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Dynamic tasks are pervasive in organizational decision making. Improving managerial performance in dynamic tasks is an ongoing research endeavor. We report a laboratory experiment in which participants managed a dynamic task by playing the roles of fishing fleet managers. The two experimental groups used a computer simulation-based interactive learning environment (ILE) with an outcome-oriented debriefing and a process-oriented debriefing. To assess the users’ learning and performance, a comprehensive five-dimensional model was used to evaluate subjects’ task performance, decision time, decision strategy, structural knowledge, and heuristics knowledge. The results showed that process-oriented debriefing improved subjects’ task performance, helped users gain task knowledge, develop heuristics, and adapt to systematic-variable consistent strategies. Contrary to our hypothesis, the process-oriented debriefing group did not use less decision time. In contrast to the cost-benefit approach to decision making, a relatively more systematic effort is needed to perform better in dynamic tasks such as fisheries management.

Instrumented gait analysis allows for the identification of walking parameters to predict cognitive decline and the worsening of dementia. The aim of this study was to perform a meta-analysis to better clarify which gait parameters are affected or modified with the progression of the dementia in a larger sample, as well as which gait assessment conditions (single-task or dual-task conditions) would be more sensitive to reflect the influence of dementia. Literature searches were conducted with the keywords “quantitative gait” OR “gait analysis” AND “dementia” AND “single-task” AND “dual-task,” and for “quantitative gait” OR “gait analysis” AND “dementia” AND “fall risk” on PubMed, EMBASE, the Cochrane Library, Scopus, and Web of Science. The results were used to perform a systematic review focussing on instrumental quantitative assessment of the walking of patients with dementia, during both single and dual tasks. The search was performed independently by two authors (C. R. and C. M.) from January 2018 to April 2020 using the PICOS criteria. Nine publications met the inclusion criteria and were included in the systematic review. Our meta-analysis showed that during a single task, most of the spatiotemporal parameters of gait discriminated best between patients with dementia and healthy controls, including speed, cadence, stride length, stride time, stride time variability, and stance time. In dual tasks, only speed, stride length, and stride time variability discriminated between the two groups. In addition, compared with spatial parameters (e.g. stride length), some temporal gait parameters were more correlated to the risk of falls during the comfortable walking in a single task, such as cadence, stride time, stride time variability, and stance time. During a dual task, only the variability of stride time was associated with the risk of falls.

This paper presents a computational model of the dynamics of a human's functional state in relation to task performance and environment. It can be used in intelligent systems that support humans in demanding circumstances. The model takes task demand and situational aspects as input and calculates internal factors related to human functioning, such as the experienced pressure, exhaustion, and motivation, and how they affect performance. Simulation experiments under different parameter settings pointed out that the model is able to produce realistic behavior of humans with different types of personalities. Moreover, by a mathematical analysis the equilibria of the model have been determined, and by automated checking a number of expected properties of the model have been confirmed. In addition to this "internal" validation of the model, an experiment has been designed for the purpose of external validation, addressing the estimation of aspects of the human process that are relevant for its practical application. Output from the experiment, like information about personality characteristics and performance quality, has been used to perform estimation of the parameters of the model. By the parameter estimation, a set of parameter values has been identified by which an adequate representation of a person's functional state when performing a task is achieved.