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Employing FFNN and Learning Styles to Improve Knowledge Acquisition in Educational Digital Games

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Novel & Intelligent Digital Systems: Proceedings of the 2nd International Conference (NiDS 2022) (NiDS 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 556))

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Abstract

This paper presents an educational digital game which combines FFNN and learning styles to provide optimal types of learning units to learners so they can advance their knowledge level and improve their and learning outcomes. The digital game has ten stages and its main scope it to teach the players basic computer science concepts. In each stage, there are agents who give the learning units to the player in the gamified environment. The learning activities are delivered using a Feed Forward Neural Network (FFNN) and Weighted Sum Model (WSM) for optimizing the types of delivered learning activities to students based on their learning style. The students’ learning style is based on the Honey and Mumford model. The final output of the FFNN is different types of learning activities, delivered to students. For the evaluation of the game, we used a questionnaire and the statistical hypothesis test. The results show high level of acceptance of the presented model in digital games environment.

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Authors and Affiliations

  1. Department of Informatics and Computer Engineering, University of West Attica, 12243, Egaleo, Greece

    Christos Troussas, Akrivi Krouska & Cleo Sgouropoulou

Authors
  1. Christos Troussas
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  2. Akrivi Krouska
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  3. Cleo Sgouropoulou
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Corresponding author

Correspondence to Christos Troussas .

Editor information

Editors and Affiliations

  1. University of West Attica, Aigaleo, Greece

    Akrivi Krouska

  2. University of West Attica, Aigaleo, Greece

    Christos Troussas

  3. College of Engineering, University of the Philippines, Diliman, Philippines

    Jaime Caro

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Troussas, C., Krouska, A., Sgouropoulou, C. (2023). Employing FFNN and Learning Styles to Improve Knowledge Acquisition in Educational Digital Games. In: Krouska, A., Troussas, C., Caro, J. (eds) Novel & Intelligent Digital Systems: Proceedings of the 2nd International Conference (NiDS 2022). NiDS 2022. Lecture Notes in Networks and Systems, vol 556. Springer, Cham. https://doi.org/10.1007/978-3-031-17601-2_10

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