Context-based Automated Scoring of Complex Mathematical Responses

A. Cahill, James H. Fife, Brian Riordan, Avijit Vajpayee, Dmytro Galochkin
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引用次数: 7

Abstract

The tasks of automatically scoring either textual or algebraic responses to mathematical questions have both been well-studied, albeit separately. In this paper we propose a method for automatically scoring responses that contain both text and algebraic expressions. Our method not only achieves high agreement with human raters, but also links explicitly to the scoring rubric – essentially providing explainable models and a way to potentially provide feedback to students in the future.
基于上下文的复杂数学反应自动评分
自动为数学问题的文本或代数回答打分的任务都得到了很好的研究,尽管是分开的。在本文中,我们提出了一种自动评分的方法,同时包含文本和代数表达式的回答。我们的方法不仅与人类评分者达成了高度一致,而且还明确地与评分标准相关联——本质上提供了可解释的模型和一种将来可能向学生提供反馈的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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