A framework for informal learning analytics - Evidence from the literacy domain

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Abstract

Multidisciplinary approaches to learning analytics (LA) have the potential to provide important insights into student learning beyond interactions within learning management systems (LMS). In this paper we demonstrate the benefits of such an approach by proposing a framework that adds the contextual elements of task design, tools and technologies and datasets to established LA processes. Our framework was developed as a design science research (DSR) artifact, working with teachers of English at two Swedish secondary schools. The results highlight the importance of valid task design for generating relevant, useful insights and provide a basis for simplifying and automating in-situ LA that can be used by teachers in their everyday work. The study also provided important insights for the field of online research and comprehension (ORC) both in relation to methodology and how students engage with a task that requires locating and synthesizing information on the open Internet in a second language.

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APA

Rizk, A., & Rodriguez, A. (2021). A framework for informal learning analytics - Evidence from the literacy domain. In Proceedings of the Annual Hawaii International Conference on System Sciences (Vol. 2020-January, pp. 1509–1518). IEEE Computer Society. https://doi.org/10.24251/hicss.2021.183

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