Second International Workshop on Teaching Analytics

Ravi Vatrapu, Peter Reimann, Wolfgang Halb, Susan Bull

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    Abstract

    Teaching Analytics is conceived as a subfield of learning analytics that focuses on the design, development, evaluation, and education of visual analytics methods and tools for teachers in primary, secondary, and tertiary educational settings. The Second International Workshop on Teaching Analytics (IWTA) 2013 seeks to bring together researchers and practitioners in the fields of education, learning sciences, learning analytics, and visual analytics to investigate the design, development, use,
    evaluation, and impact of visual analytical methods and tools for teachers’ dynamic diagnostic decision-making in real-world settings.
    Original languageEnglish
    Title of host publicationProceedings of the Third International Conference on Learning Analytics and Knowledge. LAK '13
    EditorsDan Suthers, Katrien Verbert, Erik Duval , Xavier Ochoa
    Place of PublicationNew York
    PublisherAssociation for Computing Machinery
    Publication date2013
    Pages287-289
    ISBN (Print)9781450317856
    DOIs
    Publication statusPublished - 2013
    EventThe 3rd International Conference on Learning Analytics and Knowledge - University of Leuven, Leuven, Belgium
    Duration: 8 Apr 201312 Apr 2013
    Conference number: 3
    http://lakconference2013.wordpress.com/

    Conference

    ConferenceThe 3rd International Conference on Learning Analytics and Knowledge
    Number3
    LocationUniversity of Leuven
    CountryBelgium
    CityLeuven
    Period08/04/201312/04/2013
    Internet address
    SeriesACM International Conference Proceeding Series

    Cite this

    Vatrapu, R., Reimann, P., Halb, W., & Bull , S. (2013). Second International Workshop on Teaching Analytics. In D. Suthers, K. Verbert, E. Duval , & X. Ochoa (Eds.), Proceedings of the Third International Conference on Learning Analytics and Knowledge. LAK '13 (pp. 287-289 ). Association for Computing Machinery. ACM International Conference Proceeding Series https://doi.org/10.1145/2460296.2460360