Supporting Learning Analytics Adoption

Authors Justian Knobbout, Esther van der Stappen, Johan Versendaal, Rogier van de Wetering
Published in Applied Sciences
Publication date 2023
Research groups Digital Ethics
Type Article

Summary

Although learning analytics benefit learning, its uptake by higher educational institutions remains low. Adopting learning analytics is a complex undertaking, and higher educational institutions lack insight into how to build organizational capabilities to successfully adopt learning analytics at scale. This paper describes the ex-post evaluation of a capability model for learning analytics via a mixed-method approach. The model intends to help practitioners such as program managers, policymakers, and senior management by providing them a comprehensive overview of necessary capabilities and their operationalization. Qualitative data were collected during pluralistic walk-throughs with 26 participants at five educational institutions and a group discussion with seven learning analytics experts. Quantitative data about the model’s perceived usefulness and ease-of-use was collected via a survey (n = 23). The study’s outcomes show that the model helps practitioners to plan learning analytics adoption at their higher educational institutions. The study also shows the applicability of pluralistic walk-throughs as a method for ex-post evaluation of Design Science Research artefacts.

On this publication contributed

Language English
Published in Applied Sciences
Year and volume 13 5
Key words learning analytics, higher education, adoption, design science research, evaluation, organizational capabilities
Digital Object Identifier 10.3390/app13053236

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