Large Language Models Meet User Interfaces: The Case of Provisioning Feedback
This work addresses usability and ethical issues for educators and students in adopting GenAI tools, though it is incremental in proposing a framework rather than a novel method.
The paper tackles the challenge of integrating large language models (LLMs) into education by moving from conversational user interfaces (CUIs) to user-friendly applications, demonstrating effectiveness with a tool called Feedback Copilot that provides personalized feedback on student assignments.
Incorporating Generative AI (GenAI) and Large Language Models (LLMs) in education can enhance teaching efficiency and enrich student learning. Current LLM usage involves conversational user interfaces (CUIs) for tasks like generating materials or providing feedback. However, this presents challenges including the need for educator expertise in AI and CUIs, ethical concerns with high-stakes decisions, and privacy risks. CUIs also struggle with complex tasks. To address these, we propose transitioning from CUIs to user-friendly applications leveraging LLMs via API calls. We present a framework for ethically incorporating GenAI into educational tools and demonstrate its application in our tool, Feedback Copilot, which provides personalized feedback on student assignments. Our evaluation shows the effectiveness of this approach, with implications for GenAI researchers, educators, and technologists. This work charts a course for the future of GenAI in education.