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Topic-based Revision Tool to Support Academic Writing Skill for Research Students

Authors:
Harriet N Ocharo
Shinobu Hasegawa
Kiyoaki Shirai

Keywords: research support system; academic writing; writing tools; writing skill

Abstract:
When students write academic articles, they undergo a revision process where they receive feedbackin the form of comments from their supervisors to　improve the quality of the articles. The comments can be　broadly classified into three categories: grammatical　comments, format-related comments and topic-related　comments. Comments related to the topic of the research　are the hardest to resolve because students may lack　discipline-specific writing skills needed to resolve such comments. This research developed an interactive tool to enable students search an archive of previous students’ articles showing the revision history and comments. A machine learning approach was used to　automatically classify the comments in the database into the three categories so that only topic-related comments were brought up in the search result. The result of the search was presented to the student in a way that　clearly showed the process previous students used to resolve related comments, thereby showing them a similar way they could use to resolve any difficult topic-related comments. As the student’s writing skill level increases, the amount of detail presented to the student reduces so as to avoid over-reliance on the tool. In this way, students could improve their academic writing skills.

Pages: 102 to 107

Copyright: Copyright (c) IARIA, 2017

Publication date: March 19, 2017

Published in: conference

ISSN: 2308-4138

ISBN: 978-1-61208-538-8

Location: Nice, France

Dates: from March 19, 2017 to March 23, 2017