A four-country cross-case analysis of academic staff expectations about learning analytics in higher education

Kaire Kollom, Kairit Tammets, Maren Scheffel, Yi-Shan Tsai, Ioana Jivet, Pedro J. Muñoz-Merino, Pedro Manuel Moreno-Marcos, Alexander Whitelock-Wainwright, Adolfo Ruiz Calleja, More Authors

Research output: Contribution to journalArticleScientificpeer-review

28 Citations (Scopus)
41 Downloads (Pure)


The purpose of this paper is to explore the expectations of academic staff to learning analytics services from an ideal as well as a realistic perspective. This mixed-method study focused on a cross-case analysis of staff from Higher Education Institutions from four European universities (Spain, Estonia, Netherlands, UK). While there are some differences between the countries as well as between ideal and predicted expectations, the overarching results indicate that academic staff sees learning analytics as a tool to understand the learning activities and possibility to provide feedback for the students and adapt the curriculum to meet learners' needs. However, one of the findings from the study across cases is the generally consistently low expectation and desire for academic staff to be obligated to act based on data that shows students being at risk of failing or under-performing.

Original languageEnglish
Article number100788
Pages (from-to)1-19
Number of pages19
JournalInternet and Higher Education
Publication statusPublished - 2021

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.


  • Academic staff
  • Expectations
  • Focus groups
  • Higher education
  • Learning analytics
  • Questionnaire


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