Digging into Computer Science Students’ Learning Journals
Article No.: 16, Pages 1 - 6
Abstract
Motivation. Learning journals have the potential of providing important pointers to improving students’ learning in Computer Science (CS) higher education. Objectives. We aim to identify, define and categorize attributes of CS students’ notes, and analyze relationships among those attributes. Method. We use a mixed method approach to analyse notes from 184 student journals. The analyzed notes, containing over 100,000 words, represented content of one lecture of an undergraduate course on introduction to software development. Results. We find students’ notes are mostly verbatim with little self-reflection, albeit presenting a rich variety of content highlighting and outlining. Statistical results indicate little correlation among journal attributes. Discussion. We discuss our early results, limitations, future work, and list recommendations around note-taking for instructors.
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Association for Computing Machinery
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Published: 22 November 2020
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Koli Calling '20
Koli Calling '20: 20th Koli Calling International Conference on Computing Education Research
November 19 - 22, 2020
Koli, Finland
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