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

Challenges Pub Date : 2022-09-05 DOI:10.3390/challe13020045
Carol Nash
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引用次数: 2

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.
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物理学研究生教育的自我导向:来自David J. Rowe职业生涯方法的STEM见解
自主指导研究项目的能力决定了研究生学位的完成程度。然而,关于科学、技术、工程和数学(STEM)研究生课程不完成的研究假设学生目前的自我指导水平是足够的,而忽视了自我指导学习(SDL)的缺乏是关键。本文探讨了SDL在STEM中的应用,提出了理论核物理学家David J. Rowe的工作,作为在实践中应用SDL过程的一个关键例子。Rowe专注于物理研究生教育的这一挑战,通过研究流程的类型来促进SDL,这种研究流程已经被发现为研究人员带来了最大的满足感。他探索的策略包括他的空间、时间、开放的思想以及与学生和同事合作的理论贡献。作为一名自我指导的学习者,Rowe开发了指导方法,鼓励物理学研究生认识到对称在快速确定问题解决方案方面是有价值的——帮助学生率先找到复杂的、多维的、数学物理不确定性的深刻解决方案。在这种背景下,这些支持SDL的策略在这里进行了检查,并使用叙事研究来解释与作者交换的文本和对话。Rowe开发的SDL过程提出了关于如何对Rowe的方法进行建模以更广泛地改善STEM研究生教育中的自我指导的建议。
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