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Dispositions, skills, and knowledge form the three components of competency-based education. Moreover, dispositions are considered crucial for students to succeed in the workplace. Few studies investigate how dispositions manifest in the form of observable behaviors, which causes challenges for both students and educators. Computing students, for example, may not understand what is expected of them, and how to achieve dispositions. This paper presents the results of a qualitative, multi-institutional study on students’ understanding of the dispositions adaptable, persistent, self-directed, meticulous, and professional. Perceptions were gathered by asking for exemplary situations of students applying each of the five dispositions in the context of assignments within computing courses. Students who indicated they did not apply the disposition were asked to describe the hindering circumstances. The data was evaluated by using Mayring’s content analysis technique, resulting in the development of deductive-inductive categories of observable behaviors reflecting the student’s perspective. For meticulous and professional, new categories representing observable behaviors were developed. For adaptable, persistent, and self-directed, the authors confirmed and extended prior work. Moreover, factors hindering students in applying the investigated dispositions are identified. The resulting categories with observable student behaviors are an important step toward the operationalization of competency-based learning outcomes including dispositions. A common understanding of dispositions will also help with the design of new forms of instruction and measures to foster the application of dispositions in the context of computing education.
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This content will become publicly available on June 13, 2026
The Self-Directed Disposition: What Computing Students Say
Lifelong learning is essential in computing, given the dynamic nature of the field. Employers and curricular reviewers recognize the value of being self-directed in support of becoming a lifelong learner. The ACM/IEEE-CS Computing Curricula 2020 report identifies self-directed as having elements of self-motivation, determination, and independence. Little is known, however, about how to cultivate this disposition in computing courses. The motivation of this study is to better understand what behaviors computing students believe are self-directed. This study’s research questions are: 1) What do students describe as their self-directed practices in computing? and 2) What do students report are factors that prevent them from being self-directed? Assignments in five undergraduate computing courses from four institutions included prompts to elicit student’s reflections on how they were self-directed (or not). Thematic content analysis using the constant comparative method produced eight categories of self-directed behaviors (utilizing external resources, learning necessary material, working independently, assessing oneself, planning ahead, applying useful techniques, completing the assigned work, and reviewing against expectations). Thematic analysis also resulted in five categories of factors that impeded the self-directed behavior (assignment structure, unsuccessful effort, self-sufficiency, insufficient motivation, and insufficient time). Understanding how students describe self-directedness can help educators design pedagogical and assessment approaches that facilitate self-directed student behaviors in the classroom.
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- PAR ID:
- 10616656
- Publisher / Repository:
- ACM
- Date Published:
- ISBN:
- 9798400715679
- Page Range / eLocation ID:
- 107 to 113
- Format(s):
- Medium: X
- Location:
- Nijmegen Netherlands
- Sponsoring Org:
- National Science Foundation
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