Students' expectations of Learning Analytics across Europe

Sebastian Wollny*, Daniele Di Mitri, Ioana Jivet, Pedro Muñoz‐Merino, Maren Scheffel, Jan Schneider, Yi‐Shan Tsai, Alexander Whitelock‐Wainwright, Dragan Gašević, Hendrik Drachsler

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


Learning Analytics (LA) is an emerging field concerned with measuring, collecting, and analysing data about learners and their contexts to gain insights into learning processes. As the technology of Learning Analytics is evolving, many systems are being implemented. In this context, it is essential to understand stakeholders' expectations of LA across Higher Education Institutions (HEIs) for large-scale implementations that take their needs into account.
This study aims to contribute to knowledge about individual LA expectations of European higher education students. It may facilitate the strategy of stakeholder buy-in, the transfer of LA insights across HEIs, and the development of international best practices and guidelines.
To this end, the study employs a ‘Student Expectations of Learning Analytics Questionnaire’ (SELAQ) survey of 417 students at the Goethe University Frankfurt (Germany) Based on this data, Multiple Linear Regressions are applied to determine how these students position themselves compared to students from Madrid (Spain), Edinburgh (United Kingdom) and the Netherlands, where SELAQ had already been implemented at HEIs.
Results and Conclusions
The results show that students' expectations at Goethe University Frankfurt are rather homogeneous regarding ‘LA Ethics and Privacy’ and ‘LA Service Features’. Furthermore, we found that European students generally show a consistent pattern of expectations of LA with a high degree of similarity across the HEIs examined. European HEIs face challenges more similar than anticipated. The HEI experience with implementing LA can be more easily transferred to other HEIs, suggesting standardized LA rather than tailor-made solutions designed from scratch.
Original languageEnglish
Pages (from-to)1325-1338
Number of pages14
JournalJournal of Computer Assisted Learning
Issue number4
Early online date7 Mar 2023
Publication statusPublished - Aug 2023


  • Europe
  • Learning Analytics
  • comparison
  • higher education
  • students' expectations


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