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<p>The Interval Fuzzy Rule evaluation for Life Education Programs (IFRE-LEP) has been proposed to improve the accuracy and attain decisions of physical education evaluation from the life education program. The proposed research is of a threefold approach; interval type 2 fuzzy logic is implemented to improve the accuracy and robustness of physical education within life education programs by effectively managing uncertainty based on the instructor’s feedback using a fuzzy rule set. Second, the Interval Matching Degree (IMD) is identified to align the program objective with evaluating fuzzy rule sets using the alpha-cut procedure. Then, an enhanced Karnik–Mendel type reduction algorithm is used to improve the accuracy of the evaluation score of fuzzy rule sets in an interval range followed by a centroid defuzzification process. The system’s efficacy for various performance indicators is demonstrated by comparing the proposed approach with the existing methodologies regarding student participation, learning outcome, program quality, and performance accuracy of the evaluation score. Thus, integrating LEP into PE evaluation seeks to provide a more well-rounded assessment by considering physical fitness, personal development, and life skills, thereby improving college students’ participation in physical activity for future endeavors.</p>

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The Fuzzy Rule Set for College Physical Education Evaluation with Life Education Programs

  • 期刊论文

  • 发表日期：

    2025年1月7日

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  • Yunlong Lv

摘要

The Interval Fuzzy Rule evaluation for Life Education Programs (IFRE-LEP) has been proposed to improve the accuracy and attain decisions of physical education evaluation from the life education program. The proposed research is of a threefold approach; interval type 2 fuzzy logic is implemented to improve the accuracy and robustness of physical education within life education programs by effectively managing uncertainty based on the instructor’s feedback using a fuzzy rule set. Second, the Interval Matching Degree (IMD) is identified to align the program objective with evaluating fuzzy rule sets using the alpha-cut procedure. Then, an enhanced Karnik–Mendel type reduction algorithm is used to improve the accuracy of the evaluation score of fuzzy rule sets in an interval range followed by a centroid defuzzification process. The system’s efficacy for various performance indicators is demonstrated by comparing the proposed approach with the existing methodologies regarding student participation, learning outcome, program quality, and performance accuracy of the evaluation score. Thus, integrating LEP into PE evaluation seeks to provide a more well-rounded assessment by considering physical fitness, personal development, and life skills, thereby improving college students’ participation in physical activity for future endeavors.