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Predicting Low vs. High Disparity between Peer and Expert Ratings in Peer Reviews of Physics Lab Reports

机译:在物理实验室报告的同行评审中,预测对等级和专家评级之间的低与高的差异

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Our interest in this work is to automatically predict whether peer ratings have high or low agreement in terms of disparity with instructor ratings, using solely features extracted from quantitative peer ratings and text-based peer comments. Experimental results suggest that our model can indeed outperform a majority baseline in predicting low versus high rating disparity. Furthermore, the reliability of both peer ratings and comments (in terms of peer disagreement) shows little correlation to disparity.
机译:我们对这项工作的兴趣是自动预测对等评级是否与教师评级的差异方面具有高或低的协议,仅使用从定量同行评级和基于文本的对等评论中提取的特征。实验结果表明,我们的模型确实可以表现出大多数基线预测低额定值差距。此外,对等额定值和评论的可靠性(在对等分歧方面)显示与差异的相关性。

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