Exploring the nature of peer feedback: An epistemic network analysis approach

Research output: Contribution to journalJournal articleResearchpeer-review

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Exploring the nature of peer feedback : An epistemic network analysis approach. / Viberg, Olga; Baars, Martine; Mello, Rafael Ferreira; Weerheim, Niels; Spikol, Daniel; Bogdan, Cristian; Gasevic, Dragan; Paas, Fred.

In: Journal of Computer Assisted Learning, 2024.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Viberg, O, Baars, M, Mello, RF, Weerheim, N, Spikol, D, Bogdan, C, Gasevic, D & Paas, F 2024, 'Exploring the nature of peer feedback: An epistemic network analysis approach', Journal of Computer Assisted Learning. https://doi.org/10.1111/jcal.13035

APA

Viberg, O., Baars, M., Mello, R. F., Weerheim, N., Spikol, D., Bogdan, C., Gasevic, D., & Paas, F. (2024). Exploring the nature of peer feedback: An epistemic network analysis approach. Journal of Computer Assisted Learning. https://doi.org/10.1111/jcal.13035

Vancouver

Viberg O, Baars M, Mello RF, Weerheim N, Spikol D, Bogdan C et al. Exploring the nature of peer feedback: An epistemic network analysis approach. Journal of Computer Assisted Learning. 2024. https://doi.org/10.1111/jcal.13035

Author

Viberg, Olga ; Baars, Martine ; Mello, Rafael Ferreira ; Weerheim, Niels ; Spikol, Daniel ; Bogdan, Cristian ; Gasevic, Dragan ; Paas, Fred. / Exploring the nature of peer feedback : An epistemic network analysis approach. In: Journal of Computer Assisted Learning. 2024.

Bibtex

@article{946aa66b2b2c47dab889ac6b4cfcd21e,
title = "Exploring the nature of peer feedback: An epistemic network analysis approach",
abstract = "Background Study: Peer feedback has been used as an effective instructional strategy to enhance students' learning in higher education. Objectives: This paper reports on the findings of an explorative study that aimed to increase our understanding of the nature and role of peer feedback in the students' learning process in a computer-supported collaborative learning (CSCL) setting. Exploring what types of feedback are used, and how they relate to each other and are related to academic performance has important implications for students and teachers. Methods: This study was conducted in the higher education setting. It used a dataset consisting of student peer feedback messages (N = 2444) and grades from 231 students who participated in a large engineering course. Using qualitative methods, peer feedback was coded inductively. Epistemic network analysis (ENA) was used to analyse the relation between peer feedback types and performance. Results: Based on the five types of peer feedback (i.e., {\textquoteleft}management{\textquoteright}, {\textquoteleft}cognition{\textquoteright} {\textquoteleft}affect{\textquoteright}, {\textquoteleft}interpersonal factors{\textquoteright} and {\textquoteleft}suggestions for improvements{\textquoteright}), the results of the ENA showed that student feedback categories {\textquoteleft}management{\textquoteright}, {\textquoteleft}cognition{\textquoteright} and {\textquoteleft}affect{\textquoteright} were positively related to student performance at the formative assessment phase. Conclusions: The findings and the ENA visualizations also show that {\textquoteleft}suggestions for improvement{\textquoteright} and {\textquoteleft}interpersonal factors{\textquoteright} were not a significant part of student learning in peer assessment and feedback in the studied context.",
keywords = "computer-supported collaborative learning settings, epistemic network analysis, learning performance, peer feedback",
author = "Olga Viberg and Martine Baars and Mello, {Rafael Ferreira} and Niels Weerheim and Daniel Spikol and Cristian Bogdan and Dragan Gasevic and Fred Paas",
note = "Publisher Copyright: {\textcopyright} 2024 The Author(s). Journal of Computer Assisted Learning published by John Wiley & Sons Ltd.",
year = "2024",
doi = "10.1111/jcal.13035",
language = "English",
journal = "Journal of Computer Assisted Learning",
issn = "0266-4909",
publisher = "Wiley-Blackwell",

}

RIS

TY - JOUR

T1 - Exploring the nature of peer feedback

T2 - An epistemic network analysis approach

AU - Viberg, Olga

AU - Baars, Martine

AU - Mello, Rafael Ferreira

AU - Weerheim, Niels

AU - Spikol, Daniel

AU - Bogdan, Cristian

AU - Gasevic, Dragan

AU - Paas, Fred

N1 - Publisher Copyright: © 2024 The Author(s). Journal of Computer Assisted Learning published by John Wiley & Sons Ltd.

PY - 2024

Y1 - 2024

N2 - Background Study: Peer feedback has been used as an effective instructional strategy to enhance students' learning in higher education. Objectives: This paper reports on the findings of an explorative study that aimed to increase our understanding of the nature and role of peer feedback in the students' learning process in a computer-supported collaborative learning (CSCL) setting. Exploring what types of feedback are used, and how they relate to each other and are related to academic performance has important implications for students and teachers. Methods: This study was conducted in the higher education setting. It used a dataset consisting of student peer feedback messages (N = 2444) and grades from 231 students who participated in a large engineering course. Using qualitative methods, peer feedback was coded inductively. Epistemic network analysis (ENA) was used to analyse the relation between peer feedback types and performance. Results: Based on the five types of peer feedback (i.e., ‘management’, ‘cognition’ ‘affect’, ‘interpersonal factors’ and ‘suggestions for improvements’), the results of the ENA showed that student feedback categories ‘management’, ‘cognition’ and ‘affect’ were positively related to student performance at the formative assessment phase. Conclusions: The findings and the ENA visualizations also show that ‘suggestions for improvement’ and ‘interpersonal factors’ were not a significant part of student learning in peer assessment and feedback in the studied context.

AB - Background Study: Peer feedback has been used as an effective instructional strategy to enhance students' learning in higher education. Objectives: This paper reports on the findings of an explorative study that aimed to increase our understanding of the nature and role of peer feedback in the students' learning process in a computer-supported collaborative learning (CSCL) setting. Exploring what types of feedback are used, and how they relate to each other and are related to academic performance has important implications for students and teachers. Methods: This study was conducted in the higher education setting. It used a dataset consisting of student peer feedback messages (N = 2444) and grades from 231 students who participated in a large engineering course. Using qualitative methods, peer feedback was coded inductively. Epistemic network analysis (ENA) was used to analyse the relation between peer feedback types and performance. Results: Based on the five types of peer feedback (i.e., ‘management’, ‘cognition’ ‘affect’, ‘interpersonal factors’ and ‘suggestions for improvements’), the results of the ENA showed that student feedback categories ‘management’, ‘cognition’ and ‘affect’ were positively related to student performance at the formative assessment phase. Conclusions: The findings and the ENA visualizations also show that ‘suggestions for improvement’ and ‘interpersonal factors’ were not a significant part of student learning in peer assessment and feedback in the studied context.

KW - computer-supported collaborative learning settings

KW - epistemic network analysis

KW - learning performance

KW - peer feedback

UR - http://www.scopus.com/inward/record.url?scp=85197820526&partnerID=8YFLogxK

U2 - 10.1111/jcal.13035

DO - 10.1111/jcal.13035

M3 - Journal article

AN - SCOPUS:85197820526

JO - Journal of Computer Assisted Learning

JF - Journal of Computer Assisted Learning

SN - 0266-4909

ER -

ID: 398549009