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Students' Expectations of Learning Analytics in a Swedish Higher Education Institution
KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.
KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.ORCID iD: 0000-0002-8543-3774
KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.ORCID iD: 0000-0001-5626-1187
KTH, School of Industrial Engineering and Management (ITM), Learning, Digital Learning.ORCID iD: 0000-0002-9984-6561
2022 (English)In: Proceedings Of The 2022 Ieee Global Engineering Education Conference (Educon 2022) / [ed] Kallel, I Kammoun, HM Akkari, A Hsairi, L, IEEE , 2022, p. 1975-1980Conference paper, Published paper (Refereed)
Abstract [en]

The potential of learning analytics (LA) to improve learning and teaching is high. Yet, the adoption of LA across countries still remains low. One reason behind this is that the LA services often do not adequately meet the expectations and needs of their key stakeholders, namely students and teachers. Presently, there is limited research focusing on the examination of the students' expectations of LA across countries, especially in the Nordic, largely highly digitalized context. To fill this gap, this study examines Swedish students' attitudes of LA in a higher education institution. To do so, the validated survey instrument, Student Expectations of Learning Analytics Questionnaire (SELAQ) has been used. Through the application of SELAQ, the students' ideal and predicted expectations of the LA service and their expectations regarding privacy and ethics were examined. Data were collected in spring 2021. 132 students participated in the study. The results show that the students have higher ideal expectations of LA compared to the predicted ones, especially in regards to privacy and ethics. Also, the findings illustrate that the respondents have low expectations in areas related to the instructor feedback, based on the analytics results. Further, the results demonstrate that the students have high expectations on the part of the university in matters concerning privacy and ethics. In sum, the results from the study can be used as a basis for implementing LA in the selected context.

Place, publisher, year, edition, pages
IEEE , 2022. p. 1975-1980
Series
IEEE Global Engineering Education Conference, ISSN 2165-9567
Keywords [en]
learning analytics, adoption, higher education, students' expectations
National Category
Information Systems, Social aspects Learning
Identifiers
URN: urn:nbn:se:kth:diva-317195DOI: 10.1109/EDUCON52537.2022.9766482ISI: 000836390500289Scopus ID: 2-s2.0-85130488492OAI: oai:DiVA.org:kth-317195DiVA, id: diva2:1695617
Conference
13th IEEE Global Engineering Education Conference (IEEE EDUCON), 28-31 mars 2022, Gammarth, Tunisia
Note

QC 20220914

Part of proceedings: ISBN 978-1-6654-4434-7

Available from: 2022-09-14 Created: 2022-09-14 Last updated: 2022-09-14Bibliographically approved

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Engström, LindaViberg, OlgaBälter, OlleHrastinski, Stefan

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