$Enhancing Automated Scoring of Math Self-Explanation Quality Using LLM-Generated Datasets: A Semi-Supervised Approach$

Enhancing Automated Scoring of Math Self-Explanation Quality Using LLM-Generated Datasets: A Semi-Supervised Approach

In the realm of mathematics education, self-explanation stands as a crucial learning mechanism, allowing learners to articulate their comprehension of intricate mathematical concepts and strategies. As digital learning platforms grow in prominence, there are mounting opportunities to collect and uti...

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Bibliographic Details
Main Authors:	Ryosuke Nakamoto, Brendan Flanagan, Taisei Yamauchi, Yiling Dai, Kyosuke Takami, Hiroaki Ogata
Format:	Article
Language:	English
Published:	MDPI AG 2023-10-01
Series:	Computers
Subjects:	self-explanation automated scoring semi-supervised learning language learning model (LLM) data augmentation
Online Access:	https://www.mdpi.com/2073-431X/12/11/217

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