To Balance Innovation with Care

Artificial intelligence for personalized learning: a systematic literature review by Glenn Hardaker; Liyana Eliza Glenn, Corresponding Author
International Journal of Information and Learning Technology, January 13, 2025

The integration of artificial intelligence (AI) into personalized learning presents both strategic opportunities and ethical responsibilities for educational leaders. Personalized learning, defined as instruction that optimizes pace and approach to meet individual learner needs, requires leadership that prioritizes responsiveness, equity, and coherence across instructional systems. AI, grounded in computer science and theories of human intelligence, enables schools to move beyond static instructional models by leveraging advanced data analysis to adapt content, assessment, and delivery to learners’ evolving needs. From a leadership perspective, the emergence of AI-supported digital classrooms and learning analytics reshapes how teaching and learning are monitored and managed. Machine learning applications, such as automated assessment, performance prediction, and adaptive feedback, offer efficiencies that can support instructional improvement at scale. However, educational leaders must critically evaluate how these tools influence professional judgment, student autonomy, and instructional quality. While AI can reduce reliance on predefined algorithms and increase responsiveness to learner performance, it also introduces heightened demands for ethical oversight, transparency, and alignment with pedagogical values. Effective educational leadership, therefore, involves stewarding AI integration in ways that balance innovation with care.