Title: Scientific competence and acquisition challenges in education managed by analytics

Authors: K.K. Ramachandran; Budhi Sagar Mishra; Himani Oberai; Gazala Masood; Ila Mehrotra Anand; Nidhi Shukla

Addresses: Department of Management, Commerce and International Business, Dr. G.R.D. College of Science, Coimbatore, Tamil Nadu, India ' Department of Management, L.N. Mishra College of Business Management, Muzaffarpur, Bihar, India ' Department of Management, GLA University, Mathura, India ' Faculty of Commerce and Management, Rama University, Kanpur, India ' School of Business and Management, CHRIST University, Bengaluru, Karnataka, India ' Presidency Business School, Presidency College, Bangalore, Karnataka, India

Abstract: Integration of instructional, informational, and communication technology underpins modern higher education. After decades without computer networks, these technologies have transformed learning. E-learning has transformed the education sector, solving its problems. The similarities between technology and cognition make this change noteworthy. Artificial intelligence-inspired model-based reinforcement learning lets agents predict states and outcomes across activities and settings to modify their behaviour. The human brain has similar mechanisms, especially in model selection, which is a fascinating mystery. This study examined the brain's model selection process and found that sensory prediction errors motivate the brain to choose between computational models. The theory was contrasted with internal modelling and incentive predictive performance to show how prediction errors influence computational model selection. The brain can choose an internal validation learning model based on incentive prediction mistakes, as empirical evidence demonstrates that the policy gradient method matches these models. These models were intended to address higher education issues like administration, academic delivery, instructional design, and ethics. The report also suggested that e-learning could help solve industry issues like student concentration on campuses, brain drain, and resource shortages. This research shows how technology can change higher education and the future of learning.

Keywords: education learning; infrastructure administration; academic delivery; instructional design; e-learning model; human resource; education management; education policy.

DOI: 10.1504/IJIE.2025.145654

International Journal of Intelligent Enterprise, 2025 Vol.12 No.2, pp.126 - 147

Received: 08 Sep 2023
Accepted: 01 Oct 2024
Published online: 11 Apr 2025 *

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