Online Optimization and Personalization of Teaching Sequences - Inria - Institut national de recherche en sciences et technologies du numérique
Conference Papers Year : 2014

Online Optimization and Personalization of Teaching Sequences

Benjamin Clément
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Didier Roy
Manuel Lopes
Pierre-Yves Oudeyer

Abstract

In this work we are focused on the tutoring model, that is, how to choose the activities that provide a better learning experience based on the estimation of the student competence levels and progression, and some knowledge about the cognitive and student model. We can imagine a student wanting to acquire many different skills, e.g. adding, subtracting and multiplying numbers. A teacher can help by proposing activities such as: multiple choice questions, abstract operations to compute with a pencil, games where items need to be counted through manipulation, videos, or others. The challenge is to decide what is the optimal sequence of activities that maximizes the average competence level over all skills.
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Dates and versions

hal-01061211 , version 1 (05-09-2014)

Identifiers

  • HAL Id : hal-01061211 , version 1

Cite

Benjamin Clément, Didier Roy, Manuel Lopes, Pierre-Yves Oudeyer. Online Optimization and Personalization of Teaching Sequences. DI : Digital Intelligence - 1st International conference on digital cultures, 2014, Nantes, France. ⟨hal-01061211⟩
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