Towards a capitalization of processes analyzing learning interaction traces

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Abstract

Analyzing data coming from e-learning environments can produce knowledge and potentially improve pedagogical efficiency. Nevertheless, TEL community faces heterogeneity concerning e-learning traces, analysis processes and tools leading these analyses. Therefore, analysis processes have to be redefined when their implementation context changes: they cannot be reused, shared nor easily improved. There is no capitalization and we consider this drawback as an obstacle for the whole community. In this paper, we propose an independent formalism to describe analysis processes of e-learning interaction traces, in order to capitalize them and avoid these technical dependencies. We discuss both this capitalization and its place and effects in the iterative learning analysis procedure.

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Lebis, A., Lefevre, M., Luengo, V., & Guin, N. (2016). Towards a capitalization of processes analyzing learning interaction traces. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9891 LNCS, pp. 397–403). Springer Verlag. https://doi.org/10.1007/978-3-319-45153-4_33

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