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Meta-reasoning refers to processes by which people monitor problem-solving activities and regulate effort investment. Solving is hypothesized to begin with an initial Judgment of Solvability (iJOS)--the solver's first impression as to whether the problem is solvable--which guides solving attempts. Meta-reasoning research has largely neglected non-verbal problems. In this study we used Raven's matrices to examine iJOS in non-verbal problems and its predictive value for effort investment, final Judgment of Solvability (fJOS), and confidence in the final answer. We generated unsolvable matrix versions by switching locations of elements in original Raven's matrices, thereby breaking the rules while keeping the original components. Participants provided quick (4 s) iJOSs for all matrices and then attempted to solve them without a time limit. In two experiments, iJOS predicted solving time, fJOS, and confidence. Moreover, although difficulty of the original matrices was dissociated from solvability, iJOS was misled by original matrix difficulty. Interestingly, when the unsolvable matrices were relatively similar to the originals (Experiment 2), iJOSs were reliable, discriminating between solvable and unsolvable matrices. When the unsolvable matrices involved greater disruption of the rules (Experiment 1), iJOS was not consistently predictive of solvability. This study addresses a gap in meta-reasoning research by highlighting the predictive value of iJOS for the solving processes that follow. The study also provides many future directions for meta-reasoning research in general, and regarding non-verbal problems, in particular.

Initial Judgment of Solvability (iJOS) is a metacognitive judgment that reflects solvers' first impression as to whether a problem is solvable. We hypothesized that iJOS is inferred by combining prior expectations about the entire task with heuristic cues derived from each problem's elements. In two experiments participants first provided quick iJOSs for all problems, then attempted to solve them. We manipulated expectations by changing the proportion of solvable problems conveyed to participants, 33%, 50%, or 66%, while the true proportion was the 50% for all. In Experiment 1 we used the non-verbal Raven's matrices and examined nameability as the element-based heuristic cue. Unsolvable matrices were generated by switching locations of elements in original Raven's matrices. In Experiment 2 we used the verbal Compound Remote Associate (CRA) problems and examined word's frequency in the language as the element-based heuristic cue. Unsolvable CRAs were random word triads from the same word pool. The results were consistent in suggesting that quick iJOS integrates prior expectations and experience-based heuristic cues. Notably, iJOS was predictive for the subsequent solving attempt only for Raven's matrices. [ABSTRACT FROM AUTHOR]

Success in cognitive tasks is associated with effort regulation and motivation. We employed the meta-reasoning approach to investigate metacognitive monitoring accuracy and effort regulation in problem solving across cultures. Adults from China, from Israel, and from Europe and North America (for simplicity: "Western countries") solved nonverbal problems and rated their confidence in their answers. The task involved identifying geometric shapes within silhouettes and, thus, required overcoming interference from holistic processing. The Western group displayed the worst monitoring accuracy, with both the highest overconfidence and poorest resolution (discrimination in confidence between the correct and wrong solutions). The Israeli group resembled the Western group in many respects but exhibited better monitoring accuracy. The Chinese group invested the most time and achieved the best success rates, demonstrating exceptional motivation and determination to succeed. However, their efficiency suffered as they correctly solved the fewest problems per minute of work. Effort regulation analysis based on the Diminishing Criterion Model revealed distinct patterns: the Western participants invested the least amount of time regardless of item difficulty and the Israelis invested more time only when addressing the hardest items. The Chinese group allocated more time throughout but particularly in moderate to difficult items, hinting at their strategic determination to overcome the challenge. Understanding cultural differences in metacognitive processes carries implications for theory (e.g., motivational factors) and practice (e.g., international teams, education). The present findings can serve as a foundation for future research in these and other domains. [ABSTRACT FROM AUTHOR]

The Emergency Department (ED) of a modem hospital is a highly complex system that gives rise to numerous managerial challenges. It spans the full spectrum of operational, clinical, and financial perspectives, over varying horizons: operational-a few hours or days ahead; tactical-weeks or a few months ahead; and strategic, which involves planning on monthly and yearly scales. Simulation offers a natural framework within which to address these challenges, as realistic ED models are typically intractable analytically. We apply a general and flexible ED simulator to address several significant problems that arose in a large Israeli hospital. The article focuses mainly, but not exclusively, on workforce staffing problems over these time horizons. First, we demonstrate that our simulation model can support real-time control, which enables short-term prediction and operational planning (physician and nurse staffing) for several hours or days ahead. To this end, we present a novel simulation-based technique that implements the concept of offered-load and discover that it performs better than a common alternative. Then we evaluate ED staff scheduling that adjusts for midterm changes (tactical horizon, several weeks or months ahead). Finally, we analyze the design and staffing problems that arose from physical relocation of the ED (strategic yearly horizon). Application of the simulation-based approach led to the implementation of our design and staffing recommendations. [ABSTRACT FROM AUTHOR]