Reconceptualizing Digital Pedagogy: Integrating Artificial Intelligence and Learning Analytics for Adaptive Education Systems

Abstract

This study reconceptualizes digital pedagogy by integrating artificial intelligence (AI) and learning analytics as core drivers of adaptive education systems. While existing research has largely positioned digital technologies as supplementary instructional tools, this study argues that AI and data-driven systems fundamentally reshape pedagogical structures, learner engagement, and educational outcomes. Using a systematic literature review approach, this study synthesizes recent developments in artificial intelligence in education and learning analytics to identify key patterns and conceptual relationships. The findings reveal that effective digital pedagogy is characterized by the integration of AI-driven personalization, learning analytics, pedagogical alignment, and continuous feedback mechanisms. Based on these findings, this study proposes an Adaptive Digital Pedagogy Framework that conceptualizes digital learning as a dynamic and multidimensional system. This framework highlights the importance of aligning technological capabilities with instructional design to support adaptive and data-informed learning environments. This study contributes to the literature by offering a unified theoretical framework that bridges previously fragmented domains of AI in education and learning analytics. It also provides practical implications for educators and policymakers in designing scalable, adaptive, and inclusive education systems in the digital era.