Context-Based Automated Scoring Of Complex Mathematical Responses

Aoife Cahill, James H. Fife,Brian Riordan,Avijit Vajpayee, Dmytro Galochkin

INNOVATIVE USE OF NLP FOR BUILDING EDUCATIONAL APPLICATIONS(2020)

引用 7|浏览33
暂无评分
摘要
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.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要