Formation and Action of a Learning Community with Collaborative Learning Software

• 成果类型: Article
• 署名作者: Eryilmaz, Evren; Thoms, Brian; Ahmed, Zafor; Lee, Howard
• 署名单位: California State University System; California State University Sacramento; California State University System; California State University Channel Islands; University of Houston System; University of Houston; University of Houston Downtown; Pennsylvania State System of Higher Education (PASSHE); Bloomsburg University of Pennsylvania
• 刊物名称: JOURNAL OF MANAGEMENT INFORMATION SYSTEMS
• ISSN/ISSBN: 0742-1222
• DOI: 10.1080/07421222.2023.2172774
• 发表日期: 2023
• 页码: 38-55
• 关键词: online; network; INFORMATION; analytics; KNOWLEDGE; students; MODEL

摘要

This paper explores the formation of a learning community facilitated by custom collaborative learning software. Drawing on research in group cognition, knowledge building discourse, and learning analytics, we conducted a mixed-methods field study involving an asynchronous online discussion consisting of 259 messages posted by 50 participants. The cluster analysis results provide evidence that the recommender system within the software can support the formation of a learning community with a small peripheral cluster. Regarding knowledge building discourse, we identified the distinct roles of central, intermediate (i.e., middle of three clusters), and peripheral clusters within a learning community. Furthermore, we found that message lexical complexity does not correlate to the stages of knowledge building. Overall, this study contributes to the group cognition theory to deepen our understanding about collaboration to construct new knowledge in online discussions. Moreover, we add a much-needed text mining perspective to the qualitative interaction analysis model.