Working memory capacity, processing speed, and fluid intelligence: an eye movement analysis

2006 ◽  
Author(s):  
Thomas S. Redick ◽  
Richard P. Heitz ◽  
Aida Aguilera Martinez ◽  
Randall W. Engle
Keyword(s):  
Working Memory ◽  
Eye Movement ◽  
Processing Speed ◽  
Fluid Intelligence ◽  
Working Memory Capacity ◽  
Movement Analysis ◽  
Memory Capacity ◽  
Eye Movement Analysis

A.#Working Memory, Processing Speed, and Intelligence: An Eye Movement Analysis

2006 ◽  
Author(s):  
Thomas S. Redick ◽  
Richard P. Heitz ◽  
Aida Aguilera Martinez ◽  
Randall W. Engle
Keyword(s):  
Working Memory ◽  
Eye Movement ◽  
Processing Speed ◽  
Movement Analysis ◽  
Memory Processing ◽  
Eye Movement Analysis

Understanding the Relationship Between Rationality and Intelligence: A Latent-Variable Approach

2021 ◽  
Author(s):  
Alexander P. Burgoyne ◽  
Cody Mashburn ◽  
Jason S. Tsukahara ◽  
Zach Hambrick ◽  
Randall W Engle
Keyword(s):  
Working Memory ◽  
Latent Variable ◽  
Fluid Intelligence ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Attention Control ◽  
Equation Modeling ◽  
General Intelligence ◽  
Variable Approach ◽  
The Relationship

A hallmark of intelligent behavior is rationality—the disposition and ability to think analytically to make decisions that maximize expected utility or follow the laws of probability, and therefore align with normative principles of decision making. However, the question remains as to whether rationality and intelligence are empirically distinct, as does the question of what cognitive mechanisms underlie individual differences in rationality. In a large sample of participants (N = 331), we used latent variable analyses to assess the relationship between rationality and intelligence. The results indicated that there was a common ability underpinning performance on some, but not all, rationality tests. Latent factors representing rationality and general intelligence were strongly correlated (r = .54), but their correlation fell well short of unity. Indeed, after accounting for variance in performance attributable to general intelligence, rationality measures still cohered on a latent factor. Confirmatory factor analysis indicated that rationality correlated significantly with fluid intelligence (r = .56), working memory capacity (r = .44), and attention control (r = .49). Structural equation modeling revealed that attention control fully accounted for the relationship between working memory capacity and rationality, and partially accounted for the relationship between fluid intelligence and rationality. Results are interpreted in light of the executive attention framework, which holds that attention control supports information maintenance and disengagement in service of complex cognition. We conclude by speculating about factors rationality tests may tap that other cognitive ability tests miss, and outline directions for further research.

scholarly journals Is working memory capacity a causal factor in fluid intelligence?

2019 ◽  
Vol 26 (4) ◽  
pp. 1333-1339 ◽  
Author(s):  
Alexander P. Burgoyne ◽  
David Z. Hambrick ◽  
Erik M. Altmann
Keyword(s):  
Working Memory ◽  
Fluid Intelligence ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Causal Factor

scholarly journals Working memory capacity mediates the relationship between removal and fluid intelligence

2018 ◽  
Vol 101 ◽  
pp. 18-36 ◽  
Author(s):  
Krishneil A. Singh ◽  
Gilles E. Gignac ◽  
Christopher R. Brydges ◽  
Ullrich K.H. Ecker
Keyword(s):  
Working Memory ◽  
Fluid Intelligence ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
The Relationship

Effects of working memory capacity in processing wh-extractions: eye-movement evidence from Chinese-English bilinguals

2016 ◽  
Vol 40 (4) ◽  
pp. 420-438 ◽  
Author(s):  
Huixia Zhou ◽  
Sonja Rossi ◽  
Juan Li ◽  
Huanhuan Liu ◽  
Ran Chen ◽  
...  
Keyword(s):  
Working Memory ◽  
Eye Movement ◽  
Working Memory Capacity ◽  
Memory Capacity

scholarly journals Cognitive Modeling in Intelligence Research: Advantages and Recommendations for their Application

2018 ◽  
Author(s):  
Gidon T. Frischkorn ◽  
Anna-Lena Schubert
Keyword(s):  
Working Memory ◽  
Cognitive Processes ◽  
Processing Speed ◽  
Cognitive Modeling ◽  
Cognitive Process ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Cognitive Models ◽  
Model Fit ◽  
General Intelligence

Mathematical models of cognition measure individual differences in cognitive processes, such as processing speed, working memory capacity, and executive functions, that may underlie general intelligence. As such, cognitive models allow identifying associations between specific cognitive processes and tracking the effect of experimental interventions aimed at the enhancement of intelligence on mediating process parameters. Moreover, cognitive models provide an explicit theoretical formalization of theories regarding specific cognitive process that may help overcoming ambiguities in the interpretation of fuzzy verbal theories. In this paper, we give an overview of the advantages of cognitive modeling in intelligence research and present models in the domains of processing speed, working memory, and selective attention that may be of particular interest for intelligence research. Moreover, we provide guidelines for the application of cognitive models in intelligence research, including data collection, the evaluation of model fit, and statistical analyses.

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