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Examining the Effects of Different Forms of Teacher Feedback Intervention for Learners' Cognitive and Emotional Interaction in Online Collaborative Discussion: A Visualization Method for Process Mining Based on Text Automatic Analysis

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Title: Examining the Effects of Different Forms of Teacher Feedback Intervention for Learners' Cognitive and Emotional Interaction in Online Collaborative Discussion: A Visualization Method for Process Mining Based on Text Automatic Analysis
Language: English
Authors: Wei Xu (ORCID 0000-0002-9042-213X), Le-Ying Yang, Xiao Liu, Pin-Nv Jin
Source: Education and Information Technologies. 2024 29(6):6525-6551.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 27
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Feedback (Response), Teacher Student Relationship, Communities of Practice, Cooperative Learning, Computer Mediated Communication, Bayesian Statistics, College Students, College Faculty, Comparative Analysis, Group Discussion, Discourse Analysis, Emotional Response, Cognitive Processes
DOI: 10.1007/s10639-023-12097-6
ISSN: 1360-2357
1573-7608
Abstract: Teacher feedback is the key to online collaborative discussion. To investigate the effects of different forms of teacher feedback intervention on learners' cognitive and emotional interactions in online collaborative discussion, this study collected collaborative discussion text data of online collaborative learners. Based on the framework of Community of Inquiry theory, naive Bayes algorithm for automatic coding of collaborative discussion text data was adopted. A bivariate (with or without emotion/guidance) experiment was designed based on teacher feedback. The participants of this study were college students (N = 109, average age = 20) of normal major participating in Teaching System Design. They were randomly divided into four experimental groups. In each experimental group, 4-5 people work in a group for collaborative learning. This study adopts quasi experimental research method, and the experiment period is 10 class hours. Reliability analysis, automatic text coding and ANOVA of cognitive-affective variables were used to conduct process mining for the collaborative discussion of four groups of learners by using heuristic mining algorithms. It found that different forms of teacher feedback have different effects on learners' cognitive emotion. Teachers' emotional feedback promotes learners' emotional interaction and cognitive interaction, whiccoch is easier to promote learners' cognitive interaction. Different forms of teacher feedback promote four types of cognitive emotion interaction process. This suggests that the multi-branch type of voice prompt feedback group has the best effect on learners' cognitive and emotional impact.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1421003
Database: ERIC
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  Data: <searchLink fieldCode="AR" term="%22Wei+Xu%22">Wei Xu</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-9042-213X">0000-0002-9042-213X</externalLink>)<br /><searchLink fieldCode="AR" term="%22Le-Ying+Yang%22">Le-Ying Yang</searchLink><br /><searchLink fieldCode="AR" term="%22Xiao+Liu%22">Xiao Liu</searchLink><br /><searchLink fieldCode="AR" term="%22Pin-Nv+Jin%22">Pin-Nv Jin</searchLink>
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  Data: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
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– Name: Abstract
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  Data: Teacher feedback is the key to online collaborative discussion. To investigate the effects of different forms of teacher feedback intervention on learners' cognitive and emotional interactions in online collaborative discussion, this study collected collaborative discussion text data of online collaborative learners. Based on the framework of Community of Inquiry theory, naive Bayes algorithm for automatic coding of collaborative discussion text data was adopted. A bivariate (with or without emotion/guidance) experiment was designed based on teacher feedback. The participants of this study were college students (N = 109, average age = 20) of normal major participating in Teaching System Design. They were randomly divided into four experimental groups. In each experimental group, 4-5 people work in a group for collaborative learning. This study adopts quasi experimental research method, and the experiment period is 10 class hours. Reliability analysis, automatic text coding and ANOVA of cognitive-affective variables were used to conduct process mining for the collaborative discussion of four groups of learners by using heuristic mining algorithms. It found that different forms of teacher feedback have different effects on learners' cognitive emotion. Teachers' emotional feedback promotes learners' emotional interaction and cognitive interaction, whiccoch is easier to promote learners' cognitive interaction. Different forms of teacher feedback promote four types of cognitive emotion interaction process. This suggests that the multi-branch type of voice prompt feedback group has the best effect on learners' cognitive and emotional impact.
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      – SubjectFull: Teacher Student Relationship
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      – SubjectFull: Communities of Practice
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