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Semantic visual analytics for today's programming courses

Published:25 April 2016Publication History

ABSTRACT

We designed and studied an innovative semantic visual learning analytics for orchestrating today's programming classes. The visual analytics integrates sources of learning activities by their content semantics. It automatically processs paper-based exams by associating sets of concepts to the exam questions. Results indicated the automatic concept extraction from exams were promising and could be a potential technological solution to address a real world issue. We also discovered that indexing effectiveness was especially prevalent for complex content by covering more comprehensive semantics. Subjective evaluation revealed that the dynamic concept indexing provided teachers with immediate feedback on producing more balanced exams.

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  • Published in

    cover image ACM Other conferences
    LAK '16: Proceedings of the Sixth International Conference on Learning Analytics & Knowledge
    April 2016
    567 pages
    ISBN:9781450341905
    DOI:10.1145/2883851

    Copyright © 2016 ACM

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 25 April 2016

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    • short-paper

    Acceptance Rates

    LAK '16 Paper Acceptance Rate36of116submissions,31%Overall Acceptance Rate236of782submissions,30%

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