HAROR: A System for Highlighting and Rephrasing Open-Ended Responses
Jionghao Lin, Kenneth R. Koedinger · 2024
Automated feedback systems are pivotal for scaling personalized learning, especially when dealing with large cohorts of learners.This paper introduces HAROR (Highlighting and Rephrasing Openended Responses), a feedback system that utilizes the advanced capabilities of Generative Pre-trained Transformer (GPT) models, including GPT-4 and GPT-3.5, to provide explanatory feedback on learner responses (trainee tutors as learners in our study) to openended questions.HAROR can identify desirable and undesirable parts of open-ended responses, offer explanatory feedback, and rephrase the undesired responses into desirable forms, aiming to foster learners' understanding and improvement.