The Role of Artificial Intelligence (AI) in Personalizing Online Learning

Abstract

Purpose: The objective of this study was to examine the role of Artificial Intelligence (AI) in personalizing online learning.
 Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library.
 Findings: The findings revealed that there exists a contextual and methodological gap relating to the role of Artificial Intelligence (AI) in personalizing online learning. Preliminary empirical review revealed the transformative potential of AI in personalizing online learning, aligning with established learning theories and offering practical applications such as adaptive content delivery and data-driven decision-making. However, the responsible and ethical use of AI remains paramount, requiring privacy safeguards and ongoing collaboration among stakeholders. This research underscores AI's capacity to make online education more engaging and effective while emphasizing the need for ongoing exploration and responsible implementation to shape the future of learning.
 Unique Contribution to Theory, Practice and Policy: The Cognitive Load Theory (CLT), the Constructivist Learning Theory and Self-Determination Theory (SDT) may be used to anchor future studies on personalizing online learning. The study made the following recommendations: Incorporating artificial intelligence (AI) effectively into online learning requires institutions to integrate AI-powered personalization tools, continually monitor and improve AI systems, prioritize ethical considerations and transparency, offer professional development for educators, support research and evaluation efforts, focus on customization and scalability, and establish regular feedback mechanisms from all stakeholders. These measures collectively ensure that AI enhances online learning experiences by providing tailored content and recommendations while maintaining data privacy, ethical standards, and educator involvement, ultimately benefiting learners and educators alike.