کنفرانس بین المللی یادگیری و یاددهی الکترونیکی ایران

صفحه اصلی / نوزدهمین کنفرانس ملی و سیزدهمین کنفرانس بین المللی یادگیری و یاددهی الکترونیکی ایران

LSFIS: A Fuzzy Inference System to Identify the Learning Styles in E-Learning Environment

نویسندگان :

Mohammadreza Amiri¹ Gholam Ali Montazer² Alireza Abdolhosseinzadeh³

1- Tarbiat Modares University 2- Tarbiat Modares University 3- Tarbiat Modares University

کلمات کلیدی :

E-learning،Learning Style،Learner Behavior Modeling،Felder-Silverman Model،Fuzzy Inference System

چکیده :

Learners have diverse learning styles, preferring different types of information and using distinct methods to process it. As a result, their learning efficiency and achievement vary. Learning effectiveness depends on the information provided and the interactive activities used. Traditionally, standard questionnaires in educational sciences and learning psychology identify learning styles. However, in e-learning, with learner-centered approaches and minimal teacher guidance, conventional questionnaires may not be practical. This paper proposes an alternative approach to determine learning styles by analyzing learners’ behaviors and network activities in e-learning environments. Since human behaviors are often conceptual, uncertain, and dynamic, fuzzy set theory is used to model them. The proposed Learning Style Fuzzy Identification System (LSFIS) is evaluated against standard questionnaires, showing an average correlation of 79.8%, demonstrating its effectiveness in identifying learning styles.