人类多任务处理
心理学
认知灵活性
灵活性(工程)
认知心理学
认知
理论(学习稳定性)
控制(管理)
注意力控制
认知科学
神经科学
人工智能
计算机科学
统计
数学
机器学习
作者
Russell J. Boag,Luke Strickland,Andrew Heathcote,Shayne Loft
摘要
Managing the trade-off between stability (robustness to interference) and flexibility (readiness to adapt to change) places considerable demands on human attention, cognitive control, and meta-control processes. However, little is known about the cognitive mechanisms driving stability-flexibility adaptation in multitasking contexts, and such mechanisms have implications for effective task completion in everyday life and in complex work settings, particularly when individuals enter performance "red zones" where task demands exceed capacity to manage them. We present a computational model that explains how individuals, in a cognitively demanding prospective memory (PM) paradigm, cognitively adapt to the relative prevalence of competing task responses to achieve more stable or more flexible performance under conditions in and out of the "red zone" (high vs. low time pressure). The model explained observed ongoing- and PM-task performance in terms of the quality and quantity of attentional capacity directed to each task and context-sensitive differences in proactive and reactive cognitive control. The results are consistent with a view of stability and flexibility as potentially independent dimensions of control, the management of which is subject to human processing/capacity constraints. The model furthers understanding of human cognitive flexibility, with potential implications for humans working in dynamic, information-rich settings requiring behavioral flexibility. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
科研通智能强力驱动
Strongly Powered by AbleSci AI