For more than a decade, education systems throughout the world have implemented significant interventions to lift student outcomes in science, technology, engineering, and mathematics (STEM). To address the need for nations to compete globally in STEM, government bodies, higher education institutions (HEIs), professional associations, and school systems have established research and education initiatives. Many HEIs and university educators have played a prominent role in these STEM-focused programs. Despite the prominent role that university educators take in progressing STEM initiatives (e.g., running projects; designing STEM units, activities, and lessons; consulting), particularly in the school system, little is known about these educators’ perspectives on STEM and the use of STEM as an interdisciplinary approach to teaching and learning. Previous research indicates that for professionals in STEM education, developing a shared conceptualization of what STEM is might be helpful for fostering a clearer understanding about how to address issues in STEM and achieve shared outcomes in this area (Breiner et al., 2012).

Research undertaken through the Investigating Academics’ Perspectives on STEM project explored the perceptions of a group of educators about STEM, STEM learning environments, and necessary capabilities for STEM educators at a university. In this article, we report on the participants’ perceptions of STEM and its teaching and learning, as gleaned from their Draw a STEM Learning Environment (D-STEM; Hatisaru & Fraser, 2021) pictures and associated texts. The article extends the findings on individuals’ perceptions about STEM education (e.g., Margot & Kettler, 2019) to explore university educators’ understanding of STEM education. The article contributes to discussions regarding key STEM-content-specific issues that have been missing in STEM teaching or professional learning (PL) efforts (Winberg et al., 2019).

Background

The acronym “STEM” is sometimes used to refer to each of the four component disciplines (science, technology, engineering, and mathematics) separately and sometimes to the integrated teaching of two or more of the disciplines (e.g., science and mathematics). Although STEM education is sometimes considered as both curriculum and pedagogy (Margot & Kettler, 2019), it is widely defined as an educational approach that coordinates the learning objectives of science, technology, engineering, and mathematics through open-ended, realistic, and interdisciplinary problems (Vasquez et al., 2013). This approach is increasingly believed to have a positive impact on students’ learning outcomes (Margot & Kettler, 2019).

There is, however, a lack of consensus on how STEM should be taught in the classroom. According to Vasquez (2014), at the heart of STEM education is application. STEM teaching and learning does not necessarily include all four STEM disciplines, but all STEM teaching practices provide students with opportunities to utilize the knowledge and skills they have gained. STEM instruction can take various forms, which extend across disciplinary, multidisciplinary, interdisciplinary, and transdisciplinary learning experiences (see Appendix A). In their exploration of school principals’ perceptions of STEM learning environments, Hatisaru et al. (2020) undertook an extensive review of the relevant literature (e.g., Glancy & Moore, 2013; Hobbs et al., 2018; Vasquez et al., 2013) and identified aspects of effective STEM learning environments. In this operationalization, STEM practices use knowledge from different disciplines, and problems are completed by combining knowledge and skills from two or more STEM disciplines. Problems are interdisciplinary and grounded in the real world in that they are experienced by the community. Students relate to and engage with problems that make sense to them based on their own experiences. Students work collaboratively with their peers, undertaking particular roles and responsibilities (i.e., teamwork). Concepts or problems are represented in multiple ways and structured such that they require translations between different modes of representations (see Table 1).

There are also several practical challenges in terms of successful implementation of STEM, including the necessity for educators of the component disciplines to collaborate closely to ensure authentic and meaningful learning, the lack of educators’ knowledge and skill to implement STEM activities, and beliefs and self-efficacy related to STEM integration (Honey et al., 2014; Margot & Kettler, 2019). Although extensive research has been undertaken to understand K–12 teachers’ perceptions of STEM education (Margot & Kettler, 2019), little is known about how university educators perceive teaching and learning of STEM, and importantly, as stated by Winberg et al. (2019), how university educators acquire STEM-specific pedagogical competence that could help them provide students with high-quality learning experiences. This gap in our knowledge may become increasingly important as high school students, who have experience in integrated STEM learning, graduate and commence their university studies.

There is no doubt that there has been an increased focus on the quality of teaching and learning in universities (Chalmers, 2011), with academics in many universities offered the opportunity or being required to undertake PL in university teaching. In their critical review of the literature on learning to teach the STEM disciplines in higher education, Winberg et al. (2019) suggest that pedagogies such as collaborative problem-based learning and situating learning in real-world contexts are known to be effective for student learning and are particularly suited for STEM education. The authors found that only 20 out of 77 of the research studies that they reviewed included a STEM focus, with the majority of the studies not addressing “the key issues of what makes the STEM disciplines difficult to learn and challenging to teach” (Winberg et al., 2019, p. 940). Although the authors note that much of the PL that their review highlighted had value, they suggest that STEM academics would benefit from PL focused on STEM content and therefore teaching and learning experiences more likely to improve students’ access to STEM disciplinary knowledge.

Research aim and question

In this study, we aimed to explore the perceptions expressed in the discourse of a sample of university academics when they depicted and described a STEM learning environment. We used the term learning environment to represent the diverse physical, online, or blended location, context, and culture in which learning takes place. The research question that guided the study was as follows: What are university educators’ perceptions of STEM and its teaching and learning? We explored the answer to this question by analyzing aspects of STEM learning environments in the pictorial and written discourse of the participants as a mechanism to make conjectures about how STEM is conceived and might be taught in the class.

The study

Context

The study grew out of previous research implemented by a team of researchers led by the first author of this article. The team patterned the D-STEM instrument from the literature and implemented it as part of an Australian national STEM project. They then developed the D-STEM Rubric, which includes research-informed elements of effective STEM learning environments (e.g., Glancy & Moore, 2013; Hobbs et al., 2018; Vasquez et al., 2013; see Table 1), to analyze the data and report the perceptions of STEM learning environments held by both the project team members (Hatisaru et al., 2019) and school principals (Hatisaru et al., 2020). In this study, we extended the application of the D-STEM instrument to explore university educators’ understanding of STEM education.

The D-STEM instrument comprises both drawing and written descriptions and is constructed as two pages. On the first page, participants are asked to draw a picture of a STEM learning environment. The following prompt is provided to ensure a common understanding and to trigger participants’ thinking: “A learning environment is the diverse physical or online/blended location, context, and culture in which students learn. Think about yourself and the kinds of things you do in your STEM learning environments. Draw a STEM learning environment.”

On the second page, participants are asked to provide a brief explanation of their drawing: “Look back at the drawing. In the space below, provide a brief explanation of your drawing so that anyone looking at it could understand what it means.” On this second page, participants are also given the opportunity to complete the following prompt: “STEM is…” This prompt enables our further exploration of participants’ understanding of STEM.

Participants and data generation

Academic staff from two colleges at an Australian research-focused university were invited to participate in the research by attending one of two workshops (2–3 hours in duration) run by the authors. The workshops focused on unearthing and considering aspects of effective STEM learning environments based on the D-STEM Rubric. Fifteen academics from across the two colleges (College of Arts, Law, and Education and College of Sciences and Engineering) voluntarily participated in the study, with academics drawing from a range of discipline areas: computing and information and communication technology (n = 4); medicine and pharmacy (n = 4); education (n = 3); architecture and design (n = 1); mathematics and physics (n = 1); biology (n = 1); and management (n = 1).

At the commencement of the workshop, the participants were given the D-STEM sheets and 25–30 minutes to complete them. Once the forms were completed, all participants attached their drawings to a wall in the room and had time to peruse one another’s drawings. This session was intended to provide the participants with an opportunity to reflect on both the variation in understanding of STEM learning environments within the group and themselves as teachers of STEM. The workshop concluded with a group discussion of the nature of STEM education, which was informed by the D-STEM Rubric and the extent to which each person’s participation had influenced their thinking about and plans for teaching STEM in their own classes.

Data analysis

A deductive analysis (Elo & Kyngäs, 2008) of the drawings and written descriptions of a STEM learning environment was conducted by the first two authors using the D-STEM Rubric, followed by an inductive approach in which the authors identified a list of key elements of teaching and learning of STEM that were evident in drawings and written descriptions. The D-STEM Rubric includes elements of effective STEM learning environments informed by the literature. Specifically, the rubric focuses on evidence of STEM integration, realistic problems, the collaborative nature of STEM, personal experience, multiple representations, and community-industry engagement in either the participants’ drawings or accompanying texts (see Table 1).

The rubric was used to code the elements in a Likert fashion using the following ratings: strong indication, some indication, or no indication. Using the scale enabled the authors to explore the extent to which each element seemed to be represented in drawings or texts. The participants’ perceptions of STEM teaching and learning were then situated on Vasquez’s (2014, p. 13) Inclined Plane of STEM Integration from disciplinary through transdisciplinary. The assignment of the responses within the plane was achieved by focusing on the teaching and learning experiences depicted in the D-STEM, with reference to the examples provided in the online appendix. Where it was not possible to assign participants’ perceptions to one of those planes (e.g., drawings and/or texts portrayed physical learning environment and/or general pedagogy rather than STEM problems or tasks), they were grouped as “Other.”

Further exploration of the participants’ understanding of STEM was undertaken through an analysis of the themes emerging from their responses to the prompt “STEM is…” The themes that were evident in the participants’ responses are discussed extensively in the following section. In both analyses, participants’ names were assigned codes (e.g., P1, P2, P3) to ensure anonymity.

Results

An initial attempt to deductively analyze the participants’ responses based on the D-STEM Rubric had only partial success (Table 2), as both in drawings and texts, the discipline-related teaching aspects were generally less apparent. Many of the drawings (n = 10) presented the physical elements of a learning environment or generic pedagogical approaches without reference to a STEM-specific problem or context (see Appendix B for an indicative example). The focus in those drawings was on the social aspects of the learning process—in particular, spaces for group work and research where students can look up information and discuss with others or where the teacher can present information—and some portrayal of nontraditional teaching approaches in which students are active.

As noted earlier, the second phase of analysis incorporated an inductive approach to identify a list of key elements of STEM teaching and learning that participants included in their D-STEM drawings (Table 3). The text participants provided with their drawings in response to the prompt to describe the drawing was also reviewed to inform the elements proposed in Table 3. Consistent across the analysis of the participants’ responses against the D-STEM Rubric, only some of the responses (n = 7) indicated discipline-specific teaching contexts, and only a few of these responses (n = 5) indicated any integration of STEM disciplines. Closer analysis of the D-STEM responses identified common themes around learning environments (e.g., inside/outside classroom, multifunction/flexible teaching space) and ways of learning (e.g., from existing knowledge, by doing, by inquiry/experimenting/creating), with 9 out of the 15 participants more clearly illustrating nondisciplinary general pedagogy and learning environments as opposed to representing the interdisciplinary nature of STEM.

Although many of the participants viewed STEM teaching as generic pedagogy, in a few cases (P2, P4, P8, P9, and P12), participants provided rich examples of STEM instruction in their D-STEM depictions. These responses illustrated an experimental or investigative process in learning along with the consultation of external people or within an environment outside of the classroom. Such responses included references to an integrated approach to STEM utilizing multiple aspects of STEM knowledge and skills to investigate a practical problem (see Appendices C and D). These participants’ perceptions of STEM teaching and learning are situated at the higher end of Vasquez’s (2014) Inclined Plane of STEM Integration, with their contexts representing either interdisciplinary or transdisciplinary integration (Table 4). The remaining participants’ responses were grouped into the Other category because they only portrayed a physical learning environment or general pedagogy, rather than discipline-specific or STEM teaching and learning practices.

In a disciplinary D-STEM drawing, the context that was represented indicated a purely disciplinary knowledge and skills focus (e.g., P1 identified their representation as “primarily maths education”), and an interdisciplinary D-STEM drawing indicated that disciplinary knowledge and skills were being learned through the interconnection of disciplines without necessarily addressing a specific problem or project (e.g., P4 connected IT/computing, biology/field observations, and chemistry/water sampling without defining an integrated problem or project). Although we were unable to discern any multidisciplinary approaches to STEM learning in the D-STEM diagrams, we could recognize transdisciplinary D-STEM drawings through their inclusion of an authentic context and real-world task or problem (e.g., P2 was focused on studying fish bycatch using knowledge and skills across biology, mathematics, and engineering and technology; P8 represented the integrative and collaborative inputs from zoology, ecology, architecture, and engineering to address threats to wedge-tailed eagles; see Appendices C and D, respectively).

The final level of exploration of the participants’ responses was undertaken by an analysis of the themes emerging from their descriptions to the prompt “STEM is…” Four key themes were identified from the responses (Table 5). Six of the participants literally defined the acronym, and another six participants provided responses that were independent of STEM or any individual STEM discipline. These responses focused on skill development, our understanding of the world, our ways of thinking, and the processes of gaining new knowledge and understanding through inquiry, with P12 specifically mentioning “research” (see Table 6).

Discussion

The analysis of participants’ perceptions of STEM indicated limited understandings of STEM education’s purposes, structures, or signature pedagogies (Shulman, 2005). Few participants were able to describe STEM as transdisciplinary, meaning that it draws from multiple disciplines and engages with relevant and real-world problems. Those who were able to do so came from disciplines or subject or curriculum areas that include a focus on ecological issues (e.g., P2 from fisheries sustainability; P8 from design and conservation), disciplines that are inherently transdisciplinary.

In general, the participants did not provide STEM disciplines–focused responses to the D-STEM instrument; rather, their responses indicate an understanding of STEM in accordance with what Vasquez (2014, p. 11) describes as an (active) “approach to learning.” Their responses suggest that they perceive STEM to be a way of thinking, a way of understanding our world, and an inquiry-based and collaborative way of learning that draws from multiple sources of information. Such approaches to teaching and learning, of course, are not only fundamental aspects of STEM education (Savelsbergh et al., 2016) but also fundamental aspects of any field of education—including individual disciplines within the sciences as well as the arts or humanities. We contend that participants’ responses indicate not only a lack of a clear representation of STEM or STEM disciplines but also a lack of clarity about discipline-related pedagogical knowledge. The responses indicate pedagogical approaches that—although they should be applauded for their good practice—are general in nature and not “centered on the discipline” (Tenenberg & Fincher, 2007, p. 514).

The understandings of STEM unearthed in this research align with research conducted in universities in the United States. In their study of the conceptions of STEM held by university faculty members, Breiner et al. (2012) found that several academics defined STEM in quite a colloquial manner, drawing on their perceptions of how STEM affects their daily lives. Coupled with this finding is an identified lack of focused, pedagogically STEM-relevant PL for university educators (Winberg et al., 2019). Winberg et al. (2019) have argued that for academics to develop interdisciplinary understandings of pedagogy, they need access to PL that incorporates key disciplinary concepts and how to teach them and that draws on pedagogical content knowledge approaches. In the absence of such rich collaborative learning experiences, it would be unsurprising for sophisticated understandings of STEM education to be uncommon among university academics.

The more general focus on ways of thinking, understanding, and learning may also reflect the insularity that we see in many disciplines, particularly at higher education institutions, where academics work to become specialized in a very narrow field of their chosen discipline and potentially commingle their understanding of STEM with their own academic discipline (Breiner et al., 2012). This is likely more of an issue in the fundamental sciences (e.g., chemistry, physics, mathematics), particularly in the first-year units of study, where the focus is the teaching of key skills and knowledge (i.e., STEM disciplinary knowledge) that underpin higher-level learning. Academics who teach students in the later years of their course may view the purpose of their teaching as educating students to become more specialized in one discipline or even subdiscipline (e.g., organic chemistry), as they are themselves, without necessarily acknowledging or thinking about the contributions of other disciplines (e.g., mathematics; technology). Curriculum is undoubtedly a factor, whether it is determined by the institution, discipline, or individual. For example, if there is a continued focus on delivering a content-heavy, single-discipline-focused curriculum, then it is more likely that the learning environment will be at the lower end of Vasquez’s (2014) STEM integration plane: disciplinary. Additionally, institutional funding arrangements are not necessarily conducive to establishing cross-disciplinary collaboration for curriculum development.

Conclusion

The participant academics in this study were drawn from two colleges and diverse disciplines within one university. Although not all participants were active educators of STEM disciplines, all expressed an interest in STEM education and a desire to learn more about it. Their reasons for volunteering to participate in the research differed, but during their introductions to the group, it was clear that the participants regarded STEM as “an important part of understanding the world and making it better” (quote from P3). Moreover, participants found the conversation we led in the latter half of the workshop about the ways that STEM education can be constructed to be rich and informative. P12 called the discussion a “thought-provoking and novel way to immediately respond to your own learning and teaching environment.”

Even though the study was limited by its small sample size, its findings inform discussions about integrated STEM and its place in course offerings in higher education. The drawing task was well received by school principals (Hatisaru et al., 2020) and a research team active in STEM education (Hatisaru et al., 2019), but the structure of the drawing task was met with concern from several participants. Using drawing as a tool for exploring understandings, perceptions, and experiences seems to have been quite a novel and somewhat challenging request for some participants. At least one participant was quite open in asking what it was that we wanted him to draw! Furthermore, it was apparent that some of the participants followed the instructions we gave quite literally, with most of them representing their own pedagogical or physical learning environment within a STEM class (e.g., P6 showed students using microscopes). We cannot be certain whether the difficulty that participants displayed with completing the task was a result of being required to draw something (an unfamiliar activity) or because they had limited understanding about, or ability to imagine, a STEM learning environment (an unfamiliar concept). Our subsequent analysis of their drawings and texts suggests that it is more likely the latter.

The study has revealed that there are several factors to consider when exploring the perceptions of university educators about STEM and its teaching and using these understandings to enhance educational practice. What, if any, educational PL the educators may have had and the extent to which these learning opportunities incorporate a focus on STEM pedagogical competence (Winberg et al., 2019) is an area requiring further interrogation. We contend that the drawing task (D-STEM) does contribute to the discussions on how to best help educators understand what STEM education means and how they might integrate the component disciplines into their classes. As the creation of STEM learning environments may be an unfamiliar idea for many STEM discipline educators and opportunities for them to discuss their pedagogical practice with their peers may be limited, the D-STEM activity could serve to initiate or stimulate discussions (Hatisaru & Fraser, 2021).

Acknowledgment

The Investigating Academics’ Perspectives on STEM project is funded by the University of Tasmania College of Arts, Law and Education Hothouse Research Enhancement Program.

Vesife Hatisaru (v.hatisaru@ecu.edu.au) is an adjunct senior researcher in the School of Education at the University of Tasmania in Tasmania, Australia, and a lecturer in mathematics education at Edith Cowan University in Joondalup Western Australia. Andrew Seen (andrew.seen@utas.edu.au) is the head of discipline, chemistry, and the associate dean for learning and teaching for the College of Science and Engineering; and Sharon Fraser (Sharon.fraser@utas.edu.au) is a professor in science education and the associate head, research, in the School of Education, both at the University of Tasmania in Tasmania, Australia.