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A systematic analysis of learning analytics using multi-source data in the context of Spain

Learning analytics (LA) employs educational data to improve the timeliness of support for learners. Apart from technical aspects, there is a need to understand social complexities brought about by different stakeholders, so as to systematise the adoption of LA in Higher Education (HE). We present an...

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Bibliographic Details
Published in:Behaviour & information technology 2023-04, Vol.42 (5), p.643-657
Main Authors: Muñoz-Merino, Pedro J., Moreno-Marcos, Pedro Manuel, Rubio-Fernández, Aarón, Tsai, Yi-Shan, Gašević, Dragan, Delgado Kloos, Carlos
Format: Article
Language:English
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Summary:Learning analytics (LA) employs educational data to improve the timeliness of support for learners. Apart from technical aspects, there is a need to understand social complexities brought about by different stakeholders, so as to systematise the adoption of LA in Higher Education (HE). We present an analysis of the situation, needs and challenges of LA in the context of Spanish HE, considering managers', teachers' and students' perspectives. Qualitative research is employed using recursive abstraction. Results reveal that the level of institutional adoption is low and none of the analysed institutions had an LA policy. Furthermore, only two of these institutions had an initial LA strategy. While the institutions shared some commonalities in their objectives for LA, chosen tools and adoption challenges, the distinct differences in the political contexts and institutional practices among the institutions reaffirmed that LA solutions and services cannot be implemented in the same manner. Moreover, different needs for LA and concerns are identified about its adoption among managers, students and teachers. These observations lead to our conclusion that the main challenges to implement LA in Spain are not related to technological issues but to the social and cultural issues rooted in institutions and those associated with different stakeholders.
ISSN:0144-929X
1362-3001
DOI:10.1080/0144929X.2022.2039767