Proceedings of the 4th International Conference on Social Science, Humanity and Public Health, ICoSHIP 2023, 18-19 November 2023, Surabaya, East Java, Indonesia

Research Article

Student Modelling and Classification Rules Learning for Educational Resource

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  • @INPROCEEDINGS{10.4108/eai.18-11-2023.2342552,
        author={Enik  Rukiati and Shabrina  Choirunnisa and Fredy Eka Ardhi Pratama and Khafidurrohman  Agustianto},
        title={Student Modelling and Classification Rules Learning for Educational Resource},
        proceedings={Proceedings of the 4th International Conference on Social Science, Humanity and Public Health, ICoSHIP 2023, 18-19 November 2023, Surabaya, East Java, Indonesia},
        publisher={EAI},
        proceedings_a={ICOSHIP},
        year={2024},
        month={1},
        keywords={student modeling e-learning rule-based system},
        doi={10.4108/eai.18-11-2023.2342552}
    }
    
  • Enik Rukiati
    Shabrina Choirunnisa
    Fredy Eka Ardhi Pratama
    Khafidurrohman Agustianto
    Year: 2024
    Student Modelling and Classification Rules Learning for Educational Resource
    ICOSHIP
    EAI
    DOI: 10.4108/eai.18-11-2023.2342552
Enik Rukiati1, Shabrina Choirunnisa2,*, Fredy Eka Ardhi Pratama3, Khafidurrohman Agustianto2
  • 1: Language, Communication and Tourism, Politeknik Negeri Jember
  • 2: Department of Information Technology Department, Politeknik Negeri Jember
  • 3: Department of Agribusiness Management, Politeknik Negeri Jember
*Contact email: shabrinacnisa@polije.ac.id

Abstract

Learning management systems are commonly used to present learning content to students assuming that each student has the same characteristics in terms of expectations, culture, background, and learning style. But in reality, each student has different characteristics. This is supported by a learning concept that focuses on conveying general learning content without considering individual differences. This study aims to solve this problem by presenting student modeling specifically for e-learning/distance learning applications. In this study, a learning style modeling using the Felder-Silverman learning style model was conducted and it aimed at students' interaction with e-learning. The research results show that the method applied in the research is efficient, with an accuracy value of 96.35%.