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.
|Title of host publication||Methods for researching professional learning and development|
|Subtitle of host publication||Challenges, applications and empirical illustrations |
|Editors||Michael Goller, Eva Kyndt, Susanna Paloniemi, Crina Damsa|
|Number of pages||23|
|Publication status||Published - 1 Aug 2022|
|Series||Professional and Practice-based Learning|