The Prediction of Problem-Solving Assessed Via 					Microworlds

Greiff, Samuel; Krkovic, Katarina; Hautamäki, Jarkko

doi:10.1027/1015-5759/a000263

Cited by 15 publications

(30 citation statements)

References 19 publications

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“…These results complement the mixed pattern of previous findings, in which working memory explained CPS variance above and beyond intelligence (Wittmann and Süß, 1999), was the only predictor of CPS variance when simultaneously considering figural reasoning (Bühner et al, 2008), but did not explain CPS variance above and beyond reasoning (Greiff et al, 2016). In our view, there is little unique criterion variance to explain because the predictors are highly correlated.…”

Section: Discussionsupporting

confidence: 89%

“…Working memory is considered the most important cognitive resource for complex information processing, which includes reasoning (e.g., Kyllonen and Christal, 1990; Süß et al, 2002; Conway et al, 2003), language comprehension (e.g., King and Just, 1991), and math performance (e.g., Swanson and Kim, 2007). Consequently, previous research has found a significant relation between WMC and CPS (e.g., Wittmann and Süß, 1999; Bühner et al, 2008; Schweizer et al, 2013; Greiff et al, 2016). However, whether the more basic construct (i.e., WMC) is a stronger symmetrical predictor of CPS than reasoning from the perspective of the Brunswik symmetry principle (Wittmann, 1988) is not clear (for an overview, see Zech et al, 2017).…”

Section: Part I: Empirical Investigation Of the Cognitive Prerequisitmentioning

confidence: 94%

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Impact of Cognitive Abilities and Prior Knowledge on Complex Problem Solving Performance – Empirical Results and a Plea for Ecologically Valid Microworlds

Süß

Kretzschmar

2018

Front. Psychol.

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The original aim of complex problem solving (CPS) research was to bring the cognitive demands of complex real-life problems into the lab in order to investigate problem solving behavior and performance under controlled conditions. Up until now, the validity of psychometric intelligence constructs has been scrutinized with regard to its importance for CPS performance. At the same time, different CPS measurement approaches competing for the title of the best way to assess CPS have been developed. In the first part of the paper, we investigate the predictability of CPS performance on the basis of the Berlin Intelligence Structure Model and Cattell’s investment theory as well as an elaborated knowledge taxonomy. In the first study, 137 students managed a simulated shirt factory (Tailorshop; i.e., a complex real life-oriented system) twice, while in the second study, 152 students completed a forestry scenario (FSYS; i.e., a complex artificial world system). The results indicate that reasoning – specifically numerical reasoning (Studies 1 and 2) and figural reasoning (Study 2) – are the only relevant predictors among the intelligence constructs. We discuss the results with reference to the Brunswik symmetry principle. Path models suggest that reasoning and prior knowledge influence problem solving performance in the Tailorshop scenario mainly indirectly. In addition, different types of system-specific knowledge independently contribute to predicting CPS performance. The results of Study 2 indicate that working memory capacity, assessed as an additional predictor, has no incremental validity beyond reasoning. We conclude that (1) cognitive abilities and prior knowledge are substantial predictors of CPS performance, and (2) in contrast to former and recent interpretations, there is insufficient evidence to consider CPS a unique ability construct. In the second part of the paper, we discuss our results in light of recent CPS research, which predominantly utilizes the minimally complex systems (MCS) measurement approach. We suggest ecologically valid microworlds as an indispensable tool for future CPS research and applications.

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Section: Discussionsupporting

confidence: 89%

Section: Part I: Empirical Investigation Of the Cognitive Prerequisitmentioning

confidence: 94%

Impact of Cognitive Abilities and Prior Knowledge on Complex Problem Solving Performance – Empirical Results and a Plea for Ecologically Valid Microworlds

Süß

Kretzschmar

2018

Front. Psychol.

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“…For answering this question, we utilized the data from the study of Bühner, Krumm, Ziegler, and Plücken [5] and compared the results to those of Wittmann and Süss [1], Bühner, Kröner, and Ziegler [6], and Greiff, Krkovic, and Hautamäki [7]. Note, however, that the present analyses of the Bühner et al [5] data are novel, as the previous publication based on these data did not include the results of the problem solving scenario, due to a different research focus.…”

Section: Introductionmentioning

confidence: 99%

The Impact of Symmetry: Explaining Contradictory Results Concerning Working Memory, Reasoning, and Complex Problem Solving

et al. 2017

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Abstract:Findings of studies on the unique effects of reasoning and working memory regarding complex problem solving are inconsistent. To find out if these inconsistencies are due to a lack of symmetry between the studies, we reconsidered the findings of three published studies on this issue, which resulted in conflicting conclusions regarding the inter-relations between reasoning, working memory, and complex problem solving. This was achieved by analysing so far unpublished problem solving data from the study of Bühner, Krumm, Ziegler, and Plücken (2006) (N= 124). One of the three published studies indicated unique effects of working memory and reasoning on complex problem solving using aggregated scores, a second study found no unique contribution of working memory using only figural scores, and a third study reported a unique influence only for reasoning using only numerical scores. Our data featured an evaluation of differences across content facets and levels of aggregation of the working memory scores. Path models showed that the results of the first study could not be replicated using content aggregated scores; the results of the second study could be replicated if only figural scores were used, and the results of the third study could be obtained by using only numerical scores. For verbal content, none of the published results could be replicated. This leads to the assumption that not only symmetry is an issue when correlating non-symmetrical data, but that content also has to be taken into account when comparing different studies on the same topic.

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“…As a response to this need, complex problem solving (CPS) has received considerable attention over the last couple of years as one potential extension of current theories. Both its role within the nexus of other cognitive abilities as well as its assessment are currently under intensive scientific investigation [8,9,10,11]. The core of this special issue is to shed further light on the role of CPS within the broad field of research on the human intellect.…”

mentioning

confidence: 99%

Complex Problem Solving and Its Position in the Wider Realm of the Human Intellect

Greiff

Scherer

2018

J. Intell.

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We cannot solve our problems with the same thinking we used when we created them.-Albert Einstein Over the last century, a wealth of studies has accumulated that provides evidence for the paramount relevance of general mental ability or g as an overarching indicator of the human intellect for virtually any indicator of life success [1]. For instance, Deary, Strand, Smith, and Fernandes (2007) report a correlation of 0.81 between a latent g-factor score and a latent factor of educational achievement in a prospective study of 70,000 secondary students over five years [2]. In fact, there are many other studies that support this pattern of results. Also, comprehensive theories such as the Cattell-Horn-Carroll-theory (CHC-theory) often contain g as the most general (and most relevant) factor at the apex, but they usually include additional factors that are sometimes located on the same level as g and sometimes located on conceptually lower or more specific levels [3]. For instance, CHC-theory assumes a broad g-factor on the top (stratum III), which is further differentiated into lower-level and more specific cognitive abilities (stratum II and stratum I) [3].The type, number, and nature of these additional factors have been subject of intensive and controversial scientific debate, and CHC-theory is still experiencing extensions, particularly with regard to stratum II and stratum III abilities [4]. Some of the efforts that focus on extensions of existing theories of the human intellect are accompanied by general criticisms on the abstract nature of standard tests of g, such as Raven's Advanced Progressive Matrices [5]. These tests are, according to their critics, largely out of touch with reality and have limited real-world relevance. Moreover, there is a need for measures that capture certain aspects of the human intellect more comprehensively in addition to and beyond g [6,7].As a response to this need, complex problem solving (CPS) has received considerable attention over the last couple of years as one potential extension of current theories. Both its role within the nexus of other cognitive abilities as well as its assessment are currently under intensive scientific investigation [8][9][10][11]. The core of this special issue is to shed further light on the role of CPS within the broad field of research on the human intellect.When first research reports on CPS emerged in the 1970s, it was the complex and highly face-valid nature of the problem scenarios used in this line of research, in which participants had to explore complex systems and work through environments that tried to mimic real-life scenarios, that was considered important and a viable alternative to or augmentation of existing measures of intelligence [7]. However, the hope put into CPS diminished rather quickly because the conceptual delineation between CPS and g was difficult to establish and to substantiate empirically.

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The Prediction of Problem-Solving Assessed Via Microworlds

Cited by 15 publications

References 19 publications

Impact of Cognitive Abilities and Prior Knowledge on Complex Problem Solving Performance – Empirical Results and a Plea for Ecologically Valid Microworlds

Impact of Cognitive Abilities and Prior Knowledge on Complex Problem Solving Performance – Empirical Results and a Plea for Ecologically Valid Microworlds

The Impact of Symmetry: Explaining Contradictory Results Concerning Working Memory, Reasoning, and Complex Problem Solving

Complex Problem Solving and Its Position in the Wider Realm of the Human Intellect

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