A Framework for Applying Generative AI in Outcome Based Teaching Learning Systems

An example of a revolutionary shift in Indian higher education is the integration of Generative Artificial Intelligence (GenAI) into the Outcome-Based Education (OBE) framework mandated by AICTE, NBA, and NAAC. This paper examines how GenAI tools—particularly large language models, content-generation systems, and adaptive learning platforms—can support every stage of the OBE cycle, including curriculum design, delivery, assessment, feedback, and accreditation documentation. It maps specific GenAI applications to OBE components, showing how AI can automate CO–PO–PSO mapping, create adaptive and multilingual learning resources, generate question banks aligned with Bloom’s taxonomy, and provide analytics-driven feedback for continuous improvement. The study emphasizes how GenAI can increase consistency, efficiency, and transparency in meeting accreditation requirements while enabling more personalized and student-centric learning. It also addresses critical challenges related to data integrity, ethical use, plagiarism, and faculty readiness, and proposes directions for responsible and sustainable adoption of GenAI in Indian engineering education.