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This full research paper contributes to current work on fostering the collaborative disposition among computing and engineering students. Collaborative work is essential in computing and engineering, given the scope and complexity of the projects within these fields. However, little is known about how to cultivate this disposition in the undergraduate classroom. The motivation of this research is to identify the categories of behaviors that students associate with being collaborative. The research questions for this study are: 1) What do students describe as collaborative practices applied to their coursework? and 2) What do students report as factors that prevent them from being collaborative? In computing courses at three institutions, students were asked to complete programming assignments and complete a reflection prompt after each assignment that asked “Describe an example of you being collaborative when completing this assignment. Otherwise, describe the circumstances that prevented you from being collaborative”. Responses were qualitatively/thematically analyzed resulting in the identification of ten categories of collaborative behaviors and nine categories of factors that impeded collaborative behavior. The significance of the study is that it deepens understanding of the collaborative disposition and identifies conditions that promote or discourage it. The results of this work will help educators design classroom interventions that will facilitate the development of the collaborative disposition among computing and engineering students.
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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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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Conference Paper:
- https://doi.org/10.1145/3724363.3729114
