Centric Student Assessment Framework Integrating Co-Po And Pso Performance Through An Nlp-Enhanced Obe Approach.

Abstract

This study presents an Outcome-Based Education (OBE) framework integrated with Artificial Intelligence (AI) and Natural Language Processing (NLP) to assess Course Outcomes (CO), Program Outcomes (PO), and Program-Specific Outcomes (PSO). The proposed system leverages data-driven techniques to evaluate student performance holistically, emphasizing cognitive, psychomotor, and affective learning dimensions. A hybrid AI model combining K-Nearest Neighbors (KNN), Decision Trees, and K-Means clustering was used to classify and predict student readiness for industry and entrepreneurial potential. The results demonstrate that integrating AI into OBE-based assessment enhances accuracy, interpretability, and the relevance of academic outcomes to real-world applications.