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cs.LG2025
Towards Privacy-Preserving Data-Driven Education: The Potential of Federated Learning
Mohammad Khalil, Ronas Shakya, Qinyi Liu
The increasing adoption of data-driven applications in education such as in learning analytics and AI in education has raised significant privacy and data protection concerns. Whil…
cs.LG2025
Creating Artificial Students that Never Existed: Leveraging Large Language Models and CTGANs for Synthetic Data Generation
Mohammad Khalil, Sam Urmian, Ronas Shakya +1
In this study, we explore the growing potential of AI and deep learning technologies, particularly Generative Adversarial Networks (GANs) and Large Language Models (LLMs), for gene…