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Despite the increasing diversity of undergraduate students in the United States, university faculty demographics, particularly in science, technology, engineering, and mathematics (STEM) fields, remain largely homogeneous, which is problematic for fostering an inclusive academic environment. We examined the hiring process for tenure-track teaching-focused faculty (TFF) positions, specifically within the University of California system, to develop and implement inclusive hiring practices that may promote greater faculty diversity. Through a series of faculty learning communities (FLCs), we developed and implemented inclusive hiring rubrics designed to better evaluate teaching excellence and ensure the recruitment of diverse faculty members. Our findings highlight the critical need for faculty diversity, particularly TFF who instruct in gateway introductory STEM courses, to enhance student outcomes by fostering more inclusive teaching practices and reducing racial disparities in academic achievement. We recommend that institutions adopt inclusive hiring practices, including the use of tailored hiring rubrics, to create a more equitable and supportive learning environment for all students. 

Embedding change agent individuals within STEM departments may drive instructional and pedagogical change efforts. This study seeks to assess whether tenure-track, teaching-focused faculty housed in STEM departments are perceived as influential on the instructional and pedagogical domains of their colleagues. 

Inquiry-based course experiences provide a scalable and equitable way to engage students in research. In this study, we describe how we introduced inquiry-based experiences to ten lower-division and upper-division courses across the biology curriculum at a regionally comprehensive public university serving the diverse population in a major metropolitan area. Student survey data suggest this redesign effectively developed students’ scientific skills and nurtured their sense of belonging. This project illustrates how inquiry-based experiences can be implemented sustainably across institutional context. 

Many science, technology, engineering, and math (STEM) community college students do not complete their degree, and these students are more likely to be women or in historically excluded racial or ethnic groups. In introductory courses, low grades can trigger this exodus. Implementation of high-impact study strategies could lead to increased academic performance and retention. The examination of study strategies rarely occurs at the community college level, even though community colleges educate approximately half of all STEM students in the United States who earn a bachelor’s degree. To fill this research gap, we studied students in two biology courses at a Hispanic-serving community college. Students were asked their most commonly used study strategies at the start and end of the semester. They were given a presentation on study skills toward the beginning of the semester and asked to self-assess their study strategies for each exam. We observed a significantly higher course grade for students who reported spacing their studying and creating drawings when controlling for demographic factors, and usage of these strategies increased by the end of the semester. We conclude that high-impact study strategies can be taught to students in community college biology courses and result in higher course performance. 

Abstract BackgroundThe University of California system has a novel tenure-track education-focused faculty position called Lecturer with Security of Employment (working titles: Teaching Professor or Professor of Teaching). We focus on the potential difference in implementation of active-learning strategies by faculty type, including tenure-track education-focused faculty, tenure-track research-focused faculty, and non-tenure-track lecturers. In addition, we consider other instructor characteristics (faculty rank, years of teaching, and gender) and classroom characteristics (campus, discipline, and class size). We use a robust clustering algorithm to determine the number of clusters, identify instructors using active learning, and to understand the instructor and classroom characteristics in relation to the adoption of active-learning strategies. ResultsWe observed 125 science, technology, engineering, and mathematics (STEM) undergraduate courses at three University of California campuses using the Classroom Observation Protocol for Undergraduate STEM to examine active-learning strategies implemented in the classroom. Tenure-track education-focused faculty are more likely to teach with active-learning strategies compared to tenure-track research-focused faculty. Instructor and classroom characteristics that are also related to active learning include campus, discipline, and class size. The campus with initiatives and programs to support undergraduate STEM education is more likely to have instructors who adopt active-learning strategies. There is no difference in instructors in the Biological Sciences, Engineering, or Information and Computer Sciences disciplines who teach actively. However, instructors in the Physical Sciences are less likely to teach actively. Smaller class sizes also tend to have instructors who teach more actively. ConclusionsThe novel tenure-track education-focused faculty position within the University of California system represents a formal structure that results in higher adoption of active-learning strategies in undergraduate STEM education. Campus context and evolving expectations of the position (faculty rank) contribute to the symbols related to learning and teaching that correlate with differential implementation of active learning. 

The Classroom Observation Protocol for Undergraduate STEM (COPUS) provides descriptive feedback to instructors by capturing student and instructor behaviors occurring in the classroom. Due to the increasing prevalence of COPUS data collection, it is important to recognize how researchers determine whether groups of courses or instructors have unique classroom characteristics. One approach uses cluster analysis, highlighted by a recently developed tool, the COPUS Analyzer, that enables the characterization of COPUS data into one of seven clusters representing three groups of instructional styles (didactic, interactive, and student centered). Here, we examine a novel 250 course data set and present evidence that a predictive cluster analysis tool may not be appropriate for analyzing COPUS data. We perform a de novo cluster analysis and compare results with the COPUS Analyzer output and identify several contrasting outcomes regarding course characterizations. Additionally, we present two ensemble clustering algorithms: 1) k-means and 2) partitioning around medoids. Both ensemble algorithms categorize our classroom observation data into one of two clusters: traditional lecture or active learning. Finally, we discuss implications of these findings for education research studies that leverage COPUS data. 

To understand instruction during the spring 2020 transition to emergency distance learning (EDL), we surveyed a sample of instructors teaching undergraduate EDL courses at a large university in the southwest. We asked them how frequently they used and how confident they were in their ability to implement each of nine promising practices, both for their spring 2020 EDL course and a time when they previously taught the same course face-to-face (F2F). Using latent class analysis, we examined how behavioral frequencies and confidence clustered to form meaningful groups of instructors, how these groups differed across F2F and EDL contexts, and what predicted membership in EDL groupings. Results suggest that in the EDL context, instructors fell into one of three profiles in terms of how often they used promising practices: Highly Supportive, Instructor Centered, and More Detached. When moving from the F2F to EDL context, instructors tended to shift “down” in terms of their profile—for example, among F2F Highly Supportive instructors, 34% shifted to the EDL Instructor Centered profile and 30% shifted to the EDL More Detached Profile. Instructors who reported lower self-efficacy for EDL practices were also more likely to end up in the EDL More Detached profile. These results can assist universities in understanding instructors' needs in EDL, and what resources, professional development, and institutional practices may best support instructor and student experiences.