Quantitative learning effect evaluation of programming learning tools

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    Children can learn programming using different tools. Understanding how the characteristics and features of each tool impact the learning effect will enhance learning. However, the impact of specific tools on the learning effect is unclear. In this study, we conducted a workshop to evaluate the characteristics and features of six tools on the learning effect. Our study reveals that the learning effect clearly differs between the six tools.

    Original languageEnglish
    Title of host publicationProceedings of 2017 IEEE International Conference on Teaching, Assessment and Learning for Engineering, TALE 2017
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages209-216
    Number of pages8
    Volume2018-January
    ISBN (Electronic)9781538609002
    DOIs
    Publication statusPublished - 2018 Jan 8
    Event2017 IEEE International Conference on Teaching, Assessment and Learning for Engineering, TALE 2017 - Tai Po, Hong Kong
    Duration: 2017 Dec 122017 Dec 14

    Other

    Other2017 IEEE International Conference on Teaching, Assessment and Learning for Engineering, TALE 2017
    CountryHong Kong
    CityTai Po
    Period17/12/1217/12/14

    Fingerprint

    learning success
    programming
    evaluation
    learning

    Keywords

    • programming education
    • programming learning
    • programming learning tools

    ASJC Scopus subject areas

    • Engineering (miscellaneous)
    • Education

    Cite this

    Saito, D., Sasaki, A., Washizaki, H., Fukazawa, Y., & Muto, Y. (2018). Quantitative learning effect evaluation of programming learning tools. In Proceedings of 2017 IEEE International Conference on Teaching, Assessment and Learning for Engineering, TALE 2017 (Vol. 2018-January, pp. 209-216). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TALE.2017.8252335

    Quantitative learning effect evaluation of programming learning tools. / Saito, Daisuke; Sasaki, Ayana; Washizaki, Hironori; Fukazawa, Yoshiaki; Muto, Yusuke.

    Proceedings of 2017 IEEE International Conference on Teaching, Assessment and Learning for Engineering, TALE 2017. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. p. 209-216.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Saito, D, Sasaki, A, Washizaki, H, Fukazawa, Y & Muto, Y 2018, Quantitative learning effect evaluation of programming learning tools. in Proceedings of 2017 IEEE International Conference on Teaching, Assessment and Learning for Engineering, TALE 2017. vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 209-216, 2017 IEEE International Conference on Teaching, Assessment and Learning for Engineering, TALE 2017, Tai Po, Hong Kong, 17/12/12. https://doi.org/10.1109/TALE.2017.8252335
    Saito D, Sasaki A, Washizaki H, Fukazawa Y, Muto Y. Quantitative learning effect evaluation of programming learning tools. In Proceedings of 2017 IEEE International Conference on Teaching, Assessment and Learning for Engineering, TALE 2017. Vol. 2018-January. Institute of Electrical and Electronics Engineers Inc. 2018. p. 209-216 https://doi.org/10.1109/TALE.2017.8252335
    Saito, Daisuke ; Sasaki, Ayana ; Washizaki, Hironori ; Fukazawa, Yoshiaki ; Muto, Yusuke. / Quantitative learning effect evaluation of programming learning tools. Proceedings of 2017 IEEE International Conference on Teaching, Assessment and Learning for Engineering, TALE 2017. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. pp. 209-216
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