Complex problem solving—single ability or complex phenomenon?

Schoppek, Wolfgang; Fischer, Andreas

doi:10.3389/fpsyg.2015.01669

Cited by 21 publications

(32 citation statements)

References 19 publications

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“…For the latter, the quality of one’s hypotheses, which is based on domain knowledge, is a necessary prerequisite for successfully exploring the system. In summary, the features of MCS measurements outlined here, along with further criticisms of this approach (e.g., Funke, 2014; Scherer, 2015; Schoppek and Fischer, 2015; Dörner and Funke, 2017; Funke et al, 2017; Kretzschmar, 2017), substantially narrow the validity of the MCS approach as an indicator of CPS.…”

Section: Part Ii: Review and Critique Of The Minimally Complex Systemmentioning

confidence: 88%

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: Part Ii: Review and Critique Of The Minimally Complex Systemmentioning

confidence: 88%

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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“…Numerous articles on the subject have been published in recent years, documenting the increasing research activity relating to this field. In the following collection of papers we list only those published in 2010 and later: theoretical papers (Blech and Funke, 2010; Funke, 2010; Knauff and Wolf, 2010; Leutner et al, 2012; Selten et al, 2012; Wüstenberg et al, 2012; Greiff et al, 2013b; Fischer and Neubert, 2015; Schoppek and Fischer, 2015), papers about measurement issues (Danner et al, 2011a; Greiff et al, 2012, 2015a; Alison et al, 2013; Gobert et al, 2015; Greiff and Fischer, 2013; Herde et al, 2016; Stadler et al, 2016), papers about applications (Fischer and Neubert, 2015; Ederer et al, 2016; Tremblay et al, 2017), papers about differential effects (Barth and Funke, 2010; Danner et al, 2011b; Beckmann and Goode, 2014; Greiff and Neubert, 2014; Scherer et al, 2015; Meißner et al, 2016; Wüstenberg et al, 2016), one paper about developmental effects (Frischkorn et al, 2014), one paper with a neuroscience background (Osman, 2012) 1 , papers about cultural differences (Güss and Dörner, 2011; Sonnleitner et al, 2014; Güss et al, 2015), papers about validity issues (Goode and Beckmann, 2010; Greiff et al, 2013c; Schweizer et al, 2013; Mainert et al, 2015; Funke et al, 2017; Greiff et al, 2017, 2015b; Kretzschmar et al, 2016; Kretzschmar, 2017), review papers and meta-analyses (Osman, 2010; Stadler et al, 2015), and finally books (Qudrat-Ullah, 2015; Csapó and Funke, 2017b) and book chapters (Funke, 2012; Hotaling et al, 2015; Funke and Greiff, 2017; Greiff and Funke, 2017; Csapó and Funke, 2017a; Fischer et al, 2017; Molnàr et al, 2017; Tobinski and Fritz, 2017; Viehrig et al, 2017). In addition, a new “Journal of Dynamic Decision Making” (JDDM) has been launched (Fischer et al, 2015, 2016) to give the field an open-access outlet for research and discussion.…”

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confidence: 99%

Complex Problem Solving: What It Is and What It Is Not

2017

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Computer-simulated scenarios have been part of psychological research on problem solving for more than 40 years. The shift in emphasis from simple toy problems to complex, more real-life oriented problems has been accompanied by discussions about the best ways to assess the process of solving complex problems. Psychometric issues such as reliable assessments and addressing correlations with other instruments have been in the foreground of these discussions and have left the content validity of complex problem solving in the background. In this paper, we return the focus to content issues and address the important features that define complex problems.

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“…knowledge application). The participants are usually confronted with seven to nine tasks, each lasting about a maximum of 5 min (Greiff et al 2013a;Schoppek and Fischer 2015). In contrast, our own approach builds on analytic problem solving, in which relevant information is presented or can be derived by deductive reasoning (Leutner et al 2005), which also resembles information problem solving as, for instance, referred to by BrandGruwel et al (2009).…”

Section: Domain-specific Problem-solving Competencementioning

confidence: 99%

“…We do not follow Leutner's et al (2005) opinion that only dynamic problems are complex problems. Likewise, Schoppek and Fischer (2015) argue that problems within the MicroDYN approach lack many of the above characteristics of complex problems. Furthermore, analytic problems can apparently possess all further features of complex problems, too.…”

Section: Domain-specific Problem-solving Competencementioning

confidence: 99%

“…Thus, by including knowledge in the definition of problem-solving the construct becomes domain-specific. Although domain-specific knowledge plays an important role, problem solving is also enhanced by non-cognitive factors such as selfconfidence, perseverance, motivation, interest, frustration tolerance and the like (Frensch and Funke 1995;Schoppek and Fischer 2015;Sugrue 1995). Similarly, Kanfer and Ackerman (2005) consider knowledge, skills and abilities, motivation, personality, and self-concept as components of work competence.…”

Section: Domain-specific Problem-solving Competencementioning

confidence: 99%

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Reliability and validity of a computer-based assessment of cognitive and non-cognitive facets of problem-solving competence in the business domain

Rausch

Seifried

Wuttke

et al. 2016

Empirical Res Voc Ed Train

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Background: To measure higher-order outcomes of vocational education and training (VET) we developed a computer-based assessment of domain-specific problemsolving competence. In modeling problem-solving competence, we distinguish four components of competence: (1) knowledge application, (2) metacognition, (3) self-concept, and (4) interest as well as thirteen facets of competence, each of which is assigned to one of the four components. Methods:With regard to ecological and content validity, rather than apply highly structured items (e.g. multiple choice items), we developed three authentic problem scenarios and provided an open-ended problem space in terms of an authentic office simulation. The assessment was aimed at apprentice industrial clerks at the end of a 3-year apprenticeship program and focused on the domain of controlling (i.e., support of managerial decisions, cost planning, cost control, cost accounting, etc.). The computer-based office simulation provided typical tools (e.g., email client, spreadsheet software, file system, notebook, calculator, etc.). In order to assess the non-cognitive components in our competence model, we implemented an integrated measurement of self-concept and interest that we refer to as 'Embedded Experience Sampling' (EES). Test-takers are requested to spontaneously answer short prompts (EES items) during the test that are embedded in typical social interactions in the workplace. The empirical section is based on a study with 780 VET students from three commercial training occupations in Germany (industrial clerks and apprentices from two similar VET programs). The focus of the contribution is on testing a theoretically derived competence model based on item response theory, the implemented scoring methods and reliability of the instrument. Fine-grained response patterns from automated codings and human ratings were condensed into one partial credit item for each scenario and each of the facets in the cognitive component 'knowledge application' . Results:The multidimensional Rasch analysis revealed satisfactory EAP/PV reliabilities, which are between .78 and .84 for the 'knowledge application' facets and between .77 and .85 for the non-cognitive facets. Furthermore, the achievement differences between the industrial clerks and their comparison groups are as assumed. Conclusions:In our study, we introduced an innovative method to measure noncognitive facets of problem-solving competence in the course of complex problem Rausch et al. Empirical Res Voc Ed Train (2016) Rausch et al. Empirical Res Voc Ed Train (2016) 8:9 scenarios. Furthermore, by using authentic problem scenarios and providing an openended and authentic problem space, our assessment of domain-specific problem-solving comeptence focuses on ecological validity but also ensures reliability. RESEARCH

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Complex problem solving—single ability or complex phenomenon?

Cited by 21 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

Complex Problem Solving: What It Is and What It Is Not

Reliability and validity of a computer-based assessment of cognitive and non-cognitive facets of problem-solving competence in the business domain

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