Author: Dr. Kalpana Mahesh Patil & Heten Mahesh Patil
DOI Link: https://doi.org/10.70798/Bijmrd/04041030
Abstract: The National Education Policy (NEP) 2020 mandates a structural paradigm shift in Indian commerce education, necessitating a transition from “content-transmission” models to “competency-based” outcome frameworks. However, the operationalization of this mandate specifically the requirement for personalized learning tra- jectories within the Academic Bank of Credits (ABC) ecosystem remains a formidable challenge given the infrastructural constraints of traditional pedagogy. This paper proposes a comprehensive Algorithmic Implementation Framework to bridge this gap. Utilizing a rigorous mixedmethod approach (N = 142), we delineate critical “Structural Caveats” of the current system, primarily the static nature of curricula and the faculty-student digital divide. Subsequently, we propose and test a novel framework utilizing Deep Knowledge Tracing (DKT) and Ontology- Based Curriculum Mapping. Our experimental results demonstrate that this AI- driven approach reduces the “time-to-mastery” for complex financial competencies by 34% (p < 0.001). We conclude that AI is not merely an enhancement but the essential infrastructure for implementing the flexible, credit-based ecosystem envisioned by NEP 2020.
Keywords: National Education Policy, Academic Bank of Credits, Algorithmic Implementation Framework, Deep Knowledge Tracing, Artificial Intelligence.
Page No: 153-159