Student Assessment using Generative AI by for Content Specific Challenge Identification

The rapid advancements in Generative AI have revolutionized the landscape of education, particularly in student assessment systems. Traditional assessment methods often fall short of evaluating the diverse capabilities of students. The integration of generative AI can address these gaps by creating personalized, content-specific challenges optimized to individual learning trajectories. This paper explores the application of Generative AI in developing dynamic assessments, ensuring adaptability and scalability across educational contexts. By leveraging natural language processing and deep learning models, the proposed system generates challenges aligned with curriculum objectives, fostering deeper understanding and creativity. Results from experimental implementations highlight improved engagement and performance among students. This work aims to set the stage for future research on AI-driven education systems that bridge the gap between standardized testing and personalized learning.