Self-Direction in Physics Graduate Education: Insights for STEM from David J. Rowe’s Career-Long Methods

Carol Nash ()
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Carol Nash: History of Medicine Program, Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A1, Canada

Challenges, 2022, vol. 13, issue 2, 1-21

Abstract: The ability to self-direct a research program determines graduate degree completion. Yet, research on incompletion of science, technology, engineering, and mathematics (STEM) graduate programs assumes students’ present level of self-direction adequate and neglects to recognize a lack of self-directed learning (SDL) as key. This essay explores SDL for STEM, presenting the work of theoretical nuclear physicist David J. Rowe as a key example of applying a process of SDL in practice. Rowe focused on this challenge of physics graduate education by promoting SDL through the type of research flow that has been found to bring the greatest satisfaction to researchers regarding their insights. Strategies he explored involved his space, time, open mindedness and theoretical contributions with students and in collaboration with colleagues. A self-directed learner himself, Rowe developed methods of mentoring for encouraging physics graduate students to recognize symmetry as valuable in identifying solutions to problems quickly—helping students take the lead in finding insightful resolutions to complex, multidimensional, mathematical physics uncertainties. These strategies for supporting SDL in this context are examined here, with the use of narrative research to interpret the texts and conversations exchanged with the author. The process of SDL developed by Rowe is presented with recommendations on how Rowe’s methods may be modeled to improve self-direction in STEM graduate education more widely.

Keywords: self-directed learning; STEM; graduate education; David J. Rowe; physics; flow; open mindedness; mentoring; symmetry; narrative research (search for similar items in EconPapers)
JEL-codes: A00 C00 Z00 (search for similar items in EconPapers)
Date: 2022
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