Exploring the Relationship between Emergent Sociocognitive Roles, Collaborative Problem- Solving Skills and Outcomes: A Group Communication Analysis

Nia Dowell, Yiwen Lin, Andrew Godfrey, Christopher A. Brooks
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引用次数: 33

Abstract

Collaborative problem-solving (CPS) has become an essential component of today’s knowledge-based, innovation- centred economy and society. As such, communication and CPS are now considered critical 21st century skills and incorporated into educational practice, policy, and research. Despite general agreement that these are important skills, there is less agreement on how to capture sociocognitive processes automatically during team interactions to gain a better understanding of their relationship with CPS outcomes. The availability of naturally occurring educational discourse data within online CPS platforms presents a golden opportunity to advance understanding about online learner sociocognitive roles and ecologies. In this paper, we explore the relationship between emergent sociocognitive roles, collaborative problem-solving skills, and outcomes. Group Communication Analysis (GCA) — a computational linguistic framework for analyzing the sequential interactions of online team communication — was applied to a large CPS dataset in the domain of science (participant N = 967; team N = 480). The ETS Collaborative Science Assessment Prototype (ECSAP) was used to measure learners’ CPS skills, and CPS outcomes. Cluster analyses and linear mixed-effects modelling were used to detect learner roles, and assess the relationship between those roles on CPS skills and outcomes. Implications for future research and practice are discussed regarding sociocognitive roles and collaborative problem-solving skills.
探索新兴社会认知角色、合作解决问题能力与结果之间的关系:一项群体沟通分析
协作解决问题(CPS)已成为当今以知识为基础,以创新为中心的经济和社会的重要组成部分。因此,沟通和CPS现在被认为是21世纪的关键技能,并被纳入教育实践、政策和研究。尽管人们普遍认为这些都是重要的技能,但对于如何在团队互动中自动捕捉社会认知过程以更好地理解它们与CPS结果的关系,人们的看法却不太一致。在线CPS平台中自然发生的教育话语数据的可用性为促进对在线学习者社会认知角色和生态的理解提供了一个绝佳的机会。在本文中,我们探讨了新兴社会认知角色、协作解决问题技能和结果之间的关系。群体沟通分析(GCA)——一种用于分析在线团队沟通的顺序交互的计算语言框架——被应用于科学领域的大型CPS数据集(参与者N = 967;团队N = 480)。使用ETS合作科学评估原型(ECSAP)来衡量学习者的CPS技能和CPS结果。使用聚类分析和线性混合效应模型来检测学习者角色,并评估这些角色对CPS技能和结果的关系。讨论了社会认知角色和协作解决问题技能对未来研究和实践的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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