Abstract
Current systems aiming at engaging students in Self-Regulated Learning processes are often prompt-based and domain-dependent. Such metacognitive prompts are either difficult to interpret for novices or ignored by experts. Although domain-dependence per se cannot be considered as a drawback, it is often due to a rigid structure which prevents from moving to another domain. We detail here Apex, a two-loop system which provides texts to be learned through summarization. In the first loop, called Reading, the student formulates a query and is provided with texts related to this query. Then the student judges whether each text presented could be summarized. In the second loop, called Writing, the student writes out a summary of the texts, then gets an assessment from the system. In order to automatically perform various comprehension-centered tasks (i.e., texts that match queries, assessment of summaries), our system uses LSA (Latent Semantic Analysis), a tool devised for the semantic comparison of texts.
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Dessus, P., Lemaire, B. (2002). Using Production to Assess Learning: An ILE That Fosters Self-Regulated Learning. In: Cerri, S.A., Gouardères, G., Paraguaçu, F. (eds) Intelligent Tutoring Systems. ITS 2002. Lecture Notes in Computer Science, vol 2363. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47987-2_77
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DOI: https://doi.org/10.1007/3-540-47987-2_77
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