暂时性
计算机科学
动力学(音乐)
现象
集合(抽象数据类型)
芯(光纤)
编码(社会科学)
钥匙(锁)
知识管理
人机交互
数据科学
人工智能
心理学
认识论
社会学
哲学
电信
计算机安全
社会科学
教育学
程序设计语言
作者
Lida Z. David,Maaike Endedijk,Piet Van den Bossche
出处
期刊:Professional and practice-based learning
日期:2022-01-01
卷期号:: 187-209
被引量:4
标识
DOI:10.1007/978-3-031-08518-5_9
摘要
Teams are at the core of every organisation, composed of individuals who continuously collaborate, exchange knowledge and ideas, and constantly learn from one another through formal or informal learning experiences. Team learning is therefore a continuously changing phenomenon that develops and evolves over time as teams interact. In this chapter, we aim to promote the investigation of team learning as a temporal phenomenon, and suggest that its temporality can be captured through team interaction dynamics, defined as continuously changing patterns of micro-behaviours that emerge and evolve as teams operate. We set three key steps for initiating and leading research that captures temporality: (a) identifying the interaction dynamics of interest, (b) figuring out the best way to collect and code these, and finally (c) choosing an analysis technique that helps capture continuously and sequentially unfolding patterns. We offer some 'food for thought' on interaction dynamics that relate to team learning and the added value of investigating them, and present some existing data collection and coding methods. We finally propose a framework for choosing an appropriate analysis technique based on the dynamic output that each analysis generates.
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