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Journal of Learning Analytics
Article . 2025 . Peer-reviewed
License: CC BY
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Article . 2025
License: CC BY
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Article . 2025
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Learning Analytics in Schools

Is Digital Data Use Influenced by Teacher-Level or School-Level Factors?
Authors: Michos, Konstantinos; Schmitz, Maria-Luisa; Petko, Dominik;

Learning Analytics in Schools

Abstract

Digital transformation in schools involves the use of digital data to inform teachers’ pedagogical decisions. Previous research indicates that a deeper understanding of the factors influencing teacher utilization of learning analytics and a comprehensive school context analysis is required. In this article, we conducted a survey study with N = 2,247 teachers in 112 upper secondary schools in Switzerland to examine teacher characteristics and school-related factors that impact teacher use of digital data for pedagogical purposes. The results show that teacher characteristics including their positive beliefs about technologies, competency with digital data, and availability of data technologies significantly predict their digital data use, with differences identified between subject matter teachers and schools. School-related factors about digitalization, such as formal and informal collaboration between colleagues and support from school principals, indirectly influence teachers’ digital data use, mediated by teacher characteristics. Based on these results, personalized support can be formulated for teacher utilization of learning analytics according to their characteristics and the supportive school environment.

Keywords

learning analytics, Schools, teachers, digital data use, digital transformation, 370 Education

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Top 10%
Average
Average
Green
gold