Real-Time Automated Answer Scoring

Akash Nagaraj, Mukund Sood, G. Srinivasa
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引用次数: 2

Abstract

In recent years, the role of big data analytics has exponentially grown and is now slowly making its way into the education industry. Several attempts are being made in this sphere in order to improve the quality of education being provided to students and while many collaborations have been carried out before, automated scoring of answers has been explored to a rather limited extent. One of the biggest hurdles to choosing constructed-response assessments over multiple-choice assessments is the effort and large cost that comes with their evaluation and this is precisely the issue that this project aims to solve. The aim is to accept raw-input from the student in the form of their answer, preprocess the answer, and automatically score the answer. In addition, we have made this a real-time system that captures "snapshots" of the writer's progress with respect to the answer, allowing us to unearth trends with respect to the way a student thinks, and how the student has arrived at their final answer.
实时自动答题评分
近年来,大数据分析的作用呈指数级增长,现在正慢慢进入教育行业。为了提高向学生提供的教育质量,正在这一领域进行一些尝试,虽然以前已经进行了许多合作,但对答案的自动评分的探索程度相当有限。比起选择多项选择,选择建构式反应评估的最大障碍之一是其评估所带来的工作量和巨大成本,而这正是该项目旨在解决的问题。其目的是接受学生以答案形式提供的原始输入,对答案进行预处理,并自动对答案进行评分。此外,我们还制作了一个实时系统,可以捕捉到作者在回答问题过程中的“快照”,让我们发现学生思考方式的趋势,以及学生如何得出最终答案。
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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