Blockchain, Homomorphic Encryption (HE) and Artificial Intelligence (AI) for Confidential Student Performance Analysis and Adaptive Learning

Abstract This study introduces an advanced and integrated framework that combines blockchain technology, Homomorphic Encryption (HE), and Artificial Intelligence (AI) to enable confidential and intelligent student performance analysis and adaptive learning. Blockchain provides a decentralized, immutable ledger that ensures the transparency and tamper-proof storage of student records. Homomorphic Encryption enables the secure computation of encrypted data and ensures privacy preservation throughout data processing. AI uses encrypted data to deliver real-time personalized educational insights and adaptive learning pathways. Together, these technologies address the privacy, security, and personalization challenges in educational data management. This paper discusses system architecture, implementation strategies, real-world use cases, benefits, challenges, and future directions.