How Can I Improve? Using GPT to Highlight the Desired and Undesired Parts of Open-ended Responses

arXiv:2405.00291v1 Announce Type: new
Abstract: Automated explanatory feedback systems play a crucial role in facilitating learning for a large cohort of learners by offering feedback that incorporates explanations, significantly enhancing the learning process. However, delivering such explanatory feedback in real-time poses challenges, particularly when high classification accuracy for domain-specific, nuanced responses is essential. Our study leverages the capabilities of large language models, specifically Generative Pre-Trained Transformers (GPT), to explore a sequence labeling approach focused on identifying components of desired and …

abstract arxiv automated challenges cs.ai cs.cl cs.hc feedback gpt highlight however process real-time responses role systems type