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Fuzzy-Based Knowledge Design and Delivery Model for Personalised Learning

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Digital Transformation in Education and Artificial Intelligence Application (MoStart 2024)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 2124))

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Abstract

Adaptation to the level of knowledge of each student remains one of the key challenges of e-learning and education in general. E-learning systems provide opportunity for systematic data collection about learning activities offering valuable insights into the students’ knowledge. In order to achieve the personalised learning, this study introduces a Knowledge Design and Delivery Model (KDDM) for intelligent tutoring systems. This model uses a hybrid approach that combines traditional overlay student models with fuzzy logic and multi-criteria decision-making methods. Unlike popular machine learning approaches, these methods do not require existing datasets and they allow direct teacher involvement in knowledge delivery. The KDDM associates student stereotypes with Bloom’s revised taxonomy levels, providing a reference point for the cybernetic model. KDDM has been successfully implemented and examined in a two-year experiment which confirmed its effectiveness on 370 participants from two universities in two countries.

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Authors and Affiliations

  1. University of Mostar, Trg hrvatskih velikana 1, Mostar, Bosnia and Herzegovina

    Tomislav Volarić, Hrvoje Ljubić & Robert Rozić

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  1. Tomislav Volarić
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  2. Hrvoje Ljubić
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  3. Robert Rozić
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Correspondence to Tomislav Volarić .

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Editors and Affiliations

  1. Faculty of Science and Education, University of Mostar, Mostar, Bosnia and Herzegovina

    Tomislav Volarić

  2. Fac. of Mech. Eng., Comp. & Elec. Eng., University of Mostar, Mostar, Bosnia and Herzegovina

    Boris Crnokić

  3. Faculty of Science and Education, University of Mostar, Mostar, Bosnia and Herzegovina

    Daniel Vasić

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Volarić, T., Ljubić, H., Rozić, R. (2024). Fuzzy-Based Knowledge Design and Delivery Model for Personalised Learning. In: Volarić, T., Crnokić, B., Vasić, D. (eds) Digital Transformation in Education and Artificial Intelligence Application. MoStart 2024. Communications in Computer and Information Science, vol 2124. Springer, Cham. https://doi.org/10.1007/978-3-031-62058-4_11

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  • DOI: https://doi.org/10.1007/978-3-031-62058-4_11

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