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2019 | OriginalPaper | Chapter

Markov Decision Process for MOOC Users Behavioral Inference

Authors : Firas Jarboui, Célya Gruson-Daniel, Alain Durmus, Vincent Rocchisani, Sophie-Helene Goulet Ebongue, Anneliese Depoux, Wilfried Kirschenmann, Vianney Perchet

Published in: Digital Education: At the MOOC Crossroads Where the Interests of Academia and Business Converge

Publisher: Springer International Publishing

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Abstract

Studies on massive open online courses (MOOCs) users discuss the existence of typical profiles and their impact on the learning process of the students. However defining the typical behaviors as well as classifying the users accordingly is a difficult task. In this paper we suggest two methods to model MOOC users behaviour given their log data. We mold their behavior into a Markov Decision Process framework. We associate the user’s intentions with the MDP reward and argue that this allows us to classify them.

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previous chapter Goal Setting and Striving in MOOCs: A Peek Inside the Black Box of Learner Behaviour
next chapter Exploring the Problems Experienced by Learners in a MOOC Implementing Active Learning Pedagogies
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Metadata
Title
Markov Decision Process for MOOC Users Behavioral Inference
Authors
Firas Jarboui
Célya Gruson-Daniel
Alain Durmus
Vincent Rocchisani
Sophie-Helene Goulet Ebongue
Anneliese Depoux
Wilfried Kirschenmann
Vianney Perchet
Copyright Year
2019
Book
Digital Education: At the MOOC Crossroads Where the Interests of Academia and Business Converge

Print ISBN: 978-3-030-19874-9

Electronic ISBN: 978-3-030-19875-6

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-19875-6_9

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