Verification of Validity of Peer Feedback Using Text Mining: Focusing on the composition of peer feedback and setting the direction of pre-education (텍스트 마이닝을 활용한 동료피드백 타당성 검증: 동료피드백의 구성과 사전교육의 방향 설정을 중심으로)

Yoonkyeong Shin (신윤경); RYU SU-RIN (유수린)

doi:10.24173/jge.2021.04.15.2

Verification of Validity of Peer Feedback Using Text Mining: Focusing on the composition of peer feedback and setting the direction of pre-education

The Journal of General Education
2021, (15), pp.49~75
DOI : 10.24173/jge.2021.04.15.2
Publisher : Da Vinci Mirae Institute of General Education
Research Area : Social Science > Education > Field of Education > General Education
Received : March 21, 2021
Accepted : April 15, 2021
Published : April 30, 2021

Yoonkyeong Shin ¹, RYU SU-RIN ¹

¹가천대학교

Accredited

ABSTRACT

The purpose of this paper is to verify the validity of peer feedback in university writing and to suggest the content of feedback pre-education based on empirical analysis. The effectiveness of peer feedback in the rewriting process has already been verified in several studies. However, there are concerns that feedback from low-level group does not help improve recipients' writing, but rather may lead to errors. Therefore, in order for learners to perform peer feedback successfully, the reliability of the feedback content must be increased, and for this, the instructor must increase the validity of the feedback content through pre-education. In this paper, we first looked at the criteria for validity of feedback types, and then analyzed peer feedback data produced in writing classes of G University for one semester using text mining. First, we measured the correlation of key words in feedback, compared the vocabulary usage patterns of the upper/lower groups. Next, a tone analysis method was applied to score the types of feedback by related vocabulary lists to verify the validity of the types of feedback. Based on this result, an appropriate composition of feedback types for pre-education was proposed, and the detailed expressions were also listed. While previous studies on peer feedback evaluated the validity based on the instructor's intuition, this paper is differentiated in that it tried to verify the validity through empirical analysis and propose more specific contents derived from our results for feedback pre-education.

KEYWORDS

writing, peer feedback, validity by feedback type, text mining, correlation analysis, co-occurrence matrix, tone analysis, feedback pre-education

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* References for papers published after 2023 are currently being built.

[journal] 강지훈 / 2020 / A Study of Atypical Data Analysis Based on Text Mining - Focused on writing pattern analysis / 문화와융합 / 한국문화융합학회 42(8) : 373~391

[thesis] 곽현영 / 2019 / 동료 피드백을 활용한 고쳐쓰기 활동 양상과 지도 방안 연구: 설득적 글쓰기를 중심으로 / 석사 / 경북대학교 대학원

[journal] 김은정 / 2020 / Effective Writing Evaluation Method UsingText Mining Analysis / 인문과학연구 / 인문과학연구소 (41) : 151~174

[journal] 서영진 / 2012 / A Study of Peer Feedback Opinion Validity by Types in Writing / 국어교육학연구 / 국어교육학회 (44) : 369~395

[journal] 안의정 / 2017 / Analysing Lexical Diversity and Lexical Density in Korean Texts / 언어사실과 관점 / 언어정보연구원 41 : 349~365

[journal] 이삼형 / 2018 / A Study on the Changes in the Core Terminology and Related Network of Text / 우리말연구 / 우리말학회 (53) : 179~221

[journal] 이수상 / 2014 / A Content Analysis of Journal Articles Using the Language Network Analysis Methods / 정보관리학회지 / 한국정보관리학회 31(4) : 49~68

[journal] 이슬기 / 2017 / Exploring the Possibility of Using Text Mining in Writing Assessment / 작문연구 / 한국작문학회 (35) : 99~131

[journal] 이윤빈 / 2014 / A Study on Aspects and Validity of Peer Feedback in College Students’ Writing / 작문연구 / 한국작문학회 (20) : 299~334

[journal] 조용림 / 2020 / A Study on the Writing Data Case via Text Mining / 문화와융합 / 한국문화융합학회 42(5) : 279~307

[thesis] 하지인 / 2017 / 동료 피드백 활용 고쳐쓰기가 쓰기 능력 및 쓰기 태도에 미치는 영향 / 석사 / 대구교육대학교 교육대학원

[journal] Blei, D. M. / 2007 / A correlated topic model of Science / Annals of Applied Statistics 1(1)

[confproc] Gamon, M. / 2004 / Sentiment classification on customer feedback data:noisy data, large feature vectors, and the role of linguistic analysis / Proceedings of the 20th International Conference on Computational Linguistics (COLING-2004)

[confproc] Kamps, J. / 2002 / Words with attitude / Proceedings of the 1st International Conference on Global Word-Net

[confproc] Lai, Y. / 2017 / Analysis of user feedback in the mobile app store using text mining: A case study of Google Fit / 2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST)

[journal] Leki, I. / 1991 / Preferences of ESL students for error correction in college level writing classes / Foreign Language Annals 24(3)

[confproc] Popescu, A.-M / 2005 / Extracting Product Features and Opinions from Reviews / HLT/EMNLP

[journal] Rollinson, P. / 2005 / Using peer feedback in the ESL writing class / ELT Journal / Oxford University Press 59(1)

[journal] Zhang, S. / 1995 / Re-examining the affective advantage of peer feedback in the ESL writing class / Journal of Second Language Writing 4(3)

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The Journal of General Education 2023 KCI Impact Factor : 1.7

Verification of Validity of Peer Feedback Using Text Mining: Focusing on the composition of peer feedback and setting the direction of pre-education

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* References for papers published after 2023 are currently being built.

The Journal of General Education 2023 KCI Impact Factor : 1.7

Verification of Validity of Peer Feedback Using Text Mining: Focusing on the composition of peer feedback and setting the direction of pre-education

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KEYWORDS

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