Knowledge-building and metacognition matter: Detecting differences between high- and low-performance groups in computer-supported collaborative learning. Issue 1 (2nd January 2023)

• Record Type: Journal Article
• Authors: Zheng, Lanqin; Niu, Jiayu; Zhong, Lu; Gyasi, Juliana Fosua
• Is Part Of: Innovations in education & teaching international. Volume 60:Issue 1(2023)
• Page Start: 48
• Page End: 58
• Publication Date: 2023-01-02
• Subjects: Collaborative learning -- knowledge-building -- metacognition -- emotion -- participation; Programmed instruction -- Periodicals; Educational technology -- Periodicals; Instructional systems -- Periodicals; Periodicals; 371.33
• DOI: 10.1080/14703297.2021.1988678
• Languages: English
• ISSNs: 1470-3297

Abstract

ABSTRACT: Computer-supported collaborative learning (CSCL) has been widely adopted in the field of education. However, most studies focus on collaborative learning outcomes rather than collaborative learning processes. It is still unclear why some groups fail in CSCL. Therefore, this study extracted four process variables, namely, knowledge-building, metacognitive patterns, emotional status, and participation, to investigate the differences between high- and low-performance groups. In total, 81 undergraduate students participated in this study for one month. The results indicated that there were significant differences in knowledge-building and metacognitive patterns between the high- and low-performance groups. The high-performance groups built more knowledge and engaged in more diverse metacognitive transitions than the low-performance groups. However, no differences in emotional status or participation were found between the two groups. The results and implications are discussed in depth.