Evaluating Learning Effectiveness in Blended Electromagnetic Measurement Training Using a Hybrid EWM-AHP-DEMATEL Weighting Model
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Abstract
Blended practical training in engineering electromagnetic measurement is becoming increasingly prevalent in the context of digital transformation in education. However, due to the inherent complexity of this field, traditional evaluation methods are inadequate for effectively quantifying its technical challenges and accurately assessing student learning outcomes. To address this issue, this study proposes a blended practical training learning effectiveness evaluation method based on a combined EWM-AHP-DEMATEL weighting model. The method employs the Analytic Hierarchy Process (AHP) to determine subjective weights, the Decision Making Trial and Evaluation Laboratory (DEMATEL) technique to analyze inter-indicator correlations and dynamically adjust weights, and the Entropy Weight Method (EWM) to quantify objective weights from the information entropy of measured data, thereby establishing a comprehensive subjective-objective weighting framework. Empirical analysis of representative engineering electromagnetic measurement applications demonstrates that the proposed model effectively preserves expert experiential judgment while significantly reducing subjective bias through objective data-driven entropy analysis. This study provides a scientific diagnostic tool for optimizing blended instruction in electromagnetic measurement training and also offers valuable reference for cultivating high-quality applied talents in the field of electromagnetic non-destructive testing and sensing.
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