The Student Expectations of Learning Analytics Questionnaire
Open accessAbstract
Student engagement within the development of learning analytics services in Higher Education is an important challenge 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. Therefore, this paper presents a descriptive instrument to measure student expectations (ideal and predicted) of learning analytics services. The scales used in the instrument are grounded in a theoretical framework of expectations, specifically ideal and predicted 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 after a review of the learning analytics literature. 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. The 12‐item Student Expectations of Learning Analytics Questionnaire (SELAQ) provides researchers and practitioners with a means of measuring of students’ expectations of learning analytics services.
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Higher education students have broader expectations of independence and a preference for agency in AI-assisted classrooms.
“This aligns with higher education students' broader expectations of independence [134], and their preference for agency in AI-assisted classrooms [139].”
From AI Sensing and Intervention in Higher Education: Student Perceptions of Learning Impacts, Affective Responses, and Ethical Priorities (2026) · cites this paper as [134]
Cites
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Sample size in factor analysis.
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“The importance of focusing on service user expectations has been demonstrated in both health services (Bowling et al., 2012; Thompson & Suñol, 1995) and technology adoption research (Brown et al., 2012; Brown et al., 2014; Davis & Venkatesh, 2004).”
InfluentialEthical and privacy principles for learning analytics
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“The importance of focusing on service user expectations has been demonstrated in both health services (Bowling et al., 2012; Thompson & Suñol, 1995) and technology adoption research (Brown et al., 2012; Brown et al., 2014; Davis & Venkatesh, 2004).”
InfluentialTsai, Y.-S., & Gasevic, D. (2017) · Proceedings of the Seventh International Learning Analytics & Knowledge Conference · doi:10.1145/3027385.3027400 · Cited by 211 · cited 5× · see citing works
“The challenge of unequal stakeholder engagement in LA implementations is not limited to U.K. higher education institutions (Tsai & Ga š evi ć , 2017a), and it is necessary for each university that is interested in implementing LA services to actively engage with their stakeholders.”
InfluentialSelf-citationAn elephant in the learning analytics room: the obligation to act
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The learning analytics readiness instrument
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Students' privacy concerns in learning analytics: Model development
Mutimukwe, C., Viberg, O., Oberg, L., & Cerratto‐Pargman, T. (2022) · British Journal of Educational Technology · doi:10.1111/bjet.13234 · Cited by 90 · see citing works
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Exploring students’ expectations of learning analytics: A person-centered approach
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“This aligns with higher education students’ broader expectations of independence [134], and their preference for agency in AI-assisted classrooms [139].”
- Authors
- Whitelock‐Wainwright, A., Gašević, D., Tejeiro, R., Tsai, Y., & Bennett, K.
- Affiliations
- University of Liverpool (GB)
- Monash University (AU)
- University of Edinburgh (GB)
- Corresponding author
- Whitelock‐Wainwright, Alexander
- Venue
- Journal of Computer Assisted Learning
- Publisher
- Wiley
- Published
- 2019-06-18
- Volume
- 35
- Issue
- 5
- Pages
- 633-666
- ISSN
- 0266-4909 (ISSN-L)
- 1365-2729
- OpenAlex
- W2952648426
- Cited by
- 63
- References
- 11
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 13 · 2023: 11 · 2022: 12 · 2021: 7 · 2020: 13
- FWCI
- 8.67
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Computer Assisted Learning (publishedVersion, cc-by)
- Monash University Research Portal (Monash University) (publishedVersion, cc-by)
- Liverpool John Moores University (acceptedVersion)
- HAL (submittedVersion)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Social Sciences › Education › Higher Education Practises and Engagement
- Keywords
- learning analytics, student expectations, student agency, higher education, scale development
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