Author | Hermawati, Setia; Cibulski, Lena; Lawson, Glyn |
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Date | 2021 |
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Type | Conference Paper |
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Abstract | Visualisations provide significant support for effective reasoning and decision-making processes. Its value mainly lies in its ability to turn raw data into actionable insights that lead to a decision. This requires appropriate visual representations that are designed with the decision-maker's way of reasoning in mind. Understanding the cognitive aspects underlying decision-making with visualisations is therefore crucial. Cognitive task analysis methods have been used to elicit expert knowledge in a variety of decision-making scenarios, with the Critical Decision Method (CDM) focusing on the cognitive bases in naturalistic non-routine incidents. In this study, we aim to determine the feasibility of CDM for capturing the expert knowledge, strategies, and cues involved with visualisation-based decision-making processes. Based on an analysis of four semi-structured interviews, we evaluate the method’s potential to inform the role of visualisation for human decision-making. We anticipate that our reflections on methodological insights can serve as a starting point for other human factors and visualisation researchers, who aim at studying strategies for higher-level decision-making and problem-solving tasks. |
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Conference | Chartered Institute of Ergonomics & Human Factors (CIEHF Annual Conference) 2021 |
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Project | Cloudification of Production Engineering for Predictive Digital Manufacturing |
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Url | https://publica.fraunhofer.de/handle/publica/419101 |
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