工作记忆
记忆广度
跨度(工程)
任务(项目管理)
集合(抽象数据类型)
计算机科学
认知心理学
度量(数据仓库)
短时记忆
流体智能
人工智能
心理学
机器学习
认知
数据挖掘
土木工程
管理
神经科学
工程类
经济
程序设计语言
作者
Florian Schmiedek,Andrea Hildebrandt,Martin Lövdén,Oliver Wilhelm,Ulman Lindenberger
摘要
How to best measure working memory capacity is an issue of ongoing debate. Besides established complex span tasks, which combine short-term memory demands with generally unrelated secondary tasks, there exists a set of paradigms characterized by continuous and simultaneous updating of several items in working memory, such as the n-back, memory updating, or alpha span tasks. With a latent variable analysis (N = 96) based on content-heterogeneous operationalizations of both task families, the authors found a latent correlation between a complex span factor and an updating factor that was not statistically different from unity (r = .96). Moreover, both factors predicted fluid intelligence (reasoning) equally well. The authors conclude that updating tasks measure working memory equally well as complex span tasks. Processes involved in building, maintaining, and updating arbitrary bindings may constitute the common working memory ability underlying performance on reasoning, complex span, and updating tasks.
科研通智能强力驱动
Strongly Powered by AbleSci AI