical strategy for teaching STEM integration. The majority of the findings reported on the challenges faced by teachers when attempting STEM integration. They found that disciplinary knowledge was a primary barrier to STEM integration and made suggestions for increased access to PD opportunities for teachers and learning coaches to engage with disciplinary knowledge experts in multidisciplinary training.
Other studies focused on deploying interventions through specific pedagogical practices. Daher and Shahbari (2020), for example, worked with preservice teachers to develop their skills for integrating math into classes through scientific inquiry. After engaging participants in multiple rounds of designing inquiry activities with feedback, during which students were repeatedly pushed to increase the level of inquiry, Daher and Shahbari found improvement in the participants’ ability to design activities at the higher levels of inquiry. However, they also found that participants continued to struggle with the STEM integration component of the activities due to their relatively weak disciplinary knowledge of mathematics. In a similar study focused on PBL, Asghar et al. (2012) found that the teachers in their study did not perceive the pedagogical strategy of PBL as linked to the disciplinary content; and they noted that future PD needed to make clearer both the integration of the strategy and content, and how the content could fit into their respective disciplines.
Finally, a number of studies in this group focused on providing teachers with a general understanding of the uses and applications of STEM integration. For example, Acar and Büyüksahin (2021) implemented a PD experience for in-service teachers that presented an introduction to STEM education as a desired pedagogical outcome. Throughout the 5-day workshop, they discussed STEM as a singular concept, conducting conversations on how STEM education is implemented in the world and strategies for implementing STEM education. While the mechanisms for learning were not described in detail, there was no explicit engagement of disciplinary knowledge across the STEM fields. They found that while teachers’ interest in engaging in STEM integration increased, there were still many perceived barriers, including the need for more targeted PD and training on specific disciplinary knowledge and specific pedagogical tools for STEM integration.
Strategies and Mechanisms for Developing Disciplinary Knowledge for STEM Integration
In this section, we more closely examine the specific mechanisms and strategies for developing disciplinary knowledge that were used across of the studies we reviewed. Our analysis included 20 studies that had a focus on disciplinary learning and that clearly articulated mechanisms to develop it (Table 5 codes; Table S2 in the online version of the journal). Within these 20 studies, we identified 12 strategies for teacher learning (see Table 13). Because teaching and teacher learning are complex fields, high-quality PD necessitates the inclusion of a variety of practices and avenues for teacher learning to develop (e.g., Darling-Hammond et al., 2017). This diversity was evident in design considerations in all but five intervention studies we reviewed. Hardré et al. (2013), for example, used a research apprenticeship with scientists, collaborative lesson design, coaching on implementation, and reflections on practice. Similarly, in Roehrig et al. (2012), teachers engaged in lesson plan design, opportunities for reflections on practice, disciplinary expert collaboration, and coaching on implementation, among other activities.
However, a clear commonality we noted among the papers is that many of the mechanisms identified as directly addressing the development of teachers’ disciplinary knowledge were instead focused on their pedagogical knowledge. Furthermore, the mechanisms of experiencing STEM activities or lessons as a learner (14 studies) and of lesson development or modification (14 studies) appeared as the most frequent codes. These mechanisms were coupled with mechanisms that demonstrated access to disciplinary expertise (i.e., research apprenticeship with scientists, discipline expert collaboration, and conceptual modeling) about 60% of the time. Those studies in which a focus on pedagogy and disciplinary learning were uncoupled showed a higher percentage of teacher knowledge as being a challenge to implementation (e.g., Boesdorfer, 2017; Borowczak & Burrows, 2019; Gibson, 2012).
Of the mechanisms that were aimed squarely at developing teachers’ disciplinary knowledge, discipline expert collaboration was used most frequently (12 studies). Research apprenticeship with scientists (six studies) as well as conceptual modeling (two studies) were other mechanisms used for promoting teacher disciplinary learning. In the following sections we provide more details about how each of these categories of disciplinary knowledge development occurred with teachers, the types of knowledge that were measured, and aspects of knowledge that changed. One thing to note is that six studies were coded in two of the categories. In cases where they were double coded for discipline expert collaboration and research apprenticeship with scientist, we first report on those studies that did not explicitly use a research apprenticeship model (seven studies). We then separately report on experiences of teachers that participated in a research apprenticeship. One study was double coded in the categories of discipline expert collaboration and conceptual modeling. However, because there were only two studies in the latter category, we include both in the analysis.
Discipline Expert Collaboration
In the seven studies that used discipline expert collaboration, all studies ran PD workshops that lasted for more than 6 days, apart from one study (Gupta, 2015) that ran for only 1 day. In most cases, discipline expert collaboration was a relatively brief experience, in which teachers interacted with experts for a short period of time during the PD, but rarely afterward, during classroom implementation. Studies varied in how teachers accessed that expertise, with the most common format being disciplinary expert lectures and demonstrations. Knowles et al. (2018), for example, described a workshop that used STEM professionals in lectures and demonstrations of their practice. They wrote,
TRAILS leadership began by inviting experts to present their work at the intersections of advanced manufacturing, STEM research, biomimicry, and education. For example, advanced manufacturing experts featured presentations on additive manufacturing innovations and 3D scanning for inspection and design analysis. The topics provide the teachers with authentic contexts for learning and teaching STEM content and practices. (p. 2)
What is also notable in this excerpt and common across most of the articles was the use of topics currently investigated by real-world STEM professionals. These topics included earthquake engineering, the production of biodiesel fuel, biomimicry, bioinformatics, and the role of electromagnetic spectrum reflectance in climate change. Relatedly, a focus on the tools and processes used in research and industry activities and how they reflect the need for interdisciplinary knowledge was evident in all studies. For example, Kovarik et al. (2013) described this set of experiences for teachers in their summer workshop:
Teachers deepened their exploration of bioinformatics and related careers by touring local research facilities and learning about next-generation DNA-sequencing technology and other high-throughput data generation and analysis techniques. Guest speakers and panel discussions with scientists who perform genetic research were included in the 2-wk program to illustrate diverse careers and areas of research influenced by bioinformatics. (p. 448).
In some cases, teachers were able to test some of the tools themselves such as process flow diagrams in recycling for biodiesel production (Gupta, 2015), and using CAD software to design lures after visiting a pond and learning about aquatic insect specimens (Kelley et al., 2020). Teachers acting as students while learning through curricular resources with experts available to answer questions was also a strategy used in some studies. For example, Woniak et al. (2020) wrote, “Teachers were acting as students who had to go through every stage of the project: download the data, process it and formulate conclusions. During the workshops, all participants’ questions and doubts were clarified by a trainer” (p. 9).
All studies in this set claimed positive teacher outcomes with respect to their research goals. However, similar to studies in our dataset that did not explicitly focus on the development of disciplinary knowledge, the majority measured teachers’ self-reported improvements in self-efficacy beliefs or career awareness as a result of the PD (Gupta, 2015; Kelley et al. 2020; Knowles et al., 2018; Kovarik et al., 2013; Woniak et al., 2020). The study by Li et al. (2019) said that teachers needed more intensive technical learning support in integrating computational thinking in STEM courses and referenced content knowledge as a significant barrier. Only the study by Cavlazoglu and Stuessy (2017) measured positive significant improvements in teachers’ disciplinary knowledge (to be discussed in more detail in the section on conceptual modeling).
Research Apprenticeship With Scientists
Apart from one study conducted in the UK (Gibson, 2012), studies in this group were funded by the U.S. National Science Foundation’s (NSF) Research Experiences for Teachers (RET) program with the explicit goal of augmenting K–12 teachers’ STEM disciplinary knowledge. The program funds projects that typically offer extended summer research experiences for teachers by embedding them in university or college STEM labs and partnering them with a faculty member or graduate student for mentorship. Another explicit goal of the NSF RET program is for teachers to be able to translate their experiences in school-year classroom activities and curricula to broaden their students’ awareness of and participation in STEM fields of study. Similar to the previous category of discipline expert collaboration, teachers participate in faculty lectures and demonstrations with tours of lab and industry facilities. They also learn about research tools and practices. However, participants in this category use their newly acquired disciplinary knowledge and skills to conduct their own mini-research projects and use a portion of their summer experience to engage in lesson planning and production for classroom implementation.
The five studies in this category that were conducted in the United States followed a typical RET model offering teachers a 4- to 6-week experience in a university-based lab. The study in the UK offered industry-based placements for 5 days. All studies were aimed at supporting math and/or science teachers to integrate engineering knowledge and practices into their school curricula and hypothesized that the extended lab emersion experience would provide deeper insights into what engineers do and how they conduct their research. Investigating the challenge of designing structures to withstand windstorms, Reynolds et al. (2013) described this hands-on training with teachers:
The teachers were given the opportunity to explore structural analysis and design software RISA 3D. Three-dimensional models of the structure were built in the RISA environment. Both the gravitational loads and lateral loads because of wind were applied. The structures were then analyzed and responses were evaluated in terms of stress and deflection. (p. 14)
Teachers then took a fieldtrip to a facility that manufactured roof trusses, where they learned about the fabrication process and how the design of trusses took wind loads into consideration. What is notable in this example and illustrative of all the studies in this category is the time that was afforded to teachers to explore different engineering representations (e.g., modeling and terminology), to interact with science and math content, and to investigate theory to practice applications. Another benefit for teachers in this set of studies is related to the amount of time they spent with project teams both during the summer research experience and afterward during the school year. In the study by Hardré et al. (2013), for example, teachers explicitly stated that access to mentors over a longer period of time was helpful both to develop their own understanding of engineering and to teach it in their classrooms.
The six studies in this category all reported positive outcomes related to their study goals which were to learn about what engineers do and how engineering is defined (Gibson, 2012; Hardré, 2013; Pinnell et al., 2018), and self-efficacy beliefs and teaching about engineering (Laffey et al., 2013; Page et al., 2013; Pinnell et al., 2018; Reynolds et al., 2013). However, none of the studies actually measured the extent to which teachers developed their STEM-integrated disciplinary knowledge.
Conceptual Modeling
Only two studies used conceptual modeling as a mechanism to develop teachers’ disciplinary knowledge (i.e., Cavlazoglu & Stuessy, 2017; Roehrig et al., 2012), but we found this mechanism to be especially promising due to the explicit focus on conceptual integration. We highlight the study by Cavlazoglu and Stuessy (2017) because they had among the clearest and most central goal of developing teachers’ STEM-integrated knowledge of the 20 studies reviewed in this section. They worked with teachers in a 6-day PD program aimed at helping teachers integrate earthquake engineering into their domain-specific classrooms (these subjects included biology, chemistry, and general science). Similar to other studies, they used a variety of mechanisms for teacher learning, including experiencing STEM activities as students, collaborative lesson plan design, and disciplinary collaboration with experts. The exceptional aspect of this study arises from its use of concept mapping. The participants in the PD were given 35 key earthquake engineering concepts that were distributed across five domain areas (i.e., physical systems, designed systems, social systems, earth systems, and STEM proficiencies). The key concepts included, among others, force, energy, constraints, plate boundaries, prediction, and systems thinking. Teachers were then required to construct concept maps with labeled domain areas, paying special attention to the linkages and connecting words between concepts. Teachers worked both individually and in groups to come to consensus on a concept map that represented how the 35 key concepts were integrated across the domains prior to and after the workshop. Workshop activities described in the following excerpt show a clear focus on developing teachers’ disciplinary content and practices:
The workshop provided hands-on, minds-on experiences and background information about what earthquake engineers do; how earthquake engineers solve complex problems associated with the mitigation of seismic disasters; how the STEM-related domains of science, technology, engineering, and mathematics come together in solving complex, integrated problems; and how the use of models (including simulations and modeling software) assist student in understanding complex and interdisciplinary problems. In the EEEP workshop, we provided active, engaging educational activities, which included assuming roles as experts in making decisions about earthquake mitigation in an educational board game, Earthquake (A. Perkins, 2016), background readings, presentations and discussions, earthquake simulations and demonstrations, and teacher group projects. (p. 246)
The preintervention and postintervention concept maps demonstrated a significant increase in teacher understanding of earthquake engineering and its links with other domain-specific STEM fields. This statistical analysis was then corroborated by a content analysis of the curricular resources designed by the teachers in the PD. The authors discussed, and we agree, that concepts maps as a learning tool provided a visual scaffold for constructing a knowledge base of how concepts were integrated across different scientific domains.
Discussion
In this section, we discuss the analyses and highlight areas of strength as well as gaps in the corpus of STEM-integration research with respect to our research questions. Again, more details of each study can be found in the appendix.
We begin with an examination of the first research question: In what ways has the literature focused on teacher learning? There were several positive outcomes of our systematic review pertaining to the state of the field. Corroborating results by Ritz and Fan (2015), we found that researchers around the world are intent on understanding how best to support STEM integration in high school or secondary classes. Although more than half of the studies were conducted in the United States, there are hubs of research in countries like Turkey and the Middle East (14% of studies) and China and the Pacific Rim (6% of studies). This finding can help researchers locate interested colleagues to conduct comparative studies that can support a global unified approach to research. Where English (2016) argued for a more balanced inclusion of research in all of the STEM disciplines, particularly in mathematics and engineering, our review of the range of subjects taught by teachers demonstrated that all of the STEM disciplines were represented, with the strongest showing in mathematics. There was also a decent showing of teachers identified in the subject of engineering (15% of studies) even though it is not a common subject taught in traditional school systems. Likewise, it is encouraging that the subject of agriculture was identified in 8% of studies because of the more global educational goals for STEM-integrated instruction that support real-world innovation and economic development (Martin-Paez et al., 2019; Zollman, 2012) and the goals of practical problem solving in science standards such as the NGSS (NGSS Lead States, 2013).
We also noted several gaps, areas less represented, or challenges that are important to review. First, given that many studies noted the challenges related to teachers’ levels of disciplinary knowledge, it seems problematic that not every study reported on grade levels taught in light of well-known findings that elementary teachers need to be supported in developing STEM content knowledge. Levels of teaching experience were also reported in fewer than 45% of studies; and other characteristics of the population and teaching environment, such as previous experience with STEM-integration, were reported by only a fraction of studies. Furthermore, despite the specific inclusion criteria of studies working with high school students and teachers, 61% of the studies that reported grade levels included elementary and middle school teachers in addition to high school teachers. Where the NAS (2014) report focused a great deal on issues pertaining to the lack of STEM expertise at the elementary and middle school levels, aggregating teachers of these different grade bands in interventions may not tailor activities enough to address challenges in each group’s respective understanding of STEM disciplines. We also noted that, in terms of the disciplines reported and the types of STEM-integration conducted, 33% of studies reported “Science General” and 48% of studies reported “General STEM integration” as a focus of their studies. As discussed in the introduction, because the nature of disciplinary knowledge can have deep epistemic and practical differences (e.g., Goldman et al., 2016) and because having well-structured domain knowledge influences the ability to become adaptive experts in teaching (Tsui, 2009; Yoon et al., 2019), it seems important to specify what disciplines are at the center of teacher learning development when engaging in STEM-integrated instruction. An added challenge with respect to how to work with the teaching population on developing STEM-integrated literacies is the fact that only 25% of studies that were interventions (or 16% of the total studies reviewed) worked with pre-service teachers. Working with teachers at the beginning of their careers should be a focus of studies so that teachers can continue to develop their expertise in this area.
We turn now to the second research question: To what extent has the literature addressed the development of teacher disciplinary knowledge for STEM integration? Our results corroborate our initial beliefs about the lack of explicit focus on developing teacher disciplinary knowledge in the STEM-integration literature. Based on previous reviews of the field (e.g., Martin-Paez et al., 2019; NAS, 2014; Thibaut et al., 2018), much of the literature has skirted the topic of STEM integration despite an acknowledgement of the need for more research and more supports for teachers in this area. The good news is that in the studies that addressed teacher beliefs about STEM integration, the results showed that, by and large, teachers were positively disposed to the idea of integrating STEM subjects in their practice. Teachers were also likely to demonstrate positive beliefs after an intervention. Our review of the teacher beliefs literature also revealed the major challenges that teachers noted as being barriers to implementation, which include being underprepared and receiving little support to teach in an interdisciplinary way.
We also saw relatively high numbers of studies focused on developing teachers’ pedagogical approaches that favor STEM-integrated instruction such as inquiry-based methods. The positive outcomes from this review showed that teachers in general were better able to use these kinds of methods after an intervention. Furthermore, teachers’ interest and engagement in using the methods in their practice increased. However, similar to the teacher beliefs literature, a number of these studies highlighted the challenges that teachers faced during implementation, which suggests a lack of training in disciplinary content knowledge and practices. The fact that so few studies in our data set attempted to address the development of teachers’ PCK is also concerning because it is precisely here where teachers’ content knowledge and practices are combined with pedagogical approaches. Indeed, these findings match the analysis of the studies that reported on challenges in STEM integration, where we revealed a very high percentage in the category of teacher knowledge (Table 14). Given the number of studies that identified teacher disciplinary knowledge as a challenge to STEM integration, we would have liked to have found more studies that explicitly made this issue a focus of their research. Clearly, the field of science education has fallen short in meeting Wilson’s (2013) call, made more than a decade ago, to offer PD activities on more than general instructional strategies for implementing the new STEM-integrated NGSS science standards.
Finally, we examine the results pertaining to our third research question: To what extent does the literature provide guidance on mechanisms for developing teacher disciplinary knowledge for STEM integration? Considering the findings from the first two research questions, it is not surprising that most of the stated mechanisms to develop teacher disciplinary knowledge were in fact mainly focused on pedagogy. On the positive side, we were heartened to find many different kinds of strategies that were in use by PD developers to work with teachers. Each of these strategies appears to offer different insight into how STEM-integrated activities are likely to impact teaching practice. For example, having teachers experience STEM activities or lessons as learners can enable them to pinpoint exactly where in the instructional scope and sequence students are likely to find affordances and barriers to their learning. But as we noted in the results, only three mechanisms directly addressed the development of teachers’ disciplinary knowledge. These were collaboration with disciplinary experts, research apprenticeships, and conceptual modeling. Each of these mechanisms narrow down and centrally locate the essential content and practices of the discipline. They also highlight how integration between the disciplines naturally occurs in real-world STEM investigations.
In the case of research apprenticeships, teachers’ immersive lab experiences meant that they were able to participate in firsthand real-world STEM investigations in bounded and content-specific ways, learn STEM terminology, practice with disciplinary tools and processes, and engage in authentic disciplinary discourse. From the perspective of Goldman et al. (2016) these are the exact ingredients needed to develop disciplinary literacy. Furthermore, the extended time to learn about, reflect on, and construct representations of their newly acquired knowledge and skills through classroom lessons was found to be important in raising teachers’ confidence and self-efficacy beliefs. This was also true even through shorter interactions with discipline experts.
In fact, in all three mechanisms, having access to disciplinary concepts and practices as well as knowledge of how they can be conceptually integrated a priori was important for teacher learning. There was no guessing on the part of the teacher about disciplinary ideas with which they had no previous experience. Our interpretation of the findings from Cavlazoglu and Stuessy (2017) is that the process of making this knowledge explicit was supported by a declaration of the central key concepts that needed to be integrated from the outset by domain experts, which then primed teachers to attend to them as they experienced workshop activities. For example, that designed systems focus on concepts like constraints and reliability was likely new to the science teacher participants. They were then required to integrate concepts like urban infrastructure in social systems and motion and disturbance in physical systems, and so on. Both the delimiting of essential concepts in a domain and the a priori acknowledgment that they are all connected focused teachers’ cognitive resources instead of leaving them to discover key concepts on their own (for example, through a pedagogy like project-based learning) that they would not be primed to discover as newcomers in those domains. As discussed earlier, acquiring a sense of the well-structured knowledge domains instantiated in STEM-integrated topics would be critical to move teachers from routine experts in subjects that they teach to STEM-integrated adaptive experts (e.g., Berliner, 2001; Hatano & Oura, 2003; Yoon, Shim, et al., 2023).
Another set of findings that we would like to highlight in this section come from Tables 10 and 13 regarding the analyses on type of STEM-integration and mechanisms for addressing teacher knowledge development. We believe that the three mechanisms for positively developing teacher disciplinary knowledge can be enabled through an examination of authentic research that is happening in the STEM-integrated fields. Many of those topics—like climate change or earthquakes—present pressing issues that STEM research must address across the globe. Having an expanded and more accurate sense of the epistemic practices that STEM professionals use to investigate these topics can help teachers to teach students how to evaluate the veracity of knowledge claims (Chinn et al., 2021) that may, in turn, demystify the complexity of these issues (Gorman & Gorman, 2017). And because such topics all have a science component, it is likely that they can be incorporated into existing high school subjects. Our review showed that of all the STEM disciplines, science class was the most frequent base for integrating STEM subjects. Furthermore, engineering was the most frequently integrated subject and, therefore, might be a good place to start with respect to increasing efforts to develop teachers’ disciplinary knowledge.
A final note about the studies reviewed on mechanisms for developing teachers’ disciplinary knowledge for STEM-integration. Recall that they were selected because of their explicitly stated research goals on developing teachers’ disciplinary knowledge and clear mechanisms for achieving this goal. Based on this review, however, with the exception of Cavlazoglu and Stuessy (2017), we have shown that what researchers measured was mainly teacher’s self-efficacy beliefs rather than disciplinary knowledge. Moreover, evidence of growth in disciplinary knowledge was demonstrated largely through anecdotal comments. For example, Woniak (2020) offered this piece of evidence from a biology teacher they worked with: “Eureka! I finally understood what happens here, it is incredible how physics perfectly describes biological processes!” (p. 9). Certainly, expressions such as these are exciting for professional developers as they show interest and potentially increased confidence. However, if we are to take seriously the challenge of improving teacher’s competence in addition to confidence levels, we should be measuring whether their disciplinary knowledge for STEM integration has improved. We then need to systematically identify those mechanisms that have contributed to the improvement. Making this a goal for educational research on STEM integration would enable us to significantly move beyond the recommendations advanced by the NAS (2014) report toward greater adoption of STEM-integrated activities in high school classrooms.
Limitations
We would like to acknowledge several limitations of this systematic review that may constitute future considerations for research in STEM-integrated teaching and learning. First, since our focal inquiry was in understanding whether and how the literature base has sought to develop teachers’ STEM-integrated disciplinary knowledge, we did not investigate the extent to which or how researchers developed PCK except to note that this was explicitly a research goal in only four articles we reviewed. However, we also know that it will be crucial to cultivate the full range of teacher knowledge types for authentic STEM-integrated instruction to take place from which meaningful student learning and participation can transpire (Shulman, 1987).
Related to the notion of PCK, we recognize the importance that culturally relevant pedagogies will play in translating STEM-integrated disciplinary knowledge into practice. This is true particularly as we saw that engineering was the most identified subject that was integrated into existing school subjects (Table 11), and there is solid research on how to leverage community epistemologies and students’ funds of knowledge through engineering activities (e.g., Schenkel et al., 2021; Tan et al., 2019). We should note that none of the four articles focused on PCK included goals to enact culturally relevant pedagogies. We believe that this will be a fruitful topic to undertake in future studies.
Our review also does not tackle the consequential question of how much STEM-integrated disciplinary knowledge would be acceptable for high school teachers to teach STEM-integrated topics. In our review, we revealed the use of RET placements in university or industry labs of 4 to 6 weeks that yielded improvements in teachers’ confidence and self-efficacy beliefs. However, what is not clear is the quantity and quality of STEM-integrated disciplinary knowledge that teachers acquired that may have influenced those improvements because it was not measured in those studies. Moreover, if it were to be measured, we would also need to understand its relationship to student learning and participation outcomes. This is yet another fruitful topic for future studies.
Related to the previous limitation, we recognize that many teachers will have come to the teaching profession with an already well-honed grasp of STEM-integrated knowledge and practices, particularly if they are career changers as researchers or practitioners in STEM fields (e.g., Antink-Meyer & Brown, 2017). Building from an asset orientation to support teacher learning and PD opportunities, identifying the range of STEM-integrated personal and professional resources teachers already possess would be helpful in tailoring PD experiences that would be most beneficial to individuals. Identification and mapping of teachers’ levels of expertise can also support the creation of research-practice partnerships and codesign activities that can be conducted to promote authentic and usable classroom resources for STEM-integrated instruction, such as in our own work on agent-based modeling of socioscientific issues (e.g., Yoon, Chinn, et al., 2023).
A final limitation of our review relates to the historical nature of how STEM teachers experienced learning themselves both as students in a STEM field or to become certified as a teacher in a STEM subject. A review of course or degree offerings at the undergraduate level is beyond the scope of our study; however, we obviously know that STEM-integrated research is taking place in universities. We also know from our study that only 16% of the total articles we reviewed worked with pre-service teachers. Thus, an area for further exploration would be to examine how pre-service courses can support the development of STEM-integrated disciplinary learning through research experiences or courses that are taken as part of undergraduate degrees or in teacher preparation programs.
Conclusions and Next Steps for Research
In addition to the aforementioned areas of further research, we conclude with 10 recommendations for research on developing teachers’ STEM-integrated disciplinary knowledge based on our analyses.
• The first and most obvious recommendation is that the field needs more studies that focus on developing teachers’ disciplinary knowledge for STEM integration.
• To understand the needs of teachers, studies should focus on the strategies and resources that are required of teachers at different grade bands (e.g., elementary, middle, and high school) including identifying participant and context variables that can support or impede STEM-integrated instruction.
• To provide as much practice as possible for successful STEM-integrated instruction, more studies are needed with pre-service teachers to identify their unique learning challenges.
• To address differences in knowledge and practices of disciplines, studies should refrain from general STEM learning and specify the domains that are at the center of the intervention.
• To adequately address teacher learning, studies should differentiate the mechanisms that are aimed at developing teachers’ pedagogical knowledge, pedagogical content knowledge, and disciplinary knowledge.
• More studies should focus on investigating the explicit mechanisms being used to support the development of teachers’ STEM-integrated disciplinary knowledge that includes a specification of the knowledge and practices and the mechanisms used for their integration.
• More studies should focus on expanding the ways that teachers can have access to disciplinary experts for an extended period of time.
• To develop authentic experiences in STEM-integrated learning, more studies should focus on working with topics that are currently being researched by STEM professionals (e.g., earthquake engineering or bioinformatics).
• To understand what STEM-integrated disciplinary knowledge was learned, the quantity and quality of this learning, and whether its translation into practice improved student learning and participation, teachers’ STEM-integrated disciplinary knowledge should be measured.
• To ensure that teachers are not only developing disciplinary knowledge for STEM-integrated teaching but are transferring that knowledge to implementation, more studies should focus on understanding and developing PCK for STEM integration.
Supplemental Material
sj-docx-1-rer-10.3102_00346543241289566 – Supplemental material for Developing Teachers’ Disciplinary Knowledge for High School STEM Integration: A Review of a Decade of Educational Research
Supplemental material, sj-docx-1-rer-10.3102_00346543241289566 for Developing Teachers’ Disciplinary Knowledge for High School STEM Integration: A Review of a Decade of Educational Research by Susan A. Yoon, Katherine M. Miller, Thomas Richman, Noora Noushad, Grace Hageman, Yueqiao Liu, Weiyi Zhang and Amanda M. Cottone in Review of Educational Research
Supplemental Material
sj-pdf-1-rer-10.3102_00346543241289566 – Supplemental material for Developing Teachers’ Disciplinary Knowledge for High School STEM Integration: A Review of a Decade of Educational Research
Supplemental material, sj-pdf-1-rer-10.3102_00346543241289566 for Developing Teachers’ Disciplinary Knowledge for High School STEM Integration: A Review of a Decade of Educational Research by Susan A. Yoon, Katherine M. Miller, Thomas Richman, Noora Noushad, Grace Hageman, Yueqiao Liu, Weiyi Zhang and Amanda M. Cottone in Review of Educational Research
Footnotes
Authors
SUSAN A. YOON is a Graduation School of Education Presidential Professor and Associate Dean of Research and Faculty Affairs at the Graduate School of Education of the University of Pennsylvania, 3700 Walnut Street, Philadelphia, PA 19104; e-mail:
KATHERINE M. MILLER is a former doctoral student at the Graduate School of Education of the University of Pennsylvania and current research associate for data science education at the Concord Consortium; e-mail:
THOMAS RICHMAN is a PhD candidate at the Graduate School of Education of the University of Pennsylvania; e-mail:
NOORA NOUSHAD is a PhD candidate at the Graduate School of Education of the University of Pennsylvania; e-mail:
GRACE HAGEMAN is a former master’s student at the Graduate School of Education of the University of Pennsylvania. She is currently community outreach coordinator at the Salvation Army Kroc Community Center in Green Bay, WI; e-mail:
YUEQIAO LIU is a former master’s student at the Graduate School of Education of the University of Pennsylvania and current editor at Beijing Sci&Tech Publishing, focusing on education books as well as child development, psychology, and other related topics; e-mail:
WEIYI ZHANG is a former master’s student at the Graduate School of Education of the University of Pennsylvania and current learning experience designer at the Center for Academic Innovation of the University of Michigan; e-mail:
AMANDA M. COTTONE is a program manager at the Center for Engineering MechanoBiology of the University of Pennsylvania; e-mail:
Notes
References
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