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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Vydané v:	arXiv.org
Hlavní autori:	Scarlatos, Alexander, Smith, Digory, Woodhead, Simon, Lan, Andrew
Médium:	Paper
Jazyk:	English
Vydavateľské údaje:	Ithaca Cornell University Library, arXiv.org 12.12.2024
Predmet:	Alignment Annotations Data augmentation Distance learning Error analysis Feedback Large language models Machine learning Tutoring
ISSN:	2331-8422
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