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      Rethinking Decision Making in Complex Work Settings: Beyond Human Cognition to the Social Landscape

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      Proceedings of the 30th International BCS Human Computer Interaction Conference (HCI)

      Fusion

      11 - 15 July 2016

      Decision Making, Articulation Work, Managing Interdependencies, Air Traffic Control, Grounded Theory

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          Abstract

          This paper presents a fusion of ideas across disciplines to study and conceptualize decision making. Typically, decision making is approached as a cognitive process. Nevertheless, there is a growing shift in perception towards decision making as more than a cerebral activity to one being situated, embedded and embodied in the social landscape of work activities. Research addressing these aspects is still in its infancy and more work is required to develop the notions. The research presented in here makes a theoretical contribution to this shift. Taking a Computer Supported Cooperative Work (CSCW) perspective, this paper explores how decision making is articulated in the cooperative arrangement of a complex work setting. In the process, it explicates the situated, embedded and embodied nature of decision making. The paper reflects on conventional notions of decision making and demonstrates its differentiated nature during every day work performance in a real-world complex work setting.

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            Dynamic decision making: human control of complex systems.

            This paper reviews research on dynamic decision making, i.e., decision making under conditions which require a series of decisions, where the decisions are not independent, where the state of the world changes, both autonomously and as a consequence of the decision maker's actions, and where the decisions have to be made in real time. It is difficult to find useful normative theories for these kinds of decisions, and research thus has to focus on descriptive issues. A general approach, based on control theory, is proposed as a means to organize research in the area. An experimental paradigm for the study of dynamic decision making, that of computer simulated microworlds, is discussed, and two approaches using this paradigm are described: the individual differences approach, typical of German work in the tradition of research on complex problem solving, and the experimental approach. In studies following the former approach, the behaviour of groups differing in performance is compared, either with respect to strategies or with respect to performance on psychological tests. The results show that there are wide interindividual differences in performance, but no stable correlations between performance in microworlds and scores on traditional psychological tests have been found. Experimental research studying the effects of system characteristics, such as complexity and feedback delays, on dynamic decision making has shown that decision performance in dynamic tasks is strongly affected by feedback delays and whether or not the decisions have side effects. Although neither approach has led to any well-developed theory of dynamic decision making so far, the results nevertheless indicate that we are now able to produce highly reliable experimental results in the laboratory, results that agree with those found in field studies of dynamic decision making. This shows that an important first step towards a better understanding of these phenomena has been taken.
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              Embodied Choice: How Action Influences Perceptual Decision Making

              Embodied Choice considers action performance as a proper part of the decision making process rather than merely as a means to report the decision. The central statement of embodied choice is the existence of bidirectional influences between action and decisions. This implies that for a decision expressed by an action, the action dynamics and its constraints (e.g. current trajectory and kinematics) influence the decision making process. Here we use a perceptual decision making task to compare three types of model: a serial decision-then-action model, a parallel decision-and-action model, and an embodied choice model where the action feeds back into the decision making. The embodied model incorporates two key mechanisms that together are lacking in the other models: action preparation and commitment. First, action preparation strategies alleviate delays in enacting a choice but also modify decision termination. Second, action dynamics change the prospects and create a commitment effect to the initially preferred choice. Our results show that these two mechanisms make embodied choice models better suited to combine decision and action appropriately to achieve suitably fast and accurate responses, as usually required in ecologically valid situations. Moreover, embodied choice models with these mechanisms give a better account of trajectory tracking experiments during decision making. In conclusion, the embodied choice framework offers a combined theory of decision and action that gives a clear case that embodied phenomena such as the dynamics of actions can have a causal influence on central cognition.
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                Author and article information

                Contributors
                Conference
                July 2016
                July 2016
                : 1-10
                Affiliations
                Middlesex University

                London, UK
                Article
                10.14236/ewic/HCI2016.47
                © Selvaraj et al. Published by BCS Learning and Development Ltd. Proceedings of British HCI 2016 Conference Fusion, Bournemouth, UK

                This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                Proceedings of the 30th International BCS Human Computer Interaction Conference
                HCI
                30
                Bournemouth University, Poole, UK
                11 - 15 July 2016
                Electronic Workshops in Computing (eWiC)
                Fusion
                Product
                Product Information: 1477-9358BCS Learning & Development
                Self URI (journal page): https://ewic.bcs.org/
                Categories
                Electronic Workshops in Computing

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