Predicting Implementation of Active Learning by Tenure-Track Teaching Faculty Using Robust Cluster Analysis

Autor/inn/en	Denaro, Kameryn; Kranzfelder, Petra; Owens, Melinda T.; Sato, Brian; Zuckerman, Austin L.; Hardesty, Rebecca A.; Signorini, Adriana; Aebersold, Andrea; Verma, Mayank; Lo, Stanley M.
Titel	Predicting Implementation of Active Learning by Tenure-Track Teaching Faculty Using Robust Cluster Analysis
Quelle	In: International Journal of STEM Education, 9 (2022), Artikel 49 (21 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Denaro, Kameryn)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2196-7822
DOI	10.1186/s40594-022-00365-9
Schlagwörter	Active Learning; College Faculty; Tenure; Teacher Characteristics; Teacher Researchers; Nontenured Faculty; Academic Rank (Professional); Teaching Experience; Gender Differences; Intellectual Disciplines; Geographic Location; Class Size; STEM Education; Undergraduate Study; California + Suchen Sie Ihr Suchwort? Aktives Lernen; Fakultät; Amtszeit; Beschäftigungsdauer; Lehrerforschung; Geschlechterkonflikt; Geisteswissenschaften; Klassengröße; STEM; Grundstudium; Kalifornien
Abstract	Background: The 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. Results: We 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. Conclusions: The 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. (As Provided).
Anmerkungen	Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01