Word Embedding for Response-To-Text Assessment of Evidence

August 06, 2019 ยท Declared Dead ยท ๐Ÿ› Annual Meeting of the Association for Computational Linguistics

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Authors Haoran Zhang, Diane Litman arXiv ID 1908.01969 Category cs.CL: Computation & Language Cross-listed cs.AI Citations 6 Venue Annual Meeting of the Association for Computational Linguistics Last Checked 4 months ago
Abstract
Manually grading the Response to Text Assessment (RTA) is labor intensive. Therefore, an automatic method is being developed for scoring analytical writing when the RTA is administered in large numbers of classrooms. Our long-term goal is to also use this scoring method to provide formative feedback to students and teachers about students' writing quality. As a first step towards this goal, interpretable features for automatically scoring the evidence rubric of the RTA have been developed. In this paper, we present a simple but promising method for improving evidence scoring by employing the word embedding model. We evaluate our method on corpora of responses written by upper elementary students.
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