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Cognitive modeling for understanding interactions between people and decision support tools in complex and uncertain

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This study explores how Computational Intelligence Tools (CITs) impact human decision-making in complex situations. Findings will inform CIT design and our understanding of technology

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Area of Science:

  • Cognitive Science
  • Human-Computer Interaction
  • Decision Science

Background:

  • Computational Intelligence Tools (CITs) are increasingly vital for decision-making amid complex global challenges like pandemics and climate change.
  • Understanding the interplay between CITs and human cognition is crucial for optimizing decision-making processes.
  • Efficiently utilizing decision-makers' cognitive resources requires insight into their interaction with advanced technological tools.

Purpose of the Study:

  • To investigate the influence of Computational Intelligence Tools (CITs) on decision outcomes in complex and uncertain environments.
  • To explore the relationship between cognitive features, neural activity, physiological responses, and decision-making when using CITs.
  • To provide a comprehensive understanding of how individuals interact with technological tools for problem-solving.

Main Methods:

  • An exploratory mixed-methods study employing Solomon's group experiment design.
  • Collection of cognitive data (integrative complexity, cognitive flexibility, fluid intelligence), neural activity (NA), physiological measures (PM), and eye-tracking (ET) data.
  • Inclusion of 120 undergraduate and graduate students in decision-making tasks over a 2-year period, with strict ethical adherence.

Main Results:

  • The study is expected to yield significant insights into the cognitive, behavioral, and physiological effects of CITs on decision-making.
  • Results will elucidate the marginal impact of various cognitive and physiological processes on decision outcomes when using CITs.
  • Data will reveal the relationship between individual cognitive capabilities and the effectiveness of CITs in complex problem-solving.

Conclusions:

  • The findings will offer valuable information for the design and application of CITs in real-world complex scenarios.
  • This research enhances the understanding of the human-technology interaction, particularly in decision-making contexts.
  • The study contributes to a deeper comprehension of subjective assessments and cognitive processes during technology-aided problem-solving.