Graders as Meta-Reviewers: Simultaneously Scaling and Improving Expert Evaluation for Large Online Classrooms

David A. Joyner, W. Ashby, Liam Irish, Yeeling Lam, Jacob Langson, Isabel Lupiani, Mike Lustig, Paige Pettoruto, Dana Sheahen, Angela Smiley, A. Bruckman, Ashok K. Goel
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引用次数: 16

Abstract

Large classes, both online and residential, typically demand many graders for evaluating students' written work. Some classes attempt to use autograding or peer grading, but these both present challenges to assigning grades at for-credit institutions, such as the difficulty of autograding to evaluate free-response answers and the lack of expert oversight in peer grading. In a large, online class at Georgia Tech in Summer 2015, we experimented with a new approach to grading: framing graders as meta-reviewers, charged with evaluating the original work in the context of peer reviews. To evaluate this approach, we conducted a pair of controlled experiments and a handful of qualitative analyses. We found that having access to peer reviews improves the perceived quality of feedback provided by graders without decreasing the graders' efficiency and with only a small influence on the grades assigned.
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作为元审稿人的评分者:同时扩展和改进大型在线课堂的专家评估
无论是在线授课还是住校授课,大班授课通常都需要很多评分员来评估学生的书面作业。有些课程尝试使用自动评分或同伴评分,但这两种方法都给信用机构的评分带来了挑战,比如自动评分难以评估自由回答的答案,以及在同伴评分中缺乏专家监督。2015年夏天,在乔治亚理工学院(Georgia Tech)的一个大型在线课堂上,我们尝试了一种新的评分方法:将评分者设定为元审稿人,负责在同行评议的背景下评估原创作品。为了评估这种方法,我们进行了一对对照实验和少量定性分析。我们发现,获得同行评审可以提高评分者提供的反馈的感知质量,而不会降低评分者的效率,而且对分配的分数只有很小的影响。
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