Towards Better Support for Machine-Assisted Human Grading of Short-Text Answers
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Date
2022-01-04
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This paper aims at tools to help teachers to grade short text answers submitted by students. While many published approaches for short-text answer grading target on a fully automated process suggesting a grading result, we focus on supporting a teacher. The goal is rather to help a human grader and to improve transparency rather than replacing the human by an Oracle. This paper provides a literature overview of the numerous approaches of short text answer grading which were proposed throughout the years. This paper presents two novel approaches (answer completeness and natural variability) and evaluates these based on published exam data and several assessments collected at our university.
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Advances in Teaching and Learning Technologies, automated grading, e-learning, teaching and learning technologies
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10 pages
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Proceedings of the 55th Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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