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arXiv · 2008.01809

Automated Topical Component Extraction Using Neural Network Attention Scores from Source-based Essay Scoring

Haoran Zhang·Diane Litman
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Abstract

While automated essay scoring (AES) can reliably grade essays at scale, automated writing evaluation (AWE) additionally provides formative feedback to guide essay revision. However, a neural AES typically does not provide useful feature representations for supporting AWE. This paper presents a method for linking AWE and neural AES, by extracting Topical Components (TCs) representing evidence from a source text using the intermediate output of attention layers. We evaluate performance using a feature-based AES requiring TCs. Results show that performance is comparable whether using automatically or manually constructed TCs for 1) representing essays as rubric-based features, 2) grading essays.

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Haoran Zhang, Diane Litman. 2020-08-04. Automated Topical Component Extraction Using Neural Network Attention Scores from Source-based Essay Scoring. https://doi.org/10.18653/v1/2020.acl-main.759

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