Peer Feedback in Online Learning Communities: Its Effectiveness on Internal Motivation from the Perspective of Self-Determination Theory

Chen Hsuan Liao, Hsin Jung Chung, Jiun Yu Wu

研究成果: Conference contribution同行評審

摘要

To interrogate the inequitable amount of feedback provided by the instructor to each student in class, this study targeted at exploring the possibility of facilitating learning via peer feedback. Learning with peers is found to be beneficial to both disciplinary skills and learning motivation. Without time and space limits, educators can easily take advantage of social media develop online learning communities that empower students to conduct peer learning by giving feedback to each other. This research collected peer feedback in a Facebook private group of an introductory statistics course at a national university in northern Taiwan. Participants were 34 graduate students in the course. After analyzing and coding messages in the Facebook group into four levels (i.e., task, process, self-regulation, and self), this study found that students primarily received task-level feedback (40.79%) but infrequently received self-level feedback (8.48%). In addition, this study utilized machine learning techniques to examine the effect of different feedback levels on students' learning motivation. Results showed that self-regulation-level feedback stimulated autonomous regulation, but process-level feedback undermined it. From a student-centered perspective, this study proposed a practical framework promoting learning equity about receiving feedback. The present study implemented learning analytics, linking empirical evidence and motivational theory. It implies that teachers can promote learning equity by engaging students to initiate self-regulation level feedback for each other.

原文English
主出版物標題Proceedings - 2023 IEEE International Conference on Advanced Learning Technologies, ICALT 2023
編輯Maiga Chang, Nian-Shing Chen, Rita Kuo, George Rudolph, Demetrios G Sampson, Ahmed Tlili
發行者Institute of Electrical and Electronics Engineers Inc.
頁面144-148
頁數5
ISBN(電子)9798350300543
DOIs
出版狀態Published - 2023
事件23rd IEEE International Conference on Advanced Learning Technologies, ICALT 2023 - Hybrid, Orem, United States
持續時間: 10 7月 202313 7月 2023

出版系列

名字Proceedings - 2023 IEEE International Conference on Advanced Learning Technologies, ICALT 2023

Conference

Conference23rd IEEE International Conference on Advanced Learning Technologies, ICALT 2023
國家/地區United States
城市Hybrid, Orem
期間10/07/2313/07/23

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