scholarly journals Differential involvement of working memory capacity and fluid intelligence in verbal associative learning as a possible function of strategy-use

2020 ◽  
Author(s):  
David Martinez
Keyword(s):  
Working Memory ◽  
Cognitive Processes ◽  
Latent Class ◽  
Fluid Intelligence ◽  
Paired Associate ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Strategy Use ◽  
Human Memory And Learning ◽  
Associate Learning

Paired-associate tasks are popular tasks used in basic and applied research on human memory and learning. A number of studies have shown that individuals differ in the strategies they use to encode information in paired-associate tasks and, importantly, that strategies differ in their effectiveness. What is not so well documented is how different strategies may affect the cognitive processes assessed by paired-associate tasks. In this study, we submit archival data to distributional and latent class analyses to infer strategy-use and classify individuals as elaborators or non-elaborators. We then used regression analyses within subgroups to identify differences in dependence on fluid intelligence and working memory capacity. To the extent that our classification of individuals was accurate, the results suggest that paired-associate learning is more reliant on fluid intelligence when elaborative rehearsal is utilized and more reliant on working memory capacity when using non-elaborative strategies. To offer further evidence of the validity of our approach, we also investigated correlations between strategy-use and fluid intelligence and working memory capacity. In accord with prior research, we found that cognitive abilities were positively correlated with what we infer to be differences in strategy-use. That the cognitive processes assessed by verbal paired-associate tasks may vary as a function of strategy-use should be a concern for all researchers and practitioners who use such tasks.

Strategy use moderates the relation between working memory capacity and fluid intelligence: A combined approach

Intelligence ◽  
2022 ◽  
Vol 91 ◽  
pp. 101627
Author(s):  
Chenyu Li ◽  
Xuezhu Ren ◽  
Karl Schweizer ◽  
Tengfei Wang
Keyword(s):  
Working Memory ◽  
Fluid Intelligence ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Strategy Use ◽  
Combined Approach

Strategy use moderates the relation between working memory capacity and fluid intelligence: A combined approach

2021 ◽  
Author(s):  
Chenyu Li ◽  
Xuezhu Ren ◽  
Karl Schweizer ◽  
TENGFEI WANG
Keyword(s):  
Working Memory ◽  
Latent Profile Analysis ◽  
Fluid Intelligence ◽  
Profile Analysis ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Strategy Use ◽  
Response Elimination ◽  
Complex Span ◽  
Latent Profile

This study investigated whether the strength of the link between working memory capacity (WMC) and fluid intelligence (Gf) differs as people use different strategies to solve Gf problems. A sample of 214 university students completed three complex span tasks and Raven's Advanced Progressive Matrices (APM). Strategic behavior was measured by both a strategy questionnaire and eye tracking. Using latent profile analysis, three strategies described as constructive matching, response elimination, and isolate-and-eliminate were identified. Participants adopting constructive matching and response elimination exhibited substantial differences in the eye-movement measures across the APM items, confirming the validity of the strategy questionnaire in combination of latent profile analysis for determining strategy use. Furthermore, strategy use moderated the relationship between WMC and APM performance. The link between WMC and APM scores was significantly higher for participants who used isolate-and-eliminate (r = .54) and response elimination (r = .63) than that for participants who used constructive matching (r = .27). Our findings suggest that the simple dichotomy of strategy use in the APM is not tenable, and the extent to which WMC relates to performance on the APM varies as a function of strategy use.

Differential Effects of Executive Processes on Working Memory

2016 ◽  
Vol 37 (4) ◽  
pp. 239-249
Author(s):  
Xuezhu Ren ◽  
Tengfei Wang ◽  
Karl Schweizer ◽  
Jing Guo
Keyword(s):  
Working Memory ◽  
Cognitive Processes ◽  
Latent Variable ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Attention Control ◽  
Executive Processes ◽  
Differential Effects ◽  
Prepotent Response ◽  
Two Measures

Abstract. Although attention control accounts for a unique portion of the variance in working memory capacity (WMC), the way in which attention control contributes to WMC has not been thoroughly specified. The current work focused on fractionating attention control into distinctly different executive processes and examined to what extent key processes of attention control including updating, shifting, and prepotent response inhibition were related to WMC and whether these relations were different. A number of 216 university students completed experimental tasks of attention control and two measures of WMC. Latent variable analyses were employed for separating and modeling each process and their effects on WMC. The results showed that both the accuracy of updating and shifting were substantially related to WMC while the link from the accuracy of inhibition to WMC was insignificant; on the other hand, only the speed of shifting had a moderate effect on WMC while neither the speed of updating nor the speed of inhibition showed significant effect on WMC. The results suggest that these key processes of attention control exhibit differential effects on individual differences in WMC. The approach that combined experimental manipulations and statistical modeling constitutes a promising way of investigating cognitive processes.

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

Spontaneous Self-Distancing Mediates the Association Between Working Memory Capacity and Emotion Regulation Success

2020 ◽  
pp. 216770262095363
Author(s):  
T. H. Stanley Seah ◽  
Lindsey M. Matt ◽  
Karin G. Coifman
Keyword(s):  
Working Memory ◽  
Emotion Regulation ◽  
Cognitive Processes ◽  
Mood Induction ◽  
Working Memory Capacity ◽  
Negative Mood ◽  
Theoretical Models ◽  
Memory Capacity ◽  
Future Research ◽  
Treatment Target

Self-distancing is associated with adaptive emotion regulation (ER), thereby making it a common treatment target across psychotherapies. However, less is known about cognitive processes that facilitate self-distancing. Working memory capacity (WMC) has been associated with self-distancing and ER, although research has not directly examined WMC and spontaneous self-distancing activity. Here, we tested the association between WMC and self-distancing (indexed by pronoun use) in relation to ER during a negative-mood induction in college students ( N = 209). Results suggested a mediation model: Higher WMC predicted lower I and greater we pronouns (i.e., greater self-distancing), which in turn predicted lower negative affect. Furthermore, higher WMC predicted greater we pronouns, which predicted higher positive affect. No significant mediation was observed for you. These findings enrich current theoretical models describing WMC and self-distancing in ER and suggest important future research to further elucidate the cognitive processes underlying self-distancing with implications for clinical practice.

scholarly journals Working memory capacity and strategy use

2001 ◽  
Vol 29 (1) ◽  
pp. 10-17 ◽  
Author(s):  
Danielle S. McNamara ◽  
Jennifer L. Scott
Keyword(s):  
Working Memory ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Strategy Use
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