An Improved Phrase-based Approach to Annotating and Summarizing Student Course Responses
May 25, 2018 ยท Declared Dead ยท ๐ International Conference on Computational Linguistics
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Authors
Wencan Luo, Fei Liu, Diane Litman
arXiv ID
1805.10396
Category
cs.CL: Computation & Language
Citations
15
Venue
International Conference on Computational Linguistics
Last Checked
4 months ago
Abstract
Teaching large classes remains a great challenge, primarily because it is difficult to attend to all the student needs in a timely manner. Automatic text summarization systems can be leveraged to summarize the student feedback, submitted immediately after each lecture, but it is left to be discovered what makes a good summary for student responses. In this work we explore a new methodology that effectively extracts summary phrases from the student responses. Each phrase is tagged with the number of students who raise the issue. The phrases are evaluated along two dimensions: with respect to text content, they should be informative and well-formed, measured by the ROUGE metric; additionally, they shall attend to the most pressing student needs, measured by a newly proposed metric. This work is enabled by a phrase-based annotation and highlighting scheme, which is new to the summarization task. The phrase-based framework allows us to summarize the student responses into a set of bullet points and present to the instructor promptly.
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