Prof. Malissa Maria Mahmud, Sunway University, Malaysia

Malissa Maria Mahmud is the Dean and Professor of Educational Technology at the School of Education, Sunway University, where she is dedicated to making education more accessible, inclusive, and impactful through innovation. Her work explores how digital learning and emerging technologies can transform teaching, engagement, and learner outcomes in an evolving educational landscape. A recognized expert in educational technology, she has shared her insights at international conferences and published in leading academic journals, earning recognition for her contributions to teaching excellence and research in digital education. Passionate about bridging the gap between technology and meaningful learning, she continues to drive practical, research-driven solutions that shape the future of education.

Title：AI in Education: Are We Optimizing or Over-Engineering Learning?
Abstract: The rapid advancement of AI and adaptive learning technologies has transformed digital education, promising greater personalization and efficiency. However, despite widespread adoption, there remains a critical gap in understanding how AI-driven learning impacts cognitive processing, engagement, and long-term knowledge retention. While AI can optimize content delivery and automate assessments, its role in enhancing deep learning, critical thinking, and problem-solving skills remains underexplored. This keynote examines the intersection of AI-driven instructional design, cognitive learning theories, and learning analytics, addressing key challenges and opportunities in leveraging AI for meaningful, pedagogically sound learning experiences. The session will explore:
-The limitations of current AI-based learning models, particularly their reliance on engagement metrics over learning depth.
-How cognitive load theory and self-regulated learning frameworks can inform AI-enhanced personalization strategies.
-The role of real-time learning analytics and adaptive feedback in promoting learner autonomy and metacognition.
By synthesizing empirical research and applied case studies, this session provides a research-backed, practical perspective on the future of AI in education. The discussion will highlight how institutions and educators can move beyond automation to develop AI-powered learning ecosystems that truly enhance learning outcomes.