To use or not to use learning data: A survey study to explain German primary school teachers’ usage of data from digital learning platforms for purposes of individualization

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Digital learning platforms (DLP) provide various types of information about student learning when used for learning and practice. This learning data holds potential for individualized instruction, which has become increasingly necessary for adequately addressing learners’ individual needs. For primary schools in particular, this is important for developing inclusive schools. However, despite the potential of DLP and the learning data that can be obtained from them, they are rarely used by teachers. Furthermore, little is known about factors that lead teachers to use learning data for instruction and individual support. To address this research gap, we conducted an online cross-sectional survey study of N = 272 primary school teachers in Germany. After describing the respondents’ current and previous usage of learning data from DLP, we used structural equation modeling (SEM) to test the influence of predictors on respondents’ intention to use as well as their usage of learning data from DLP. Finally, we discuss the need for increased usage of learning data in teacher education and training, contributing to ongoing debates about the usage of digital learning data in educational research and practice.
Original languageEnglish
Article number920498
JournalFrontiers in Education
Number of pages15
Publication statusPublished - 18.08.2022

Bibliographical note

Funding Information:
This publication was funded by the Open Access Publication Fund of Leuphana University Lüneburg.

This study developed within the CODIP project. CODIP is funded by the Quality Initiative Teacher Training (Qualitätsoffensive Lehrerbildung), a joint initiative of Federal Government and the German states. The financial means were provided by the Federal Ministry of Education and Research (BMBF) (Support code: 01JA2002).

Publisher Copyright:
Copyright © 2022 Hase, Kahnbach, Kuhl and Lehr.

    Research areas

  • Psychology
  • Educational science
  • Data-Based Decision Making, digital learning platforms, individualization, Learning Analytics, primary school teacher, structural equation modeling, Theory of Planned Behavior