Student Help Request

Research on automated student help request systems aims to improve the efficiency and effectiveness of providing educational support. Current efforts focus on leveraging large language models (LLMs) like GPT-3.5 and GPT-4, along with techniques such as BERT-based question extraction from images and analysis of abstract syntax trees in code, to automatically classify student queries, provide feedback on programming assignments, and assess the quality of student-generated questions. These advancements offer the potential to significantly reduce the workload on educators while simultaneously personalizing and improving the quality of student support.