Thesis of Lemya Settouti
Subject:
Defense date: 01/10/2011
Advisor: Alain Mille
Coadvisor: Nathalie Guin
Summary:
One of the most active research problems in Technology‐Enhanced Learning (TEL)
Systems is Learner Modelling (LM). The main motivation in LM‐field concerns the elaboration
of the model of the learner which consists to deduce, from the learner's activities
observation, a description of his knowledge and skills. Obtaining and instantiating such a
model constitutes a classical and complex objective for any TEL aiming to personalize and to
individualize learner’s activities. In this thesis, we are interested in the knowledge allowing
the interpretation of the learning activity traces to elaborate the learner model. For that, we
are working to define a conceptual and computational generic framework, integrating
mechanisms of inferences allowing the traces analysis and learner model elaboration. An
implementation of such framework will support TEL‐designer in the task of LM. So, a TEL‐
designer, within this framework, can describes the activity traces model, the Learner Model
to establish (knowledge and skills of the learner, and how they are represented), and
describes also (in a formal language to be defined) the learner model elements will be
inferred and/or calculated from trace elements.