Validating the Rifdarmon E-Learning Model with Structural Equation Modeling Analysis for Enhanced Learning Outcomes and Students’ 4C Skills

The rapid development of information and communication technology (ICT) has significantly transformed the landscape of education, including in the context of vocational education. Universitas Negeri Padang (UNP), particularly the Department of Automotive Engineering, has made efforts to adapt the curriculum and learning methods to bridge the gap between education and industry demands. However, in its implementation, there are still challenges that need to be addressed, especially in the Automotive Electronics Electricity course. This study aims to validate the Rifdarmon E-Learning Model in the Automotive Electronics Electricity course through SEM-PLS and CB-SEM analysis using SmartPLS 4. The research employed a quantitative approach using two analysis methods: Structural Equation Modeling-Partial Least Square (SEM-PLS) and Covariance-Based Structural Equation Modeling (CB-SEM). Data were collected from 50 validators comprising experts in educational technology, learning models, and learning media using a 5-point Likert scale questionnaire. The model validation focused on four key syntaxes: Reciprocal Teaching (RT), Mentoring Peers (MP), Organizing Findings (OF), and Narrating Outcomes (NO). The SEM-PLS analysis demonstrated strong construct validity with satisfactory Composite Reliability (CR), Cronbach's Alpha, and Average Variance Extracted (AVE) values across all syntaxes. The CB-SEM analysis further confirmed the model's structural validity with positive outer loading values and good model fit indices. These comprehensive validation results indicate that the Rifdarmon E-Learning Model is both valid and reliable, making it suitable for implementation to enhance learning outcomes and develop students' 4C skills in Automotive Electronics Electricity education.