Hary Suswanto, Aripriharta, Anik Nur Handayani, Nandang Mufti, Aede Hatib bin Musta’Amal, Muchamad Wahyu Prasetyo
Assessing the effectiveness of experiential learning in engineering education is challenging because conventional assessment methods are often subjective and inconsistent. Traditional evaluations usually fail to account for changes in student performance over time, resulting in biased and inaccurate results. This paper introduces an advanced fuzzy-based evaluation method that integrates longitudinal analysis and SPSS statistical validation to measure learning effectiveness in practical settings objectively. By examining student performance data from 2022 to 2024, the fuzzy model delivers a flexible and responsive framework for accurately tracking changes in learning over time. Findings indicate that the fuzzy model outperforms traditional approaches, providing greater sensitivity, precision and adaptability in evaluating student learning outcomes. The research also highlights how instructional styles impact student performance trends and provides. © 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
Department of Electrical Engineering and Informatics, Universitas Negeri Malang, Malang, Indonesia; Department of Physics, Universitas Negeri Malang, Malang, Indonesia; Faculty of Educational Sciences and Technology, Universiti Teknologi Malaysia, Johor Bahru, Malaysia
