Students’ Adoption of Learner Analytics

Carly Palmer Foster*

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

    Abstract

    Learner analytics is an emerging learning and teaching tool which visualises individualised learning data to student users typically via a dashboard or similar platform. In a learner analytics model data are communicated to students directly and often without tutor contact; sense-making is assumed to occur through digital and algorithmic intermediation. Through the collection and analysis of qualitative and quantitative student data, this chapter argues that students’ propensity to adopt analytics is influenced by their existing relationship with data, their discipline, their perception of self and the connections between these factors and the following four benefits: analytics for orientating oneself academically; analytics for improved organization and management; analytics for signposting to support; analytics for fun.
    Original languageEnglish
    Title of host publicationAdoption of Data Analytics in Higher Education Learning and Teaching
    EditorsDirk Ifenthaler, David Gibson
    Place of PublicationCham, Swittzerland
    PublisherSpringer
    Chapter8
    Pages137-158
    Number of pages22
    ISBN (Electronic)9783030473921
    ISBN (Print)9783030473914, 9783030473945
    DOIs
    Publication statusPublished - 11 Aug 2020

    Publication series

    NameAdoption of Data Analytics in Higher Education Learning and Teaching
    PublisherSpringer
    ISSN (Print)2662-2122
    ISSN (Electronic)2662-2130

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