Explore cutting-edge research on predicting student success in Massive Open Online Courses (MOOCs) through this 27-minute conference talk. Delve into the innovative application of meta transfer learning techniques for early success prediction in online education. Learn about the research objectives, pipeline, and methodologies employed, including feature extraction, classification, and the use of meta models. Discover how attention layers and fine-tuning contribute to improved predictions. Gain insights into the implications of this research for the future of online learning, and understand the data collection process and potential extensions of this work. Engage with the discussion on how deep learning approaches can enhance educational outcomes in MOOCs.