The Prediction of Problem-Solving Assessed Via Microworlds

2016 ◽  
Vol 32 (4) ◽  
pp. 298-306 ◽  
Author(s):  
Samuel Greiff ◽  
Katarina Krkovic ◽  
Jarkko Hautamäki

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.

2021 ◽  
Vol 9 (1) ◽  
pp. 5
Author(s):  
André Kretzschmar ◽  
Stephan Nebe

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.


2020 ◽  
Author(s):  
Andre Kretzschmar ◽  
Stephan Nebe

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 modelling 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 two 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.


2017 ◽  
Vol 5 (2) ◽  
pp. 22 ◽  
Author(s):  
Alexandra Zech ◽  
Markus Bühner ◽  
Stephan Kröner ◽  
Moritz Heene ◽  
Sven Hilbert

Intelligence ◽  
2013 ◽  
Vol 41 (5) ◽  
pp. 579-596 ◽  
Author(s):  
Samuel Greiff ◽  
Andreas Fischer ◽  
Sascha Wüstenberg ◽  
Philipp Sonnleitner ◽  
Martin Brunner ◽  
...  

2015 ◽  
Vol 31 (3) ◽  
pp. 181-194 ◽  
Author(s):  
Jonas C. Neubert ◽  
André Kretzschmar ◽  
Sascha Wüstenberg ◽  
Samuel Greiff

Abstract. Recent advancements in the assessment of Complex Problem Solving (CPS) build on the use of homogeneous tasks that enable the reliable estimation of CPS skills. The range of problems featured in established instruments such as MicroDYN is consequently limited to a specific subset of homogeneous complex problems. This restriction is problematic when looking at domain-specific examples of complex problems, which feature characteristics absent from current assessment instruments (e.g., threshold states). We propose to utilize the formal framework of Finite State Automata (FSA) to extend the range of problems included in CPS assessment. An approach based on FSA, called MicroFIN, is presented, translated into specific tasks, and empirically investigated. We conducted an empirical study (N = 576), (1) inspecting the psychometric features of MicroFIN, (2) relating it to MicroDYN, and (3) investigating the relations to a measure of reasoning (i.e., CogAT). MicroFIN (1) exhibited adequate measurement characteristics and multitrait-multimethod models indicated (2) the convergence of latent dimensions measured with MicroDYN. Relations to reasoning (3) were moderate and comparable to the ones previously found for MicroDYN. Empirical results and corresponding explanations are discussed. More importantly, MicroFIN highlights the feasibility of expanding CPS assessment to a larger spectrum of complex problems.


2018 ◽  
Vol 84 (2) ◽  
pp. 502-513 ◽  
Author(s):  
Charly Eielts ◽  
Wim Pouw ◽  
Kim Ouwehand ◽  
Tamara van Gog ◽  
Rolf A. Zwaan ◽  
...  

2016 ◽  
Vol 49 ◽  
pp. 323-331 ◽  
Author(s):  
Anja Meißner ◽  
Samuel Greiff ◽  
Gidon T. Frischkorn ◽  
Ricarda Steinmayr

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