Scaling dialogic peer feedback via learning analytics and scripts

Erkan Er, Yannis Dimitriadis, Dragan Gasevic

    Research output: Chapter in Book/Report/Conference proceedingConference PaperOtherpeer-review


    Dialogic peer feedback is a challenge to design and implement when learning takes place at scale. For proper implementation of dialogic feedback among large learning cohorts, peers’ interactions and learning activities need to be framed and systematized within a solid theoretical perspective. This paper presents a theoretical model of dialogic peer feedback, consisting of three interconnected phases. This model incorporates learning analytics and scripts to support individual and collaborative regulatory processes involved in each phase.

    Original languageEnglish
    Title of host publicationA Wide Lens
    Subtitle of host publicationCombining Embodied, Enactive, Extended, and Embedded Learning in Collaborative Settings - 13th International Conference on Computer Supported Collaborative Learning, Conference Proceedings Volume 2
    EditorsKristine Lund, Gerald P. Niccolai, Elise Lavoue, Cindy Hmelo-Silver, Gahgene Gweon, Michael Baker
    Place of PublicationLyon France
    PublisherInternational Society of the Learning Sciences
    Number of pages2
    ISBN (Electronic)9781732467248
    Publication statusPublished - 2019
    EventComputer Supported Collaborative Learning 2019 - Lyon, France
    Duration: 17 Jun 201921 Jun 2019
    Conference number: 13th (Proceedings)


    ConferenceComputer Supported Collaborative Learning 2019
    Abbreviated titleCSCL 2019
    Internet address

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