Strategy Transfer on Fluid Reasoning Tasks

Intelligence ◽  
2022 ◽  
Vol 91 ◽  
pp. 101618
Author(s):  
Megan J. Raden ◽  
Andrew F. Jarosz
Keyword(s):  
Fluid Reasoning ◽  
Reasoning Tasks ◽  
Strategy Transfer

Mathematically gifted adolescents use more extensive and more bilateral areas of the fronto-parietal network than controls during executive functioning and fluid reasoning tasks

NeuroImage ◽  
2011 ◽  
Vol 57 (1) ◽  
pp. 281-292 ◽  
Author(s):  
Manuel Desco ◽  
Francisco J. Navas-Sanchez ◽  
Javier Sanchez-González ◽  
Santiago Reig ◽  
Olalla Robles ◽  
...  
Keyword(s):  
Executive Functioning ◽  
Mathematically Gifted ◽  
Fluid Reasoning ◽  
Reasoning Tasks ◽  
Gifted Adolescents

The Prediction of Problem-Solving Assessed Via Microworlds

2016 ◽  
Vol 32 (4) ◽  
pp. 298-306 ◽  
Author(s):  
Samuel Greiff ◽  
Katarina Krkovic ◽  
Jarkko Hautamäki
Keyword(s):  
Working Memory ◽  
Problem Solving ◽  
Complex Problem ◽  
Two Dimensions ◽  
Assessment Instruments ◽  
Complex Problem Solving ◽  
Visual Spatial ◽  
Rule Knowledge ◽  
Rule Application ◽  
Fluid Reasoning

Abstract. In this study, we explored the network of relations between fluid reasoning, working memory, and the two dimensions of complex problem solving, rule knowledge and rule application. In doing so, we replicated the recent study by Bühner, Kröner, and Ziegler (2008) and the structural relations investigated therein [ Bühner, Kröner, & Ziegler, (2008) . Working memory, visual-spatial intelligence and their relationship to problem-solving. Intelligence, 36, 672–680]. However, in the present study, we used different assessment instruments by employing assessments of figural, numerical, and verbal fluid reasoning, an assessment of numerical working memory, and a complex problem solving assessment using the MicroDYN approach. In a sample of N = 2,029 Finnish sixth-grade students of which 328 students took the numerical working memory assessment, the findings diverged substantially from the results reported by Bühner et al. Importantly, in the present study, fluid reasoning was the main source of variation for rule knowledge and rule application, and working memory contributed only a little added value. Albeit generally in line with previously conducted research on the relation between complex problem solving and other cognitive abilities, these findings directly contrast the results of Bühner et al. (2008) who reported that only working memory was a source of variation in complex problem solving, whereas fluid reasoning was not. Explanations for the different patterns of results are sought, and implications for the use of assessment instruments and for research on interindividual differences in complex problem solving are discussed.

Individual differences in fluid reasoning on a complex recent probes task

2009 ◽  
Author(s):  
Eric G. Freedman ◽  
Michael D. McManaman ◽  
Nezar Khatib
Keyword(s):  
Individual Differences ◽  
Fluid Reasoning

Cascade models of the development of speed, memory, and fluid reasoning in children

2011 ◽  
Author(s):  
Duneesha de Alwis ◽  
Sandra Hale ◽  
Joel Myerson
Keyword(s):  
Cascade Models ◽  
Fluid Reasoning

On Eliminating Individual Differences in Children's Strategy Transfer

1975 ◽  
Author(s):  
John G. Borkowski ◽  
Sandra Levers ◽  
Patricia B. Wanschura
Keyword(s):  
Individual Differences ◽  
Strategy Transfer

Evaluation Opportunities in Mechanized Theories

10.29007/7kx8 ◽  
2018 ◽  
Author(s):  
Joe Hurd
Keyword(s):  
Mathematical Theory ◽  
Theorem Prover ◽  
Mechanized Mathematics ◽  
Reasoning Tasks

This invited talk will look at logic solvers through the application lens of constructing and processing a theory library of mechanized mathematics. In fact, constructing and processing theories are two distinct applications, and each will be considered in turn. Construction is carried out by formalizing a mathematical theory using an interactive theorem prover, and logic solvers can remove much of the drudgery by automating common reasoning tasks. At the theory library level, logic solvers can provide assistance with theory engineering tasks such as compressing theories, managing dependencies, and constructing new theories from reusable theory components.

scholarly journals Working Memory, Fluid Reasoning, and Complex Problem Solving: Different Results Explained by the Brunswik Symmetry

2021 ◽  
Vol 9 (1) ◽  
pp. 5
Author(s):  
André Kretzschmar ◽  
Stephan Nebe
Keyword(s):  
Working Memory ◽  
Problem Solving ◽  
Cognitive Abilities ◽  
Latent Variables ◽  
Complex Problem ◽  
Equation Modeling ◽  
Complex Problem Solving ◽  
Symmetry Principle ◽  
Fluid Reasoning ◽  
The Impact

In order to investigate the nature of complex problem solving (CPS) within the nomological network of cognitive abilities, few studies have simultantiously considered working memory and intelligence, and results are inconsistent. The Brunswik symmetry principle was recently discussed as a possible explanation for the inconsistent findings because the operationalizations differed greatly between the studies. Following this assumption, 16 different combinations of operationalizations of working memory and fluid reasoning were examined in the present study (N = 152). Based on structural equation modeling with single-indicator latent variables (i.e., corrected for measurement error), it was found that working memory incrementally explained CPS variance above and beyond fluid reasoning in only 2 of 16 conditions. However, according to the Brunswik symmetry principle, both conditions can be interpreted as an asymmetrical (unfair) comparison, in which working memory was artificially favored over fluid reasoning. We conclude that there is little evidence that working memory plays a unique role in solving complex problems independent of fluid reasoning. Furthermore, the impact of the Brunswik symmetry principle was clearly demonstrated as the explained variance in CPS varied between 4 and 31%, depending on which operationalizations of working memory and fluid reasoning were considered. We argue that future studies investigating the interplay of cognitive abilities will benefit if the Brunswik principle is taken into account.

Individual Differences in Reward‐Based Learning Predict Fluid Reasoning Abilities

2021 ◽  
Vol 45 (2) ◽  
Author(s):  
Andrea Stocco ◽  
Chantel S. Prat ◽  
Lauren K. Graham
Keyword(s):  
Individual Differences ◽  
Reasoning Abilities ◽  
Fluid Reasoning
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