Abstract
Since college students rely more on online education, artificial intelligence (AI) is changing virtual learning paths. The study shows how schools are personalising instruction and improving student engagement, comprehension, and retention with AI algorithms and data analytics. The essay covers key features of AI-powered personalised learning , from content recommendations to customisable evaluations and real-time feedback. The essay critiques these innovations' ethical and transparency difficulties, despite their potential benefits. It emphasises ethical AI-driven teaching by highlighting prejudice and data privacy issues. AI can improve education, but it has limitations, recommending a balance between innovation and ethical scrutiny. The paper proposes federated learning to address these difficulties. Federated learning decentralises data and encourages diverse data sets in localised environments to reduce biases and privacy breaches. Federated learning protects privacy, making it a viable AI-driven education solution, as the study shows. AI-facilitated customised learning may improve academic performance and digital skills, according to the study. It stresses ethics and openness in AI-driven education. Federated learning may help ethically integrate AI into education by balancing privacy and personalisation.
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