The Student Expectations of Learning Analytics Questionnaire (SELAQ)

Alexander Whitelock-Wainwright, Dragan Gasevic, Ricardo Tejeiro, Yi-Shan Tsai, Kate Bennett

Research output: Contribution to journalArticlepeer-review


Student engagement within the development of learning analytics services in Higher Education is an important challenge for the researchers and practitioners to address. Despite calls for greater inclusion of stakeholders, there still remains only a small number of investigations into students’ beliefs and expectations towards learning analytics services. To meet the challenge of greater participation from the student population in the implementation of learning analytics services, this paper presents a descriptive instrument to measure student expectations (ideal and predicted) of learning analytics services. The scales used in the instrument have been grounded in theoretical framework of expectations, with a specific focus on ideal (hopes) and predicted (realistic beliefs) expectations. Items were then generated on the basis of four identified themes (Ethical and Privacy Expectations, Agency Expectations, Intervention Expectations, and Meaningfulness Expectations), which emerged through the undertaking of a review of the learning analytics literature. The developed instrument was then subject to peer review, pilot testing, and a full roll-out across students at two universities. The results of an exploratory factor analysis and the results from both an exploratory structural equation model and confirmatory factor analysis supported a two-factor structure best accounted for the data pertaining to ideal and predicted expectations. Factor one refers to Ethical and Privacy Expectations, whilst factor two covers Service Feature Expectations. In addition, both scales (ideal and predicted) were found to have good internal reliability. The 12-item Student Expectations of Learning Analytics Questionnaire (SELAQ) provides researchers and practitioners with a reliable and valid instrument to collect quantitative measures of students’ expectations of learning analytics services.
Original languageEnglish
Pages (from-to)633-666
Number of pages34
JournalJournal of Computer Assisted Learning
Issue number5
Early online date18 Jun 2019
Publication statusPublished - Oct 2019


  • higher education
  • ideal expectations
  • learning analytics
  • predicted expectations
  • student expectations


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