AI-DRIVEN INCLUSIVE ASSESSMENT: BRIDGING LEARNING DIVERSITY THROUGH INTELLIGENT EDUCATIONAL SYSTEMS

In contemporary educational environments, the increasing diversity of learners characterized by variations in cognitive abilities, socio-cultural backgrounds, and learning preferences— demands a shift from traditional assessment models to more inclusive and adaptive frameworks. This paper explores the role of Artificial Intelligence (AI) and technology in transforming assessment practices to better accommodate diverse learners. It critically examines the limitations of conventional evaluation systems, which often rely on standardized metrics that fail to capture individual learning trajectories and competencies. The study adopts a thematic approach to analyze how AI-driven systems can enable personalized assessment by integrating multiple data points such as attendance, internal performance, engagement