Artificial Intelligence and Human-AI Driven Accreditation System for Higher Education Quality Assurance
subject: Artificial Intelligence; Blockchain-Based Quality Assurance; Graph Attention Network (GAT); Higher Education Accreditation; Human-AI Collaboration; mRMR Feature Selection; Robust PCA (RPCA)
description: This study introduces the Artificial Intelligence and Human-AI powered Accreditation System, which is meant to transform quality assurance in higher education. The suggested framework will combine human knowledge and smart automation to guarantee transparency, scalability and reliability of accreditation assessments. The data processing algorithm is based on Robust Principal Component Analysis of noise elimination and data normalization and then on the minimum-Redundancy Maximum-Relevancefeature selection algorithm. The fundamental classifier is a Graph Attention Network developed on PyTorch and PyTorch Geometric that is able to capture all the relations between institutional characteristics to make explainable judgments. A blockchain ledger is incorporated to record accreditation results to achieve security and traceability. The experimental simulations show excellent performance with high accuracy, evaluation times, and fairness than the traditional models. The system offers a strong, smart and open accreditation system that facilitates continuous improvement and accountability in the higher education system. 2025 IEEE.
creator: Prakash, P.; Gornale, Shivanand S.; Siddalingappa, Rashmi; Priya
source: Proceedings ICECONF 2025 - 2025 2nd International Conference on Artificial Intelligence and Knowledge Discovery in Concurrent Engineering;
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 01-01-2025
rights: Restricted Access; Hardcopy may be available in the library
relation: ISBN: 979-833156070-6;
language: English
type: Conference paper
coverage: Prakash P., School of Mathematics and Computing Sciences, Rani Channamma University, Department of Computer Science, Karnataka, Belagavi, India; Gornale S.S., School of Mathematics and Computing Sciences, Rani Channamma University, Department of Computer Science, Karnataka, Belagavi, India; Siddalingappa R., Christ University, Dept. of Computer Science, Karnataka, Bengaluru, India; Priya, School of Engineering, Dayananda Sagar University, Dept. of Electronics and Communication Engineering, Karnataka, Bangalore, India