TY - GEN
T1 - Examining the Effects of Automatic Comment Classification on Comment Types in Peer Review for Graduate Students' Academic Writing
AU - Liao, Calvin C.Y.
AU - Li, Yuhuan
AU - Cheng, Hercy N.H.
N1 - Funding Information:
ACKNOWLEDGMENT This study was financially supported by National Key R&D Program of China (2017YFB1401300, 2017YFB1401301), and Self-determined Research Funds of Central China Normal University from the Colleges Basic Research and Operation of Ministry of Education of China (CCNU19QN034).
Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - Although previous studies have confirmed the effect of peer review on academic writing, graduate students are usually unable to provide appropriate comments in peer review. As a result, their comments cannot effectively help authors revise academic papers. For this reason, in order to improve the quality of students' comments, this study aims to provide peer reviewers with feedback of the automatic classification of their comments in an existing peer review system, so that reviewers can improve their comments for writers. In order to examine its effect, this study designs an experiment in an academic writing course for first-year graduate students in two semesters. In the experimental group, peer reviewers are provided with the feedback, while students in the control group did not receive any feedback. The results showed that the graduate students in the experimental group consciously improved their comments after receiving the feedback, especially on the cognitive dimensions (e.g., increasing guidance) and the metacognitive dimensions (e.g., increasing evaluating comments). The findings may provide a direction for students to write high-quality comments and improve writing proficiency.
AB - Although previous studies have confirmed the effect of peer review on academic writing, graduate students are usually unable to provide appropriate comments in peer review. As a result, their comments cannot effectively help authors revise academic papers. For this reason, in order to improve the quality of students' comments, this study aims to provide peer reviewers with feedback of the automatic classification of their comments in an existing peer review system, so that reviewers can improve their comments for writers. In order to examine its effect, this study designs an experiment in an academic writing course for first-year graduate students in two semesters. In the experimental group, peer reviewers are provided with the feedback, while students in the control group did not receive any feedback. The results showed that the graduate students in the experimental group consciously improved their comments after receiving the feedback, especially on the cognitive dimensions (e.g., increasing guidance) and the metacognitive dimensions (e.g., increasing evaluating comments). The findings may provide a direction for students to write high-quality comments and improve writing proficiency.
KW - academic writing
KW - content analysis
KW - peer feedback
KW - peer review
UR - http://www.scopus.com/inward/record.url?scp=85080902003&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85080902003&partnerID=8YFLogxK
U2 - 10.1109/IIAI-AAI.2019.00050
DO - 10.1109/IIAI-AAI.2019.00050
M3 - Conference contribution
AN - SCOPUS:85080902003
T3 - Proceedings - 2019 8th International Congress on Advanced Applied Informatics, IIAI-AAI 2019
SP - 215
EP - 220
BT - Proceedings - 2019 8th International Congress on Advanced Applied Informatics, IIAI-AAI 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2019
Y2 - 7 July 2019 through 11 July 2019
ER -