QUALITY MODEL OF TECHNICAL AND PEDAGOGICAL ASPECTS FOR MOODLE PLATFORM IN STUDYING FRENCH LANGUAGE: A CASE STUDY OF MODERN LANGUAGES STUDENTS AT YARMOUK UNIVERSITY

Abstract

This study evaluates the technical and pedagogical quality of the Moodle platform in supporting French language learning at Yarmouk University. A mixed-methods design was employed, combining quantitative and qualitative approaches, with data collected from 250 students in the Department of Modern Languages. The proposed Quality Model encompassed three dimensions: technical quality (usability, accessibility, responsiveness, interface design), general content quality (clarity, interactivity, comprehensiveness), and specialized content quality (French grammar, exercises, pronunciation tools). Data were analyzed using descriptive statistics, reliability tests, factor analysis, Pearson correlation, regression, ANOVA, Kruskal–Wallis tests, and structural equation modeling (SEM). Results revealed high internal consistency (Cronbach’s α > 0.8) and a valid factor structure, with four dominant factors—technical usability, pedagogical tools, learner engagement, and learning outcomes—explaining 68% of variance. Strong positive correlations were found between technical quality and student satisfaction (r = 0.78, p < 0.001), and between content quality and satisfaction (r = 0.72, p < 0.001). Regression analysis confirmed technical aspects as the strongest predictor of satisfaction (β = 0.62, p < 0.001), while content quality accounted for 55% of the variance in satisfaction. SEM results indicated a good model fit (RMSEA = 0.04, CFI = 0.95, TLI = 0.94). Group comparisons showed significant differences in satisfaction by age, academic year, and prior experience with Moodle (p < 0.05), but no significant differences by gender. Hypothesis testing further supported the significant impact of technical usability, pedagogical tools, engagement, and assessment on learning outcomes. The study concludes that both technical and pedagogical dimensions are critical in enhancing Moodle’s effectiveness for language education. Practical recommendations include improving Moodle’s interface design, expanding interactive and specialized content, and strengthening accessibility features. The validated model provides a comprehensive framework for evaluating and optimizing Moodle in language learning contexts, with implications for educators, developers, and policymakers. Future research should extend the model to other languages and institutions and explore the integration of emerging technologies such as AI and VR for personalized and culturally adaptive learning.