Improving the Validity of Automatically Generated Feedback via Reinforcement Learning

Automatically generating feedback via large language models (LLMs) in intelligent tutoring systems and online learning platforms has the potential to improve the learning outcomes of many students. However, both feedback generation and evaluation are challenging: feedback content has to be valid esp...

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Bibliographic Details

Published in:	arXiv.org
Main Authors:	Scarlatos, Alexander, Smith, Digory, Woodhead, Simon, Lan, Andrew
Format:	Paper
Language:	English
Published:	Ithaca Cornell University Library, arXiv.org 12.12.2024
Subjects:	Alignment Annotations Data augmentation Distance learning Error analysis Feedback Large language models Machine learning Tutoring
ISSN:	2331-8422
Online Access:	Get full text
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