Course Specific Context

Course-specific context in AI research explores how the design and application of AI models, particularly large language models (LLMs), are influenced by the unique characteristics of educational settings. Current research focuses on using LLMs for tasks like evaluating student work, providing virtual teaching assistance, and generating training data, while also investigating challenges such as prompt hacking and ensuring fairness and generalizability across diverse learning environments. These studies aim to improve the effectiveness and accessibility of AI-powered educational tools, ultimately impacting teaching methodologies and student learning outcomes. The findings inform the development of more robust and contextually aware AI systems for educational applications.