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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.
Cited literature [16 references]
https://hal.inria.fr/hal-01016428
Contributor : Manuel Lopes <>
Submitted on : Monday, June 30, 2014 - 11:31:51 AM
Last modification on : Wednesday, July 3, 2019 - 10:48:04 AM
Long-term archiving on: : Tuesday, September 30, 2014 - 3:16:02 PM
Contributor : Manuel Lopes <>
Submitted on : Monday, June 30, 2014 - 11:31:51 AM
Last modification on : Wednesday, July 3, 2019 - 10:48:04 AM
Long-term archiving on: : Tuesday, September 30, 2014 - 3:16:02 PM
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edm14mainshortLETTER.pdf
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