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A Multi-agent Based Adaptive E-Learning System

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Computational Science and Its Applications – ICCSA 2021 (ICCSA 2021)

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Abstract

In this paper, a multi-agent based adaptive e-learning system that supports personalization based on learning styles is proposed. Considering that the importance of distance education has increased with the effect of the Covid-19 pandemic, it is aimed to propose an adaptive e-learning system solution that offers more effective learning experiences by taking into account the individual differences in the learning processes of the students. The Felder and Silverman learning style model was used to represent individual differences in students’ learning processes. In our system, it is aimed to recommend learning materials that are suitable for learning styles and previous knowledge levels of the students. With the multi-agent based structure, an effective control mechanism is devised to monitor the interaction of students with the system and to observe the learning levels of each student. The purpose of this control mechanism is to provide a higher efficiency in the subjects the students study compared to non-personalized e-learning systems. This study focuses on the proposed architecture and the development of the first prototype of it. In order to test the effectiveness of the system, personalized course materials should be prepared according to the learning styles of the students. In this context, it is planned to use the proposed system in future studies within the scope of a course in which the educational content is personalized.

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Acknowledgments

This study was supported by Ege University Scientific Research Projects Coordination Unit (Project number 18-MUH-035).

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Authors and Affiliations

  1. Department of Computer Engineering, Ege University, 35100, Bornova, Izmir, Turkey

    Birol Ciloglugil, Oylum Alatli & Riza Cenk Erdur

  2. Department of Computer Education and Instructional Technology, Ege University, 35100, Bornova, Izmir, Turkey

    Mustafa Murat Inceoglu

Authors
  1. Birol Ciloglugil
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  2. Oylum Alatli
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  3. Mustafa Murat Inceoglu
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  4. Riza Cenk Erdur
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Correspondence to Birol Ciloglugil .

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Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Cagliari, Cagliari, Italy

    Chiara Garau

  5. University of Cagliari, Cagliari, Italy

    Ivan Blečić

  6. Monash University, Clayton, VIC, Australia

    David Taniar

  7. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  8. University of Minho, Braga, Portugal

    Ana Maria A. C. Rocha

  9. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

  10. Polytechnic University of Bari, Bari, Italy

    Carmelo Maria Torre

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Ciloglugil, B., Alatli, O., Inceoglu, M.M., Erdur, R.C. (2021). A Multi-agent Based Adaptive E-Learning System. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science(), vol 12951. Springer, Cham. https://doi.org/10.1007/978-3-030-86970-0_48

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  • DOI: https://doi.org/10.1007/978-3-030-86970-0_48

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