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Using Learning Analytics to Interrogate Learning Theories: An Exploration of How Students Learn to Program

Published:07 August 2022Publication History

ABSTRACT

A variety of approaches have been used in computer science education research; one relatively new addition is the use of very large data sets. This dissertation will use one of these data sets in order to investigate the process by which novice students learn to program. Specifically, an iterative approach will be used to determine which learning theories are (or are not) supported by the data. The focus will be on which patterns of behavior do (or do not) lead a student to learning a programming concept.

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  • Published in

    cover image ACM Conferences
    ICER '22: Proceedings of the 2022 ACM Conference on International Computing Education Research - Volume 2
    August 2022
    57 pages
    ISBN:9781450391955
    DOI:10.1145/3501709

    Copyright © 2022 Owner/Author

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