Using Production to Assess Learning: An ILE That Fosters Self-Regulated Learning

  • Philippe Dessus
  • Benoît Lemaire
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2363)


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.


Latent Semantic Analysis Summarizable Text Interactive Learn Environment Semantic Comparison Student Essay 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Philippe Dessus
    • 1
  • Benoît Lemaire
    • 1
  1. 1.Laboratoire des Sciences de l’EducationUniversité Pierre-Mendès-FranceGrenoble Cedex 9France

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