Safeguarding Student Data
Md Mehedi Hasan Emon, Most. Sharmin Ara Chowdhury · Advances in computational intelligence and robotics book series · 2025
This chapter explores the critical privacy and security challenges posed by AI-powered education tools. It examines how AI enhances student support and personalized learning while highlighting risks associated with chatbots, data collection, and processing. Ethical concerns, including consent and fairness, are discussed alongside the complexities of global regulations such as GDPR and FERPA. The chapter also addresses cybersecurity threats targeting educational AI systems and presents strategies to mitigate these risks. Emerging privacy-preserving techniques like federated learning and differential privacy are evaluated for their potential to safeguard student data. Drawing on case studies, it identifies best practices for ethical AI implementation and offers actionable recommendations for educators and policymakers. Finally, this chapter underscores the need for a balanced approach that protects student privacy without stifling innovation in AI-driven education.