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Data Collection
Gather a comprehensive dataset of student learning behaviors, including engagement metrics, performance data, and interaction patterns across various educational platforms.
Model Fine-Tuning
Fine-tune GPT-4 on the learning analytics dataset to optimize its ability to analyze behavioral data, identify trends, and generate personalized recommendations.
System Development
Develop an AI-powered learning analytics platform that integrates the fine-tuned model to provide real-time feedback and actionable insights to students and educators.
Expected Outcomes
This research aims to demonstrate that fine-tuning GPT-4 can significantly enhance the accuracy and personalization of AI-driven learning analytics systems. The outcomes will contribute to a deeper understanding of how advanced AI models can be adapted for educational applications, improving learning efficiency and outcomes. Additionally, the study will highlight the societal impact of AI in democratizing access to high-quality educational resources and supporting personalized learning experiences.