Divide and correct: using clusters to grade short answers at scale

Authors:
Michael Brooks;Sumit Basu;Charles Jacobs;Lucy Vanderwende
Affiliations:
University of Washington, Seattle, WA, USA;Microsoft Research, Redmond, WA, USA;Microsoft Research, Redmond, WA, USA;Microsoft Research, Redmond, WA, USA
Venue:
Proceedings of the first ACM conference on Learning @ scale conference
Year:
2014

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Abstract

In comparison to multiple choice or other recognition-oriented forms of assessment, short answer questions have been shown to offer greater value for both students and teachers; for students they can improve retention of knowledge, while for teachers they provide more insight into student understanding. Unfortunately, the same open-ended nature which makes them so valuable also makes them more difficult to grade at scale. To address this, we propose a cluster-based interface that allows teachers to read, grade, and provide feedback on large groups of answers at once. We evaluated this interface against an unclustered baseline in a within-subjects study with 25 teachers, and found that the clustered interface allows teachers to grade substantially faster, to give more feedback to students, and to develop a high-level view of students' understanding and misconceptions.