TRANSFORMING ASSESSMENT, FEEDBACK AND LEARNING ANALYTICS THROUGH ARTIFICIAL INTELLIGENCE

Abstract

This chapter examines how artificial intelligence (AI) is reshaping three interconnected dimensions of education: assessment, feedback, and learning analytics. It traces the shift from assessment as a periodic measure of learning to assessment as an ongoing, integrated process enabled by generative AI, intelligent tutoring systems, adaptive platforms, and predictive analytics. The discussion covers automated and formative assessment, dynamic and adaptive testing, and AI-generated feedback that is personalized, timely, and increasingly used alongside—rather than in place of—human judgment, since evidence shows hybrid AI-teacher-learner approaches outperform either alone. It further explores predictive learning analytics as an early-warning and decision-support tool, AI's role in fostering self-regulated learning and learner autonomy, and its influence on cognitive load, teacher roles, and professional development. Ethical considerations—privacy, algorithmic bias, transparency, academic integrity, and human oversight—are positioned as central rather than peripheral to responsible implementation. The chapter concludes that AI's greatest value lies not in automation but in supporting deeper student understanding, meaningful feedback, and equitable learning outcomes, within a human-centered model where AI provides computational capacity and teachers provide pedagogical judgment, context, and ethical stewardship.