Improving Automated Assessment and Feedback for Student Open-responses in Mathematics
Improving Automated Assessment and Feedback for Student Open-responses in Mathematics
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作者：
Sami Baral
在线学习平台的进步以多种不同方式彻底改变了教育，改变了学习体验和教学实践。自然语言处理和机器学习方法的发展有助于理解和处理学生的语言，了解他们的学习状态，并为教师构建自动化支持。因此，越来越多的研究致力于开发自动化方法来评估学生在数学和非数学领域的工作。这些自动化方法解决了两类问题：封闭式（正确答案有限）和开放式（通常是主观的，有多个正确答案），其中开放式问题主要由教师用来了解学生对特定概念的理解。对于教师来说，手动评估这些开放式问题并提供反馈通常是艰巨且耗时的。因此，已经有几项工作来了解学生对这些开放式问题的反应，以实现评估自动化并向学生提供建设性反馈。在这项研究中，我们寻求改进这种现有的学生开放式数学作业评估和反馈建议的方法。为此，我们对现有的自动评分方法“SBERT-Canberra”进行了误差分析，探讨了导致该方法误差的各种因素，并提出了通过解决这些误差因素来改进该方法的解决方案。我们进一步打算通过改进教师对学生开放式作业的反馈建议来扩展这种方法。
Advancements in online learning platforms have revolutionized education in multiple different ways, transforming the learning experiences and instructional practices. The development of natural language processing and machine learning methods have helped understand and process student languages, comprehend their learning state, and build automated supports for teachers. With this, there has been a growing body of research in developing automated meth-ods to assess students’ work both in mathematical and non-mathematical domains. These automated methods address questions of two categories; closed-ended (with limited correct answers) and open-ended (are often subjective and have multiple correct answers), where open-ended questions are mostly used by teachers to learn about their student’s understanding of a particular concept. Manually assessing and providing feedback to these open-ended questions is often arduous and time-consuming for teachers. For this reason, there have been several works to understand student responses to these open-ended questions to automate the assessment and provide constructive feedback to students. In this research, we seek to improve such a prior method for assessment and feedback suggestions for student open-ended works in mathematics. For this, we present an error analysis of the prior method ”SBERT-Canberra” for auto-scoring, explore various factors that contribute to the error of the method, and propose solutions to improve upon the method by addressing these error factors. We further intend to expand this approach by improving feedback suggestions for teachers to give to their students’ open-ended work.