Research and Teaching
By Gary A. Smith, Audriana Stark, and Julie Sanchez
The study shows that instructors, administrators, and faculty developers should view course design not only as a variety of individual approaches, but also as opportunities to stimulate networks to enhance the design process and its impact.
The national call for increasing the graduation of STEM (science, technology, engineering, and mathematics) majors (National Academies of Sciences, Engineering, and Medicine, 2010; President’s Council of Advisors on Science and Technology, 2012) stimulated research and reform focused on undergraduate STEM instruction (National Academies of Sciences, Engineering, and Medicine, 2015, 2017; National Research Council, 2012). In turn, higher education institutions use the emerging research and calls to action to drive redesign of STEM courses and curricula (Association of American Universities, 2017; Dolan et al., 2016; Wieman, 2017).
Multiple sources (Fink, 2013; Felder & Brent, 2016; Handelsman, Miller, & Pfund, 2007; Jones, Noyd, & Sagendorf, 2015; Wiggins & McTighe, 2005) provide a uniform view of the general attributes of the course-design, or redesign, process. Although varying in advocacy for linear or relational approaches, these sources converge on describing course design as the integration of learning objectives, informational content, instructional strategies, and both formative and summative assessment of learning. In addition, designing courses has grown in the last decade to be an important signature program of faculty-development centers (Beach, Sorcinelli, Austin, & Rivard, 2016). Nonetheless, the matter of how STEM instructors responsible for design and delivery of courses conceptualize the design process remains vague.
Understanding course design relates to existing research characterizing teachers’ definitions of teaching and curricula and their descriptions of learning and development as a teacher. Most of this prior work draws on the phenomenographic approach, which originated within higher education research (Tight, 2016). The method has been used to determine how students and teachers conceptualize learning and teaching (e.g., Bowden & Green, 2005; Marton & Säljö, 1976; Trigwell & Prosser, 1999), how faculty conceptualize the meaning of “curriculum” (Fraser & Bosanquet, 2006), and how faculty view their learning and development as teachers (Åkerlind, 2007; McKenzie, 2007, Töytäri et al., 2016).
Primarily phenomenographic studies show consistent variations in how college teachers describe and conceptualize teaching. These conceptualizations range from teacher-focused strategies with the intention of transmitting knowledge, through variously defined intermediate stages to learner-focused strategies intended to foster students’ construction of knowledge and conceptual change (e.g., Kember, 1997; Trigwell & Prosser, 1999; Trigwell, Prosser, & Taylor, 1994; Prosser & Trigwell, 2006; Samuelowicz & Bain, 2001).
A parallel hierarchical view of what it means to develop as a teacher is elucidated in the phenomenographic research of Åkerlind (2007) and McKenzie (2007) in different studies of Australian university faculty. Faculty members’ views of their development span from becoming more familiar with what to teach (to be a more comfortable and confident teacher) to becoming a more effective facilitator of students’ learning via research-based practices regarding student development.
In another qualitative study of Australian faculty, Fraser and Bosanquet (2006) found a range in conceptualizations of “curriculum.” These views ranged from the content of individual courses or a program of study to a dynamic entity developed interactively by faculty and students.
Other work points to the interdependence between individuals and the sociocultural environment of the institution as key elements of faculty work. Boelryk and Amundsen’s (2016) research documents the social influences of faculty members’ interactions with peers, students, and institutional priorities. Similarly, when considering how instructors report what they learn, Töytäri et al. (2016) found four related categories of individual learning, collegial learning, team learning, and innovative partnership learning.
Acknowledging the documentation of multiple conceptualizations of teaching, curriculum, and professional development in the body of literature referenced previously, we use a phenomenographic, qualitative framework to investigate higher education instructors’ understandings of STEM course design. Phenomenography asserts that individuals have different concepts of the world because any person at any time only partially experiences a phenomenon (Bowden & Walsh, 2000; Marton, 1981, 1986). Therefore, people discern contrasting aspects of a concept or a phenomenon to different degrees, including differences that arise in varying context or at different times. This leads to the fundamental nondualistic ontological position in phenomenography; object (in this case, course design) and subject (i.e., teacher) are inseparable because the subject’s experience and understanding of the object is a relationship between the two. Therefore, phenomenography is a second-order research approach because it does not simply seek to describe the phenomenon but rather the relation between the phenomenon and how people experience it from different perspectives.
This study is prompted by the question: What does course design mean to college science and math teachers? The inquiry contributes to the research on teaching that allows instructors to ground their work within the conceptualizations of other teachers while informing faculty developers of effective practices in course-design programs.
This research used a qualitative phenomenographic methodology. The researchers aim to conceptualize the experiences of a phenomenon—the meaning of mathematics and science course design to STEM teachers to describe the participants’ various understandings in a shared, relational, and categorical manner.
The study utilized semistructured interviews, each lasting 60–90 minutes, with nine STEM instructors. The nine participants consisted of tenured professors, full-time nontenure-track teaching faculty, and graduate teaching assistants in STEM disciplines. Although the participants had different levels of teaching experience, all participants completed a STEM course redesign professional development program as part of a team and taught the newly designed course prior to this study. Because of the small sample size, we do not disclose demographic data of the participants to preserve anonymity.
Each interview was a predesigned protocol of open-ended questions, shown in Table 1, with further probing by the interviewer to gain a description of course design. The project was approved by the institutional review board at the authors’ university. The interactions between the interviewer and interviewees aided the instructors to create meaning about the phenomenon of course design (Larsson, & Holmström, 2007). Concrete examples were elicited to understand how and why courses are designed as they are.
Using criterion sampling (Lincoln & Guba, 1985), participants were selected from among members of a STEM professional-development program for course redesign at a research-intensive university. The professional-development program was 1 year long and included an intensive 2.5-day institute followed by monthly meetings and consultations with two faculty developers. Instructors formed teams of 2‒5 members who redesigned an existing gateway science or mathematics course or developed a new course based on literature and best practices in teaching and learning. Each of four annual cohorts included three to four such teams who met together as a faculty learning community. Guided by the approach of Handelsman et al. (2007), each team generated active learning–focused courses based on revised or new learning objectives and accompanied by new formative and summative assessments. Interaction between teams within each cohort and across cohorts allowed for peer input beyond facilitation by the two faculty developers. The program components are described further by Smith and Stark (2016).
Interviews were conducted by an investigator who was not connected to the professional-development program. Audio recordings of the interviews were transcribed and analyzed using qualitative methods in line with a phenomenographic approach.
The three-person research team read the interview transcripts to reveal categories of description (Bowden & Green, 2005), which were identified as qualitatively different meanings or ways of experiencing the phenomenon. The categories emerged in totality from collective participant conceptualizations. Therefore, statements by an individual may fall into various categories, and the categories describe ways of conceptualizing course design and not ways of describing the individual participants. The categories resulted from an iterative analysis process with the researchers challenging, revising, and aligning the transcribed interview utterances to the apparent categories (Bowden & Walsh, 2000). The category descriptions were refined into the outcomes space that represents the course-design phenomenon as experienced by the participants (Marton & Booth, 1997). The research team analyzed all categories to ensure they were distinct, logical, and relational, as is crucial for phenomenographic analysis (Bowden & Green, 2005).
The primary limitation of this study arises from the relatively small sample of STEM participants from a large-enrollment, research-intensive institution, all of whom participated in a team-based, faculty-development program for course redesign. STEM instructors from other institutions, particularly those with more focused teaching missions and smaller class sizes, may conceptualize course design differently from the participants in this study. Likewise, references to experiences in the STEM course redesign initiative indicate conceptualizations of what it means to design a course to include participation in faculty development programs, and learning from peers within faculty learning communities, which will not be true for all STEM instructors. Finally, outcomes may differ for faculty members outside of the STEM field.
Phenomenographic studies refine themes that emerge from interviews into distinct, hierarchically related categories of description. For this study, five qualitatively distinct notions of course design emerged from the interviews (Figure 1). The categories together form an outcomes space depicting the varying conceptualizations of course design. Furthermore, the categories are hierarchically related and ordered in terms of comprehensiveness and complexity that indicates increasing breadth of awareness of the experienced phenomenon.
Following are the five categories of description capturing the ranging ideas of what it means to design a course. Each category is accompanied by an archetypal question.
These categories and their accompanying questions serve as our results from the study. We will now explore each category from the utterances in the transcripts in the following sections.
Category 1 descriptions illustrate course design as a process of selecting content. Participants ask themselves, “What do I teach?” This first category describes course design as an individual action to determine course content based on topical priorities and/or stated learning outcomes along with the time allocated to each topic or outcome (see Table 2). As one participant put it: “I come up with my list of topics, [and] then, [determine] what can be accomplished in said time period.”
The course topics might be a perception of what is traditionally accepted in the discipline, how the course has been previously taught, or the content featured in a textbook. On the basis of this topical list, instructors determine the time to spend on each topic. Student learning outcomes were included as an essential part of designing the course. Some instructors shifted their focus from topics to outcomes throughout time (Table 2, quote c).
Category 2 descriptions illusrate course design as a process of choosing the best methods for instruction (see Table 3). This category is characterized by the question, “How do I best teach this material?” Instructors conceptualize course design as an individual action where they determine the strategies and tools for instruction and assessment. In this category, instructors think about activities for the student to accomplish learning outcomes; for example, “I start to think what was the best format and activities that can allow the students to accomplish those outcomes.”
Participants would question how to best teach after considering the course content or learning outcomes (Table 3, quote a). Some instructors described incorporating in-class and out-of-class learning elements (Table 3, quote b).
A variety of teaching methods used in courses were described. The teaching strategies and tools discussed during the interviews by participants included: preparing lecture videos for online access, interactive lectures, students working in groups, instructor writing on a chalkboard or whiteboard, use of audience-response systems, writing to learn, completing homework assignments, conducting laboratory experiments, collecting data, incorporating real-world examples, and formative and summative assessment that served as learning opportunities. No participant specifically referred to creating lectures as a part of their design. Instead, instructors gravitated toward discussion about active learning techniques and how their methods for engaging learners may change over time (Table 3, quotes c and d).
Category 3 descriptions illustrate course design as a reflective practice that individuals use to improve their own course. The category is characterized by asking, “What is working, what is not working, and how can I make it better?” Course design conceptualized in this category involves an ongoing process of individual reflection on data, experiences, and/or beliefs that inform adjustments to both what is taught and how it is taught (see Table 4). A participant summarized their thinking: “What happened here? Why? Then, as a result of that thinking or reflection, I started to think about how to modify it.”
In this category, design is viewed as an iterative process that is informed by data about student learning (Table 4, quotes a and b). After teaching the course, some instructors focused on reworking the content and pedagogy rather than creating an entirely new approach. However, some instructors felt it necessary to completely discard what was not working in favor of new ideas and material to test in the classroom. Even after developing a track record with a course, some instructors would continue to collect pertinent data and refine the course using analyses from their classroom-action research.
Instructors pointed to various catalysts for their reflection including viewing students as sources of data to inform change. Reflection was triggered by conversations with students, patterns in assessment questions missed by multiple students, watching students and seeing what topics cause unproductive struggle, or reading student ratings (e.g., Table 4, quotes c and d). Participants also reflected on their past student experience to inform their course design decisions (Table 4, quote e).
Category 4 describes course design as a collaboration to improve sections and courses within a department. This category focuses on answering, “How can we align our teaching across sections and courses to make learning experiences better for students?” It is distinct from the previous categories because the discussion moves from “I” to “we” (see Table 5). This conception of course design includes people within a single department collaboratively coordinating instruction across course sections or cooperatively integrating courses within the departmental curriculum. One participant described the collaboration as such: “So, if you’re teaching ‘X’ course and there’s five faculty that are teaching, then the five faculty should get together and decide what the outcomes are.”
Participants noted that course design is fueled by the collaborative energy of engaging with department colleagues. Faculty, graduate students, and administrators within the department are part of an ecosystem for teaching and learning (Table 5, quotes a through e). Instructors share resources and insights from their teaching and the problems they experience. The “collective wisdom” spreads through the department among both advanced and novice instructors and becomes part of what it means to design a course (Table 5, quote c).
Although instructors share resources and knowledge, participants insisted that no one is compelled to teach in a specific manner, so instructors can retain their autonomy. Rather, they are provided with the resources should they choose to use them and encouraged along (Table 5, quote f). Despite varying degrees of experience, participants state that they are regarded as valuable members of their department with expertise in areas that can be added to the shared wisdom of the group.
Category 5 descriptions portray course design as a collective change process across higher education to improve teaching and learning. The category is oriented toward answering, “How can we enlarge our impact and learn from one another to continuously improve teaching and learning in higher education?” This category views course design as an activity that expands beyond a department to embrace people across disciplines and universities to develop a culture to innovate teaching and learning (see Table 6). A participant explained: “I really think that redesigning needs to be a culture. We need to work on redesigning toward a change of culture.”
The collective sharing of teaching practices that are supported by administrators, faculty members, and students define a culture of continuous improvement in teaching and learning across all of higher education.
Expanding design beyond a department includes communication across disciplines. Instructors consider other courses that students encounter along their pursuit of a degree and connect with faculty from those departments to share teaching and learning practices (Table 6, quotes a and b).
Participants discussed being part of an ecosystem of on-campus support centers. Libraries, tutoring centers, and faculty-development centers are local sources for catalyzing and reinforcing a culture for course design that spreads beyond disciplinary boundaries (Table 6, quotes d and e).
Category 5 also includes reaching to neighboring institutions and off-campus resources to improve courses. For example, participants discussed the advantages of working with counterparts at neighboring institutions. In this category, instructors look for models of best practices in teaching and learning across institutions (Table 6, quotes f and g). Professional development conferences and workshops along with research literature are seen as essential diffusion of teaching innovations that inform course design (Table 6, quote h).
To summarize, relevant utterances from interviews were grouped and refined into five distinct interpretations of what it means to design a course. Each category is a mixture of responses that were gleaned from the interviews and refined by the researchers. Categories 1–3 include an individual emphasis on choosing what to teach, how to teach, and what to change in the course. Categories 4 and 5 include a community approach to designing courses within the department, across disciplines, and beyond one’s own institution. This outcome space illustrates course design as both an individual and collective activity of developing a course by considering content, pedagogy, reflection, and a sharing of resources and knowledge.
The conceptions of course design captured in this study point to refining the culture of teaching and learning as a continuous individual and social process of improvement, with the latter including processes within departments, across disciplines, and expanding to other campuses. Designing courses is central to how instructors view teaching, their personal development as a teacher, and their perceptions of learning (Töytäri et al., 2016). How faculty conceptualize course design is also crucial to facilitating instructional-change processes (Henderson, Beach, & Finkelstein, 2011; Kezar, Gehrke, & Elrod, 2015) and thus is an important factor for faculty developers to consider.
It is important to note that our results extend beyond the idea of individual instructors developing courses (Categories 1–3) to a broader conception of course design that entails collaboration among communities of instructors who work together to develop courses (Category 4) and to collective efforts across and beyond institutions (Category 5). This finding is consistent with the view of individual learning, collegial learning, team learning, and innovative partnership learning among faculty as discussed by Töytäri et al. (2016). Elrod and Kezar (2017) similarly regarded organizational learning beyond departments as essential for reforming STEM instruction. Therefore, faculty should seek collaborators within and beyond their disciplinary departments when seeking to design new courses and redesign existing ones, and STEM department chairs and faculty developers should encourage and arrange such networking opportunities.
The strength of this broader concept of course design by the study participants differs from views of collaboration and collectivism as contrary to the culture of higher education (MacGillivray, 2017). It is consistent, however, with Boelryk and Amundsen’s (2016) conclusion that social, as well as individual, factors affect faculty learning about teaching. The broader conceptions of design as collaborative and collective activities also incorporates STEM instructors’ preference for personal evidence rather than empirical evidence (Andrews & Lemons, 2015; Dancy, Henderson, & Turpen, 2016), given that instructors become a part of a supportive ecosystem where personal connections are fostered.
Collectively, the aforementioned body of research, including this study, points to the importance of the instructor as an individual (Categories 1–3), as the member of a department (Category 4), and as part of a larger community within and beyond their own institution (Category 5) as factors in course design. This result matches with the urging by MacGillivray (2017) to catalyze innovation and progress within disciplines across geographic and cultural boundaries. Administrators, including deans and chairs, are important players in shaping the institutional culture (Kelly, 2014), but ultimately it requires energy from stakeholders at all levels, including students and instructors (Oliver & Hyun, 2011).
The work of faculty-development centers to spark and support course design and redesign should move beyond programming for individual instructors. Those interested in catalyzing change to broaden the conception of course design as a collaborative (Category 4) or collective (Category 5) endeavor should work toward promoting a shared vision (Oliver & Hyun, 2011); nurturing communities of practice (Anderson & Schönborn, 2008; Stark & Smith, 2016) and departmental faculty networks (Andrews, Conaway, Zhao, & Dolan, 2016); establishing faculty learning communities (Cox, 2004); guiding and participating in action research projects (Kember & McKay, 1996); and valuing scholarship of teaching and learning (Fraser, 2016; Saroyan & Trigwell, 2015).
The current study reveals hierarchical conceptualizations of course design (Figure 1) that interestingly parallel the results in previous, also mostly phenomenographic, studies of how faculty view teaching (Prosser, Trigwell, & Taylor, 1994; Trigwell & Prosser, 1999) and their development as teachers (Åkerlind, 2007; McKenzie, 2007). For example, Åkerlind (2007) found that instructors envision their development as teachers within a hierarchy from becoming more familiar with what to teach, to becoming more familiar with how to teach, and to finding out which teaching strategies do and don’t work for both teacher and students. This hierarchy in the development as a teacher is mirrored in the findings from this study where instructors perceived course design as what to teach (Category 1), how to teach (Category 2), and reflection on teaching experiences that inform improvement (Category 3). These comparable categories for describing different phenomena may reveal a close relationship between how faculty perceive their development as a teacher and how they perceive course design as a core responsibility. Furthermore, McKenzie (2007) viewed reflective practice as central to faculty members developing from teacher-centered to student-centered views of teaching, which matches with research results focused on how faculty define their teaching approaches (Henderson et al., 2011; McKenzie, 2007; Trigwell, Martin, Benjamin, & Prosser, 2000) and is in line with what emerged in our data for Category 3 (course design as reflective practice). Whereas McKenzie’s (2007) discussion of reflection in the context of teacher development focused on the difference between teachers reflecting on themselves, their teaching, and students’ reactions to teaching, within the conceptualization of course design presented here there is greater faculty reflection on student learning.
To summarize, the results of our research provide a model for understanding what course design means to faculty that can be used by faculty and faculty developers to plan course-design processes. The research results share some characteristics with parallel but different studies about faculty roles in teaching, thus increasing the trustworthiness of the results. Furthermore, what it means to design a course is a process that can be individual or collective, selective or reflective, and a dynamic factor influencing not only teaching, but also the learning that occurs for students.
Åkerlind G. S. (2007). Constraints on academics’ potential for developing as a teacher. Studies in Higher Education, 32, 21–37.
Anderson T. R., & Schönborn K. J. (2008). Bridging the educational research-teaching practice gap. Conceptual understanding, part 1: The multifaceted nature of expert knowledge. Biochemistry and Molecular Biology Education, 36, 309–315.
Andrews T. C., Conaway E. P., Zhao J., & Dolan E. L. (2016). Colleagues as change agents: How department networks and opinion leaders influence teaching at a single research university. Cell Biology Education, 15(2), ar15.
Andrews T. C., & Lemons P. P. (2015). It’s personal: Biology instructors prioritize personal evidence over empirical evidence in teaching decisions. CBE—Life Sciences Education, 14, 1–18.
Association of American Universities. (2017). Progress toward achieving systemic change: A five-year status report on the AAU undergraduate STEM education initiative. Washington DC: Author.
Beach A. L., Sorcinelli M. D., Austin A. E., & Rivard J. K. (2016). Faculty development in the age of evidence. Sterling, VA: Stylus.
Boelryk A., & Amundsen C. (2016). A sociocultural model for mid-career post-secondary teacher professional learning. In Billett S., Dymock D., & Choi S. (Eds.), Supporting learning across working life (pp. 91–111). New York, NY: Springer.
Bowden J. A., & Green P. (Eds.). (2005). Doing developmental phenomenography. Melbourne, Australia: RMIT University Press.
Bowden J. A., & Walsh E. (Eds.). (2000). Phenomenography. Melbourne, Australia: RMIT University Press.
Cox M. D. (2004). Introduction to faculty learning communities. New Directions for Teaching and Learning, 2004(97), 5–23.
Dancy M., Henderson C., & Turpen C. (2016). How faculty learn about and implement research-based instructional strategies: The case of peer instruction. Physical Review Special Topics—Physics Education Research, 12(10110).
Dolan E. L., Lepage G. P., Peacock S. M., Simmons E. H., Sweeder R., & Wieman C. (2016). Improving undergraduate STEM education at research universities: A collection of case studies. Tucson, AZ: Research Corporation for Science Advancement.
Elrod S., & Kezar A. (2017). In-creasing student success in STEM: Summary of a guide to systemic institutional change. Change: The Magazine of Higher Learning, 49(4), 26–34.
Felder R. M., & Brent R. (2016). Teaching and learning in STEM: A practical guide. San Francisco, CA: Jossey-Bass.
Fink L. D. (2013). Creating significant learning experiences: An integrated approach to designing college courses (2nd ed.). San Francisco, CA: Jossey-Bass.
Fraser S. P. (2016). Pedagogical content knowledge (PCK): Exploring its usefulness for science lecturers in higher education. Research in Science Education, 46, 141–161.
Fraser S. P., & Bosanquet A. M. (2006). The curriculum? That’s just a unit outline, isn’t it? Studies in Higher Education, 31, 269–284.
Handelsman J., Miller S., & Pfund C. (2007). Scientific teaching. New York, NY: Freeman.
Henderson C., Beach A., & Finkelstein N. (2011). Facilitating change in undergraduate STEM instructional practices: An analytic review of the literature. Journal of Research in Science Teaching, 48, 952–984.
Jones S. K., Noyd R. K., & Sagendorf K. S. (2015). Building a pathway to student learning: A how-to guide to course design. Sterling, VA: Stylus.
Kelly R. (2014). Informal faculty leadership: Spreading innovative teaching. Academic Leader, 30(6), 2–3.
Kember D. (1997). A reconceptual-isation of the research into university academics’ conceptions of teaching. Learning and Instruction, 7, 255–275.
Kember D., & McKay J. (1996). Action research into the quality of student learning: A paradigm for faculty development. Journal of Higher Education, 65, 528–554.
Kezar A., Gehrke S., & Elrod S. (2015). Implicit theories of change as a barrier to change on college campuses: An examination of STEM reform. Review of Higher Education, 38, 479–506.
Larsson J., & Holmström I. (2007). Phenomenographic or phenomenological analysis: Does it matter? Examples from a study on anaesthesiologists’ work. International Journal of Qualitative Studies on Health and Well-Being, 2, 55–64.
Lincoln Y. S., & Guba E. G. (1985). Naturalistic inquiry. Newbury Park, CA: Sage.
MacGillivray A. E. (2017). Social learning in higher education: A clash of cultures? In McDonald J. & Cater-Steel A. (Eds.), Communities of practice, facilitating social learning in higher education (pp. 27–45). New York, NY: Springer.
Marton F. (1981). Phenomenography—describing conceptions of the world around us. Instructional Science, 10, 177–200.
Marton F. (1986). Phenomenography—a research approach to investigating different understandings of reality. Journal of Thought, 21(3), 28–49.
Marton F., & Booth S. (1997). Learning and awareness. Mahwah, NJ: Erlbaum.
Marton F., & Säljö R. (1976). On qualitative differences in learning: 1—outcome and process. British Journal of Educational Psychology, 46, 4–11.
McKenzie J. (2007, July). Variation in patterns of teacher development and change: Connections with the development of scholarly teaching and the scholarship of teaching. In Research and development in higher education: Enhancing higher education, theory and scholarship. Proceedings of the 30th HERDSA annual conference. Available at:
National Academies of Sciences, Engineering and Medicine. (2010). Rising above the gathering storm, revisited: Rapidly approaching category 5. Washington, DC: National Academies Press.
National Academies of Sciences, Engineering, and Medicine. (2015). Integrating discovery-based research into the undergraduate curriculum. Washington, DC: National Academies Press.
National Academies of Sciences, Engineering, and Medicine. (2017). Indicators for monitoring undergraduate STEM education. Washington, DC: National Academies Press.
National Research Council. (2012). Discipline-based education research: Understanding and improving learning in undergraduate science and engineering. Washington, DC: National Academies Press.
Oliver S. L., & Hyun E. (2011). Comprehensive curriculum reform in higher education: Collaborative engagement of faculty and administrators. Journal of Case Studies in Education, 2, 1–20.
President’s Council of Advisors on Science and Technology. (2012). Engage to excel: Producing one million additional college graduates with degrees in science, technology, engineering, and mathematics. Washington, DC: The White House.
Prosser M., & Trigwell K. (2006). Confirmatory factor analysis of the approaches to teaching inventory. The British Journal of Educational Psychology, 76(Pt 2), 405–419.
Prosser M., Trigwell K., & Taylor P. (1994). A phenomenographic study of academics’ conceptions of science learning and teaching. Learning and Instruction, 4, 217–231.
Samuelowicz K., & Bain J. D. (2001). Revisiting academics’ beliefs about teaching and learning. Higher Education, 41, 299–325.
Saroyan A., & Trigwell K. (2015). Higher education teachers’ professional learning: Process and outcome. Studies in Educational Evaluation, 46, 92–101.
Smith G. A., & Stark A. M. (2016). STEM gateway course redesign teaching professional development: Resources for teaching and learning. Available at
Stark A. M., & Smith G. A. (2016). Communities of practice as agents of future faculty development. Journal of Faculty Development, 30(2), 59–67.
Tight M. (2016). Phenomenography: The development and application of an innovative research design in higher education research. International Journal of Social Research Methodology, 19, 319–338.
Töytäri A., Piirainen A., Tynjälä P., Vanhanen-Nuutinen L., Mäki K., & Ilves V. (2016). Higher education teachers’ descriptions of their own learning: A large-scale study of Finnish Universities of Applied Sciences. Higher Education Research & Development, 35, 1284–1297.
Trigwell K., Martin E., Benjamin J., & Prosser M. (2000). Scholarship of teaching: A model. Higher Education Research & Development, 19, 155–168.
Trigwell K., Prosser M., & Taylor P. (1994). Qualitative differences in approaches to teaching first year university science. Higher Education, 27, 75–84.
Trigwell K., & Prosser M. (1999). Understanding learning and teaching: The experience in higher education. London, England: McGraw-Hill Education.
Wieman C. (2017). Improving how universities teach science: Lessons from the Science Education Initiative. Cambridge, MA: Harvard University Press.
Wiggins G., & McTighe J. (2005). Understanding by design (2nd ed.). Upper Saddle River, NJ: Pearson.
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