Complex problem solving (CPS) and related topics such as dynamic decision-making (DDM) and complex dynamic control (CDC) represent multifaceted psychological phenomena. In a broad sense, CPS encompasses learning, decision-making, and acting in complex and dynamic situations. Moreover, solutions to problems that people face in such situations are often generated in teams or groups. In turn, this adds another layer of complexity to the situation itself because of the emerging issues that arise from the social dynamics of group interactions. This framing of CPS means that it is not a single construct that can be measured by using a particular type of CPS task (e.g. minimal complex system tests), which is a view taken by the psychometric community. The proposed approach taken here is that because CPS is multifaceted, multiple approaches need to be taken to fully capture and understand what it is and how the different cognitive processes associated with it complement each other.
Thus, this Research Topic is aimed at showcasing the latest work in the fields of CPS, as well as DDM and CDC that takes a holist approach to investigating and theorizing about these abilities. Particularly welcome are experimental studies involving established or new tools to examine CPS, DDM and CDC, such as simulated microworlds that were specifically designed to study certain processes. Empirical work using this kind of tool is valuable in answering questions about what strategies and what general knowledge can be transferred from one type of complex and dynamic situation to another, what learning conditions result in transferable knowledge and skills, and how these features can be trained.
We also welcome theoretical papers. A number of open questions can be addressed here: How are aptitude and motivation implicated in CPS successes or failures? Does the distinction between approach and avoidance motivation help understand basic patterns of behavior found in CPS? What role does self-regulation play in CPS? Is causal knowledge really at the heart of success in CPS, or are there other types of knowledge that share a critical role in CPS? How can existing theories be brought to bear on a theory of CPS?
As most CPL occurs outside our scientific laboratories, we also appreciate papers reporting work around examining CPS in occupational contexts, such as industrial process control or aviation. Relevant questions around submissions focused on these theme include: What are the specific difficulties of CPS in teams or how can CPS be supported using technology? Our intention is not to dismiss the psychometric approach, but to explore how it can be meaningfully integrated with these alternative approaches. All papers should discuss implications of their findings for problem solving in real life contexts.
Complex problem solving (CPS) and related topics such as dynamic decision-making (DDM) and complex dynamic control (CDC) represent multifaceted psychological phenomena. In a broad sense, CPS encompasses learning, decision-making, and acting in complex and dynamic situations. Moreover, solutions to problems that people face in such situations are often generated in teams or groups. In turn, this adds another layer of complexity to the situation itself because of the emerging issues that arise from the social dynamics of group interactions. This framing of CPS means that it is not a single construct that can be measured by using a particular type of CPS task (e.g. minimal complex system tests), which is a view taken by the psychometric community. The proposed approach taken here is that because CPS is multifaceted, multiple approaches need to be taken to fully capture and understand what it is and how the different cognitive processes associated with it complement each other.
Thus, this Research Topic is aimed at showcasing the latest work in the fields of CPS, as well as DDM and CDC that takes a holist approach to investigating and theorizing about these abilities. Particularly welcome are experimental studies involving established or new tools to examine CPS, DDM and CDC, such as simulated microworlds that were specifically designed to study certain processes. Empirical work using this kind of tool is valuable in answering questions about what strategies and what general knowledge can be transferred from one type of complex and dynamic situation to another, what learning conditions result in transferable knowledge and skills, and how these features can be trained.
We also welcome theoretical papers. A number of open questions can be addressed here: How are aptitude and motivation implicated in CPS successes or failures? Does the distinction between approach and avoidance motivation help understand basic patterns of behavior found in CPS? What role does self-regulation play in CPS? Is causal knowledge really at the heart of success in CPS, or are there other types of knowledge that share a critical role in CPS? How can existing theories be brought to bear on a theory of CPS?
As most CPL occurs outside our scientific laboratories, we also appreciate papers reporting work around examining CPS in occupational contexts, such as industrial process control or aviation. Relevant questions around submissions focused on these theme include: What are the specific difficulties of CPS in teams or how can CPS be supported using technology? Our intention is not to dismiss the psychometric approach, but to explore how it can be meaningfully integrated with these alternative approaches. All papers should discuss implications of their findings for problem solving in real life contexts.
