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Sense of belonging supports student success in science, technology, engineering, and mathematics (STEM), yet prior research indicates that systemic inequities shape who feels included in college classrooms. Racism, sexism, and classism can shape students’ belonging, which then can impact their outcomes. We studied students’ sense of belonging in 56 large introductory biology courses that used active learning, reaching more than 4900 students. We used a QuantCrit methodological framework and hierarchical linear models to examine how the intersection of racism and sexism, and racism and classism, related to three components of students’ belonging. Racism impacted groups differently, and its impact varied across intersecting identities and components of belonging. Sexism undermined women's comfort sharing ideas in class and seeking instructor help across racial/ethnic groups. Women in some racial/ethnic groups experienced greater connectedness to classmates than men. Classism diminished students’ sense of belonging across most racial/ethnic groups. Disaggregating students into more racial/ethnic groups revealed important differences in the experiences of Native American, Latiné, Black/African, and two groups of Asian students. These findings demonstrate that within the same classroom, students can have profoundly different experiences and challenge us to recognize the influence of intersecting forms of oppression on our students. 

Active learning can enhance student outcomes in STEM higher education, but its effectiveness varies with implementation. A key contributor to this variation is the pedagogical knowledge held by instructors. However, little is known about instructors’ pedagogical knowledge of how people learn, how these ideas develop over time, and how knowledge development influences active-learning implementation. This longitudinal qualitative study examined variation, development, and instructional implications of pedagogical knowledge among 11 early-career undergraduate life sciences instructors in the context of their active-learning instruction. We conducted semistructured interviews, including stimulated recall, capturing pedagogical knowledge used to plan, implement, and reflect on a lesson, repeating this process across multiple semesters. We used qualitative content analysis and an analytical framework to identify distinct pedagogical ideas about how people learn used by instructors and their alignment with passive, active, and generative cognitive engagement in the ICAP framework. Longitudinal comparisons revealed that participants did not consistently develop ideas aligned with generative cognitive engagement, indicating that teaching experience is necessary but insufficient to foster development of crucial pedagogical knowledge for effective active learning. Case studies illustrated how knowledge development can influence nuances of active-learning design and implementation. We discuss potential mechanisms of knowledge development and instructional implications. 

What instructors say during class—beyond content—has promise for supporting students’ perceptions that they are supported, connected, and valued in the classroom, which in turn predict positive outcomes in science, technology, engineering, and mathematics (STEM) education. We studied noncontent Instructor Talk used by 56 introductory biology instructors around the United States and how it related to sense of belonging among over 4900 students in their courses. Using hierarchical linear modeling, we identified positive relationships between some—but not all—categories of Instructor Talk and belonging among students. Instructor talk aimed at building relationships with students and explaining pedagogical choices had positive relationships with students’ sense of connectedness to peers (for both) and comfort seeking instructor help (for the former), but not their comfort sharing ideas with the class. Using effect coding, we probed whether these relationships differed for students with 14 intersectional identities, including men and women from seven racial and ethnic groups. Relationships between Instructor Talk categories and components of belonging varied in their direction and magnitude for students with different intersectional identities. Findings demonstrate that even simple instructor actions—particularly language—may be meaningful to students, but we cannot assume that all students experience these actions the same way. 

ABSTRACT Active learning is a phrase that lacks clear definition, which has hampered researchers’ efforts to investigate the nuances of effectiveness and instructors’ efforts to capitalize on potential benefits for students. One way to advance our understanding of “active learning” is assessing by the type of intellectual work that in-class activities require of students. We systematically analyzed in-class work opportunities created for students in 55 introductory biology courses around the United States, each of which used active learning. We did so by adapting an observation approach grounded in the ICAP framework and analyzing classroom videos in 15-s segments. Instructors devoted about a quarter of class time to student work time, on average, but this varied widely. About half of these student work opportunities focused on recall, and half required students to generate answers beyond what had been presented to them, which can foster deeper learning and better transfer than recall alone. The ratio of these levels of intellectual work varied considerably across courses. We also tested whether course- and instructor-level factors predicted the amount and level of active-learning opportunities and found no significant relationships. This work provides a striated definition of active learning that will be useful to researchers studying active-learning outcomes and instructors aiming to harness learning benefits for their students. 

Abstract Desired reforms in undergraduate education require shifts in departmental practices. Department heads are positioned to be change agents, but often lack formal leadership training, and their approaches to change have received little scholarly attention. Research findings from disciplines like organizational management can offer relevant insights. We drew on Kotter’s 8-step model for leading change as a theoretical lens for examining the ideas and actions of heads leading changes to departmental teaching evaluation practices. We used deductive and inductive qualitative content analysis to identify what was present and absent in the approaches taken by department heads. Department heads used some, but not all the steps in the 8-step model and prioritized additional actions. They sought faculty input to foster a sense of ownership in new practices and address concerns. Heads also proposed new changes strategically, worked with colleagues to develop new practices and build buy-in, and aimed to cultivate confidence about the feasibility of new practices. Compared to the 8-step model, heads did not foster a sense of urgency or intentionally craft messaging. Drawing on the collective wisdom of department heads and Kotter’s model, we present an adapted process for leading change in academic departments. The process recognizes the flat hierarchy of academic departments by including iterative steps of proposing, piloting, and revising new practices. It also highlights important steps that might not be the norm in departments, such as formulating careful messaging about the need for a change and repeatedly and intentionally broadcasting progress. 

Inadequate teaching evaluation practices undermine a department's ability to encourage, recognize, and reward effective teaching. Adopting more robust and equitable evaluation practices can address this, but faculty often worry their colleagues will resist such changes. We describe the development of the Teaching Evaluation Readiness Assessment (TERA), a survey to measure faculty readiness for reforming departmental teaching evaluation practices. The TERA is grounded in the readiness for change framework from organizational management, which stipulates components that contribute to productive engagement with an organizational change. This survey is designed to measure the extent to which faculty: (a) see value in teaching evaluation reform for themselves and their department, (b) feel their department would be capable of successfully changing teaching evaluation practices, and (c) perceive that their department head would be supportive of these changes. We used existing instruments, expert review, think-aloud interviews, exploratory factor analysis, confirmatory factor analysis, and comparisons across time and departments to develop the TERA and gather evidence of its validity as a measure of faculty readiness to change teaching evaluation. Findings suggest readiness for reform may be higher than what faculty and change agents perceived anecdotally. We discuss how the TERA can serve change agents and researchers. 

Effective teaching requires teachers to leverage their knowledge of how students think about and learn specific topics (i.e., pedagogical content knowledge). This longitudinal qualitative study of early-career biology instructors examines the development of this specialized teaching knowledge. 

We relied on change theory to design a 3-year intervention with STEM department heads to provide space for busy heads to focus on research-based change in teaching evaluation practices. The impact on departmental practices was variable and department head readiness for change mattered. 

Abstract Background STEM instructors who leverage student thinking can positively influence student outcomes and build their own teaching expertise. Leveraging student thinking involves using the substance of student thinking to inform instruction. The ways in which instructors leverage student thinking in undergraduate STEM contexts, and what enables them to do so effectively, remains largely unexplored. We investigated how undergraduate STEM faculty leverage student thinking in their teaching, focusing on faculty who engage students in work during class. Results From analyzing interviews and video of a class lesson for eight undergraduate STEM instructors, we identified a group of instructors who exhibited high levels of leveraging student thinking (high-leveragers) and a group of instructors who exhibited low levels of leveraging student thinking (low-leveragers). High-leveragers behaved as if student thinking was central to their instruction. We saw this in how they accessed student thinking, worked to interpret it, and responded in the moment and after class. High-leveragers spent about twice as much class time getting access to detailed information about student thinking compared to low-leveragers. High-leveragers then altered instructional plans from lesson to lesson and during a lesson based on their interpretation of student thinking. Critically, high-leveragers also drew on much more extensive knowledge of student thinking, a component of pedagogical content knowledge, than did low-leveragers. High-leveragers used knowledge of student thinking to create access to more substantive student thinking, shape real-time interpretations, and inform how and when to respond. In contrast, low-leveragers accessed student thinking less frequently, interpreted student thinking superficially or not at all, and never discussed adjusting the content or problems for the following lesson. Conclusions This study revealed that not all undergraduate STEM instructors who actively engage students in work during class are also leveraging student thinking. In other words, not all student-centered instruction is student-thinking-centered instruction. We discuss possible explanations for why some STEM instructors are leveraging student thinking and others are not. In order to realize the benefits of student-centered instruction for undergraduates, we may need to support undergraduate STEM instructors in learning how to learn from their teaching experiences by leveraging student thinking. 

Abstract Here, we systematically review research on teaching knowledge in the context of undergraduate STEM education, with particular attention to what this research reveals about knowledge that is important for evidence-based teaching. Evidence-based teaching can improve student outcomes in undergraduate STEM education. However, the enactment of promising evidence-based teaching strategies depends greatly on the instructor and potentially on the teaching knowledge they are able to deploy. The review includes an overview of prevalent teaching knowledge theory, including pedagogical content knowledge, mathematical knowledge for teaching, and pedagogical knowledge. We compare and contrast teaching knowledge theory and terminology across STEM disciplines in order to build bridges for researchers across disciplines. Our search for peer-reviewed investigations of teaching knowledge in undergraduate science, engineering and mathematics yielded 45 papers. We examined the theoretical frameworks used in each study and analyzed study approaches, comparing across disciplines. Importantly, we also synthesized findings from research conducted in the context of evidence-based teaching. Overall, teaching knowledge research is sparse and siloed by discipline, and we call for collaborative work and better bridge-building across STEM disciplines. Though disciplinary divergences are common in discipline-based education research, the effect is magnified in this research area because the theoretical frameworks are themselves siloed by discipline. Investigations of declarative knowledge were common, and we call for increased attention to knowledge used in the practice of teaching. Finally, there are not many studies examining teaching knowledge in the context of evidence-based teaching, but the existing work suggests that components of pedagogical content knowledge, pedagogical knowledge, and content knowledge influence the implementation of evidence-based teaching. We describe implications for future teaching knowledge research. We also call on those who develop and test evidence-based strategies and curriculum to consider, from the beginning, the teaching knowledge needed for effective implementation.