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.

本研究旨在探索一种新的方法从大量的学生反馈中提取摘要短语，通过基于短语的注释和突出显示方案，将其汇总成一组要点，以及用一种新的度量标准衡量这些短语是否满足学生的最迫切需求。