LEVERAGING AI AND BLOCKCHAIN FOR DECENTRALIZED CREDENTIAL VERIFICATION: A CASE STUDY IN ZIMBABWE’S EDUCATION SECTOR

Abstract

Academic qualification forgery poses a major concern for higher learning institutions, employers, and regulatory authorities throughout the world. In Zimbabwe, the increase in the level of fake degrees has greatly eroded trust in the education industry. Conventional verification processes are time-consuming, manual, and highly vulnerable to tampering. This paper introduces a hybrid blockchain-based and AI-enabled academic qualification verification platform to fight the problems. A prototype was implemented integrating various artificial intelligence algorithms including Convolutional Neural Networks (CNN), Autoencoder, Random Forest, and One-Class Support Vector Machines (SVM) with Algorand blockchain for secure, transparent, and decentralized record keeping. Zero-Knowledge Proofs (ZKPs) were utilized to ensure privacy. The system was tested based on a mixed-methods and Design Science Research (DSR) approach across many performance measures. Results show fraud detection accuracy, near-instantaneous verification speed, and satisfaction with privacy standards. The proposed system provides a sustainable and scalable framework for enhancing academic integrity in Zimbabwe's higher education system and primes the region for digital transformation of education.