A Conceptual Framework for Developing Web Design Competence Based on Multimodal Learning Analytics in Adaptive Digital Environments

Abstract

This study proposes a novel conceptual framework for developing web design competence in adaptive digital learning environments based on multimodal learning analytics (MLA). With the rapid transformation of digital education and the integration of artificial intelligence (AI), traditional approaches to competence development are no longer sufficient. The proposed framework integrates multimodal data sources, including behavioral, cognitive, and affective indicators, to provide personalized learning pathways and real-time feedback. The research adopts a design-based methodology, synthesizing recent advancements in adaptive learning systems, learning analytics, and AI-driven educational models. The findings demonstrate that the integration of MLA enhances students’ web design competence by enabling data-driven decision-making, improving engagement, and supporting individualized learning trajectories. The study contributes to the theoretical and methodological foundations of adaptive digital education and provides practical implications for the design of intelligent learning systems.