A Scalable Learning Analytics Platform for Automated Writing Feedback

Jacqueline L. Feild, N. Lewkow, N. Zimmerman, M. Riedesel, Alfred Essa
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引用次数: 9

Abstract

In this paper, we describe a scalable learning analytics platform which runs generalized analytics models on educational data in parallel. As a proof of concept, we use this platform as a base for an end-to-end automated writing feedback system. The system allows students to view feedback on their writing in near real-time, edit their writing based on the feedback provided, and observe the progression of their performance over time. Providing students with detailed feedback is an important part of improving writing skills and an essential component towards solving Bloom's "two sigma" problem in education. We evaluate the effectiveness of the feedback for students with an ongoing pilot study with 800 students who are using the learning analytics platform in a college English course.
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用于自动写作反馈的可扩展学习分析平台
在本文中,我们描述了一个可扩展的学习分析平台,该平台对教育数据并行运行广义分析模型。作为概念验证,我们使用这个平台作为端到端自动写作反馈系统的基础。该系统允许学生几乎实时地查看对他们写作的反馈,根据提供的反馈编辑他们的写作,并观察他们的表现随时间的进展。为学生提供详细的反馈是提高写作技能的重要组成部分,也是解决布鲁姆的“两个西格玛”教育问题的重要组成部分。我们通过一项正在进行的试点研究来评估反馈对学生的有效性,该研究有800名学生在大学英语课程中使用学习分析平台。
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