计算机科学
协作学习
构造(python库)
异步通信
认知
知识管理
学习分析
领域(数学)
透视图(图形)
推荐系统
数据科学
万维网
心理学
人工智能
计算机网络
数学
神经科学
纯数学
程序设计语言
作者
Evren Eryilmaz,Brian Thoms,Zafor Ahmed,Howard Lee
标识
DOI:10.1080/07421222.2023.2172774
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.
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