Supporting Learning Analytics Adoption
Authors | Justian Knobbout, Esther van der Stappen, Johan Versendaal, Rogier van de Wetering |
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Published in | Applied Sciences |
Publication date | 2023 |
Research groups | Betekenisvol Digitaal Innoveren |
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 | Engels |
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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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