Students' complex problem-solving abilities: Their structure and relations to reasoning ability and educational success

Sonnleitner, Philipp; Keller, Ulrich; Martin, Romain; Brunner, Martin

doi:10.1016/j.intell.2013.05.002

Cited by 66 publications

(77 citation statements)

References 48 publications

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“…In addition, the best single predictor for delayed scientific problem solving performance was delayed scientific concept dependent reasoning performance and followed by their delay scientific knowledge. Previous studies have reported t reasoning is strongly correlated with problem solving (Chang, 2010;Lee & Jeon, 1998;Sonnleitner et al, 2013), however, our results move one step further to indicate that scientific reasoning is highly correlated with problem solving and also is the best predictor for problem solving. Our result further confirms that scientific concept dependent reasoning is critical for physical science problem solving.…”

Section: Discussionsupporting

confidence: 50%

“…Voss, Greene, Post, & Penner (1983) found that domain-specific knowledge was the best predictor of performance in solving ill-structured problems. Other studies have pointed out that reasoning is related to problem solving (Bransford, 1994;English, 1996;Lee & Jeon, 1998), and others have reported that students' reasoning ability can predict their problem solving performance (Cavallo, 1996;Sonnleitner et al, 2013). However, there is a lack of studies exploring whether students' scientific knowledge, scientific concept dependent reasoning and scientific problem solving can be improved by participating in a semester-long problem solving program.…”

Section: Introductionmentioning

confidence: 99%

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The Impact of Problem-Solving Instruction on Middle School Students’ Physical Science Learning: Interplays of Knowledge, Reasoning, and Problem Solving

Cheng

She

2017

EURASIA J MATH SCI T

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The purpose of this study is to explore the impact of problem solving instruction on 126 middle school students' learning of physical science in terms of their scientific knowledge, scientific concept dependent reasoning and problem solving ability. This study used a quasi-experiment with one factorial design of instructional approaches (problem solving and traditional hands-on learning). Sixty-one students participated in problem solving while sixty-five students participated in traditional hands-on learning. Results indicate that the problem solving group significantly outperformed the traditional hands-on learning group for both immediate and retaining effect, regardless of scientific knowledge, scientific concept dependent reasoning and scientific problem solving abilities. The regression results also indicated that the scientific concept dependent reasoning test is the best predictor for scientific problem solving ability, followed by scientific knowledge itself. Our study demonstrates that students' scientific knowledge, reasoning and problem solving all are successfully improved after receiving six weeks scientific problem solving.

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Section: Discussionsupporting

confidence: 50%

Section: Introductionmentioning

confidence: 99%

The Impact of Problem-Solving Instruction on Middle School Students’ Physical Science Learning: Interplays of Knowledge, Reasoning, and Problem Solving

Cheng

She

2017

EURASIA J MATH SCI T

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“…Beckmann & Goode, 2010;Sonnleitner, Brunner, Keller, & Martin, 2013;Osman, 2014). But research also revealed a significant amount of typical errors that are made.…”

Section: Typical Errors When Dealing With Complex Systemsmentioning

confidence: 99%

“…Studies showed that even full information about the underlying connections does not guarantee perfect achievement of envisaged targets; it depends on what you make out of this knowledge (e.g. Goode & Beckmann, 2010;Sonnleitner, Brunner, Keller, Martin, 2013). Other mental pitfalls that were found in this phase of knowledge generation are mistaking correlations with causation, the illusion of being able to control variables that are beyond the influence of the problem solver, and the preference to look for evidence that supports the preconceived model instead of disproving it, which would be mentally more demanding (Brehmer, 2005;Dörner, 1989).…”

Section: Typical Errors When Dealing With Complex Systemsmentioning

confidence: 99%

Cognitive pitfalls in dealing with sustainability

Sonnleitner¹

2017

Sustainability Science

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Main summary points:• Environmental conditions in which human ancestors evolved, strongly shaped human thinking• Two complementary cognitive systems can be distinguished whose interplay causes systematic errors, especially in situations including uncertainty or complexity• These cognitive pitfalls have tremendous consequences in the context of sustainability• Leveraging cognitive biases and knowledge about them by improving education and training is vital to address ecological problems

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“…These (meta) cognitive skills are essential in order to monitor the problem-solving process, and, subsequently, publish the results (Scherer and Tiemann 2012). These processes and cognitive requirements are essential in CPS and were, at least to some degree, studied in domain-general settings Sonnleitner et al 2013). Taken together, there are at least four problem-solving components that can be distinguished: exploring and understanding, representing and formulating, planning and executing, and monitoring and reflecting (OECD 2013).…”

Section: Problem Solving From a Psychological Perspectivementioning

confidence: 99%

Developing a computer-based assessment of complex problem solving in Chemistry

2014

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Background: Complex problem-solving competence is regarded as a key construct in science education. But due to the necessity of using interactive and intransparent assessment procedures, appropriate measures of the construct are rare. This paper consequently presents the development and validation of a computer-based problem-solving environment, which can be used to assess students' performance on complex problems in Chemistry. The test consists of four scales, namely, understanding and characterizing the problem, representing the problem, solving the problem, and reflecting and communicating the solution. Based on this four-dimensional framework, the computer-based assessment has been evaluated with the data of N = 395 10th grade high school students. Results: Result showed that students' complex problem-solving competence could be modelled by four related but empirically distinct factors with moderate to high intercorrelations. The construct showed substantial relations with fluid intelligence and prior domain knowledge in Chemistry, indicating that construct validity and domain specificity were given. Processes of understanding and characterizing the problem were substantially related to subsequent processes in complex problem solving. Conclusions: Due to the complexity of complex problem-solving processes in Chemistry, multidimensionality of the construct could be assumed. Consequently, science educators should take into account abilities of understanding, representing, solving the problem, and finally reflecting and communicating the solution when developing instructional approaches and valid computer-based assessments.

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Students' complex problem-solving abilities: Their structure and relations to reasoning ability and educational success

Cited by 66 publications

References 48 publications

The Impact of Problem-Solving Instruction on Middle School Students’ Physical Science Learning: Interplays of Knowledge, Reasoning, and Problem Solving

The Impact of Problem-Solving Instruction on Middle School Students’ Physical Science Learning: Interplays of Knowledge, Reasoning, and Problem Solving

Cognitive pitfalls in dealing with sustainability

Developing a computer-based assessment of complex problem solving in Chemistry

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