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Conference Papers Year : 2014

Online Optimization of Teaching Sequences with Multi-Armed Bandits

Abstract

We present an approach to Intelligent Tutoring Systems which adaptively personalizes sequences of learning activities to maximize skills acquired by each student, taking into account limited time and motivational resources. At a given point in time, the system tries to propose to the student the activity which makes him progress best. We introduce two algorithms that rely on the empirical estimation of the learning progress, one that uses information about the difficulty of each exercise RiARiT and another that does not use any knowledge about the problem ZPDES.
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Dates and versions

hal-01016428 , version 1 (30-06-2014)

Identifiers

  • HAL Id : hal-01016428 , version 1

Cite

Benjamin Clément, Didier Roy, Pierre-Yves Oudeyer, Manuel Lopes. Online Optimization of Teaching Sequences with Multi-Armed Bandits. 7th International Conference on Educational Data Mining, 2014, London, United Kingdom. ⟨hal-01016428⟩
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