A fuzzy-based longitudinal model for evaluating practical learning effectiveness in engineering education

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.