Exploring students’ expectations of learning analytics: A person-centered approach
Open accessAbstract
In order to successfully implement learning analytics (LA), we need a better understanding of student expectations of such services. Yet, there is still a limited body of research about students’ expectations across countries. Student expectations of LA have been predominantly examined from a view that perceives students as a group of individuals representing homogenous views. This study examines students’ ideal (i.e., representing their wanted outcomes) and predicted expectations (i.e., unveiling what they realistically expect the LA service is most likely to be) of LA by employing a person-centered approach that allows exploring the heterogeneity that may be found in student expectations. We collected data from 132 students in the setting of Swedish higher education by means of an online survey. Descriptive statistics and Latent Class Analysis (LCA) were used for the analysis. Our findings show that students’ ideal expectations of LA were considerably higher compared to their predicted expectations. The results of the LCA exhibit that the Swedish students’ expectations of LA were heterogeneous, both regarding their privacy concerns and their expectations of LA services. The findings of this study can be seen as a baseline of students’ expectations or a cross-sectional average, and be used to inform student-centered implementation of LA in higher education.
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Students are not willing to disclose all data for AI applications despite anticipated benefits.
“Initial study results indicate (Howell et al., 2018;Viberg et al., 2022;West, Heath, et al., 2016;West, Huijser, et al., 2016a, 2016b) that students are not willing to disclose all data for AI applications despite anticipated benefits.”
From Artificial Intelligence in Education: Implications for Policymakers, Researchers, and Practitioners (2024) · cites this paper as Viberg et al., 2022
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- Authors
- Viberg, O., Engström, L., Saqr, M., & Hrastinski, S.
- Affiliations
- KTH Royal Institute of Technology (SE)
- University of Eastern Finland (FI)
- Corresponding author
- Viberg, Olga
- Venue
- Education and Information Technologies
- Published
- 2022-03-09
- Volume
- 27
- Issue
- 6
- Pages
- 8561-8581
- ISSN
- 1360-2357 (ISSN-L)
- 1573-7608
- OpenAlex
- W4221075601
- Cited by
- 35
- References
- 58
- Citations by year
- 2026: 6 · 2025: 9 · 2024: 6 · 2023: 12 · 2022: 2
- FWCI
- 5.60
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Education and Information Technologies (publishedVersion, cc-by)
- Funders
- Royal Institute of Technology
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Keywords
- learning analytics, student expectations, person-centered approach, privacy concerns, university students, Swedish higher education
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