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Implementation of an Adaptive Mechanism in Moodle Based on a Hybrid Dynamic User Model

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The Challenges of the Digital Transformation in Education (ICL 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 916))

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Abstract

Learning styles summarizes the concept that individuals have different learning preferences and they learn better when they receive information in their preferred way. Even though learning styles have been subjected to some criticism, they can play an important role in adaptive e-learning systems. In order to overcome the drawbacks of the traditional detection method, educational data mining techniques have been implemented in these systems for the automatic detection of students’ learning styles. The purpose of this paper is to present the implementation of an adaptive mechanism in Moodle. The proposed mechanism is based on a hybrid dynamic user model that is built with techniques that are based both on learner knowledge and behavior. An evaluation study was conducted in order to examine the effectiveness of the proposed mechanism. The results were encouraging since they indicated that our extension affected students’ motivation and performance. In addition, the precision attained by the proposed automatic detection approach was rather positive.

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Author information

Authors and Affiliations

  1. Department of Applied Informatics, University of Macedonia, 54006, Thessaloniki, Greece

    Ioannis Karagiannis & Maya Satratzemi

Authors
  1. Ioannis Karagiannis
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  2. Maya Satratzemi
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Corresponding author

Correspondence to Ioannis Karagiannis .

Editor information

Editors and Affiliations

  1. Carinthia University of Applied Sciences , Villach, Kärnten, Austria

    Michael E. Auer

  2. Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece

    Thrasyvoulos Tsiatsos

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Karagiannis, I., Satratzemi, M. (2020). Implementation of an Adaptive Mechanism in Moodle Based on a Hybrid Dynamic User Model. In: Auer, M., Tsiatsos, T. (eds) The Challenges of the Digital Transformation in Education. ICL 2018. Advances in Intelligent Systems and Computing, vol 916. Springer, Cham. https://doi.org/10.1007/978-3-030-11932-4_36

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