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Mathematical language processing: automatic grading and feedback for open response mathematical questions

机译:数学语言处理:针对开放式答案数学问题的自动评分和反馈

摘要

Mechanisms for automatically grading a large number of solutions provided by learners in response to an open response mathematical question. Each solution is mapped to a corresponding feature vector based on the mathematical expressions occurring in the solution. The feature vectors are clustered using a conventional clustering method, or alternatively, using a presently-disclosed Bayesian nonparametric clustering method. A representative solution is selected from each solution cluster. An instructor supplies a grade for each of the representative solutions. Grades for the remaining solutions are automatically generated based on their cluster membership and the instructor supplied grades. The Bayesian method may also automatically identify the location of an error in a given solution. The error location may be supplied to the learner as feedback. The error location may also be used to extract information from correct solutions. The extracted information may be supplied to a learner as a solution hint.
机译:针对开放式数学问题,自动为学习者提供的大量解决方案评分的机制。根据解决方案中出现的数学表达式,将每个解决方案映射到相应的特征向量。使用传统的聚类方法或替代地使用当前公开的贝叶斯非参数聚类方法对特征向量进行聚类。从每个解决方案集群中选择一个代表性解决方案。讲师为每个代表性的解决方案提供分数。其余解决方案的成绩将根据其群集成员资格和教师提供的成绩自动生成。贝叶斯方法还可以自动识别给定解决方案中的错误位置。错误位置可以作为反馈提供给学习者。错误位置还可以用于从正确的解决方案中提取信息。所提取的信息可以被提供给学习者作为解决方案提示。

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