Abstract
This chapter presents an interactivity -based approach to human problem-solving in the wild. It introduces the notion of ‘interactivity’, here defined as sense-saturated coordination that contributes to human action . On this view, interactivity is an ontological substrate that can be studied as interaction , as cognition , or as ecological niche production (section “Human Interactivity”). While the chapter theoretically argues in favour of a unified, anti-disciplinary approach to interactivity, it turns its attention to the cognitive ecology of human problem-solving. It does so by presenting a method of Cognitive Event Analysis (section “From Interactivity to Cognitive Events”), that leads to a detailed analysis of how a problem in the wild is being solved (section “The Invoice Case”). The analysis addresses the cognitive dynamics of how two persons in a work setting reach an insight into the nature of a problem, including the spatial organisation of the workplace, the interbodily dynamics between the two participants (especially in relation to gaze and the manual handling of papers), and verbal patterns that prompts them to simulate how the problem appears to a third party. The chapter concludes that human problem-solving is far less linear and planned than assumed in much work on the topic. Rather than problem-solving, it appears as solution-probing in real-time. The cognitive trajectory to a viable solution is thus self-organised, unplanned, and on the edge of chaos .
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Notes
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In line with this view, Donald (2001) argues that humans alone developed a cultural capacity to voluntarily retrieve experience. Culture turns our social and physical environment into a cognitive resource, and not just an independent, external material resource. Therefore, studying cognition as a Distributed Cognitive System requires that we take into account longer time-scales than that of here-and-now situated interactions, for instance those involved in autobiographical memory (Donald 1991, 2001, 2012; cf. Cowley 2012), collective memory (Wertsch 2002) and cultural artefacts.
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The light shake of the invoice is invisible in the still shots in Fig. 5.4, but a close examination of the 25 frames from the video recording reveals the movement.
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The margin of error is 40 ms, or the time between two frames. The spectrogram (made in PRAAT software) shows with accuracy when the syllable starts, and this can be imposed on the frame-by-frame video annotation (made in ELAN software). This procedure shows that the hand movement at latest starts in the frame that immediately follows the frame in which the syllable starts.
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Acknowledgements
I am grateful to the editors for the valuable comments and suggestions. Likewise, Sarah Bro Trasmundi (University of Southern Denmark) contributed with helpful suggestions, and Rasmus Nielsen (University of Southern Denmark) assisted in the interpretation of the spectrogram in Fig. 5.7. Finally, I am indebted to Anne-Kathrine Brorsen who allowed me to use her data for the in-depth analysis, and not least indebted to Black and White for sharing their problem-solving with us.
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Steffensen, S.V. (2017). Human Interactivity: Problem-Finding, Problem-Solving, and Verbal Patterns in the Wild. In: Cowley, S., Vallée-Tourangeau, F. (eds) Cognition Beyond the Brain. Springer, Cham. https://doi.org/10.1007/978-3-319-49115-8_5
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