Dual Space Search During Scientific Reasoning

Klahr, David; Dunbar, Kevin

doi:10.1207/s15516709cog1201_1

Cited by 848 publications

(522 citation statements)

References 58 publications

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“…The findings from this study can be taken as further support for Burns & Vollmeyer's (2002) Dual-Space theory (Klahr & Dunbar, 1988;Klahr, Fay, & Dunbar, 1993;Simon & Lea, 1974) in which a skill is acquired by searching through different spaces of a task. Depending on the goal of the task, problem solvers develop hypotheses of how the control system works, which they evaluate by testing and updating (Burns & Vollmeyer, 2002;Geddes & Stevenson, 1997;Klahr et al, 1993;Sanderson, 1989;Sanderson & Vicente, 1986;Vollmeyer & Rheinberg, 2000).…”

Section: So What Knowledge Is Acquired In Cdcts?supporting

confidence: 73%

“…Bandura and Locke's (2002) Social Cognitive theory, and Locke and Latham's (2002) theory of goal setting, have proposed that goals are integral to the way skilled behaviors are regulated. This is also compatible with the Dual-Space theory of goal specificity effects in CDCTs (Burns & Vollmeyer, 2002;Klahr & Dunbar, 1988;Vollmeyer et al, 1996). Goals inform how behavior is assessed (Bandura, 1997;Bandura & Locke, 2002;Locke & Latham, 2002).…”

Section: The Relationship Between Monitoring and Control And Its Effesupporting

confidence: 62%

“…Burns and Vollmeyer's (2002) recent account of the phenomena develops on Dual-Space theory (Klahr & Dunbar, 1988;Simon & Lea, 1974). Its main tenet is that a skill is acquired by applying the principles underlying scientific discovery: i.e., designing the appropriate procedure (experimental design) to evaluate a theory (hypothesis formation).…”

Section: Control Behavior: Research Histories Of Cdctsmentioning

confidence: 99%

“…This necessarily involves the exploration, generation, and evaluation of hypotheses (Klahr & Dunbar, 1988;Klahr et al, 1993), which can be biased by extraneous but highly influential information (Jacobs et al, 1984;Wisniewski & Medin, 1991). Burns & Vollmeyer (2002) showed that, even under conditions in which learning is SG-based, problem solvers allocate some learning trials to hypothesis testing.…”

Section: Successful Transfer Of Complex Control Behaviorsmentioning

confidence: 99%

See 3 more Smart Citations

Positive transfer and negative transfer/antilearning of problem-solving skills.

Osman¹

2008

Journal of Experimental Psychology: General

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The present study examined how self-regulatory processes influenced problem solving behavior under conditions in which people were either re-exposed to their prior learning, or experienced someone else's. In a series of four experiments, participants solved two complex control tasks that were identical in structure but varied in presentation format. Participants either learnt to solve the second task, based on their original learning phase from the first task, or learnt to solve the second task based on another participant's learning phase. Experiment 1 showed that, under conditions in which participants' learning phase was experienced twice, performance deteriorated in the second task compared to the first. In contrast, when the learning phases in the first and second task differed, performance improved in the second task.Experiment 2 introduced instructional manipulations that induced the same response patterns as Experiment 1, and Experiment 3 showed that participants differentially weighted the learning phase in the second task. In Experiment 4, judgments of selfefficacy were shown to track control performance. The implications of these findings for induction, self-regulation, and insight are discussed. examples share a precise goal that involves accurately and reliably controlling a complex dynamic control task (CDCT-i.e., the aircraft). Control behavior in this, and other types of CDCTs (e.g., air-traffic control, naval mine sweeping, car driving) depends on the development of expertise (e.g., Brehmer, 1992;Funke, 2001; Gonzalez, Lerch, & Lebiere, 2003;Kerstholt, 1996;Randel & Pugh, 1996;Sweller, 1988;.Expertise involves both monitoring-through self-evaluation of goal-directed actions (e.g., Bandura & Locke, 2003; Ericsson & Lehman, 1996;Karoly, 1993;Lerch & Harter, 2001;Rossano, 2003;VanLehn, 1996)-and control, or the generation and selection of goal-directed actions (e.g., Lerch & Harter, 2001; Locke & Latham, 2002;Rossano, 2003;Sweller, 1988;VanLehn, 1996;Vollmeyer, Burns, & Holyoak, 1996). Both behaviors are also interrelated (e.g., Bandura & Locke, 2003; Ericsson & Lehman, 1996;Karoly, 1993;Lerch & Harter, 2001;Rossano, 2003;VanLehn, 1996). However, studies of skill learning in CDCTs have overlooked this relationship, particularly how it influences the transferability of expertise (e.g., Berry, 1991;Berry & Broadbent, 1988;Burns & Vollmeyer, 2002). Without an Anti-Learning 5 understanding of how individuals monitor their behavior, little can be said about how evaluative processes are employed when transferring learnt skills to achieve unpracticed goals.For instance, the critical difference between the examples above is that, in the first case, training (i.e., control performance) and assessment (i.e., monitoring) are based on self-generated behavior; whereas, in the second, assessment is based on comparing self-and other-generated training behavior. These types of training procedures are often used in educational (Pintrich & De Groot, 1990;Pressley, & Ghatala, 1990;Zimmerman, 1990), clin...

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Section: So What Knowledge Is Acquired In Cdcts?supporting

confidence: 73%

Section: The Relationship Between Monitoring and Control And Its Effesupporting

confidence: 62%

Section: Control Behavior: Research Histories Of Cdctsmentioning

confidence: 99%

Section: Successful Transfer Of Complex Control Behaviorsmentioning

confidence: 99%

See 2 more Smart Citations

Positive transfer and negative transfer/antilearning of problem-solving skills.

Osman¹

2008

Journal of Experimental Psychology: General

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“…Thus, some researchers have suggested that children's naive theories might be generated by domain-specific modules (Leslie, 1994;Scholl & Leslie, 1999) or innate concepts in core domains (Carey & Spelke, 1994;Keil, 1995), whereas other researchers have focused on children's ability to learn causal relations from statistical evidence Gopnik, Sobel, Schulz, & Glymour, 2001;Shultz & Mendelson, 1975;Siegler & Liebert, 1975;Sobel, Tenenbaum, & Gopnik, 2004;Watson & Ramey, 1972). Although some research on the development of scientific reasoning has emphasized the importance of integrating domain-specific knowledge with domain-general strategies (Barrett, Abdi, Murphy, & Gallagher, 1993;Klahr & Dunbar, 1988;Koslowski, 1996;Koslowski, Okagaki, Lorenz, & Umbach, 1989;Pazzani, 1991;Penner & Klahr, 1996;Schauble, 1990), those studies have focused primarily on adolescents and adults. Surprisingly little research has looked at how prior theories and evidence interact in young children's causal learning.…”

mentioning

confidence: 99%

Can being scared cause tummy aches? Naive theories, ambiguous evidence, and preschoolers' causal inferences.

Schulz¹,

Bonawitz²,

Griffiths³

2007

Developmental Psychology

158

119

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Causal learning requires integrating constraints provided by domain-specific theories with domaingeneral statistical learning. In order to investigate the interaction between these factors, the authors presented preschoolers with stories pitting their existing theories against statistical evidence. Each child heard 2 stories in which 2 candidate causes co-occurred with an effect. Evidence was presented in the form: AB 3 E; CA 3 E; AD 3 E; and so forth. In 1 story, all variables came from the same domain; in the other, the recurring candidate cause, A, came from a different domain (A was a psychological cause of a biological effect). After receiving this statistical evidence, children were asked to identify the cause of the effect on a new trial. Consistent with the predictions of a Bayesian model, all children were more likely to identify A as the cause within domains than across domains. Whereas 3.5-year-olds learned only from the within-domain evidence, 4-and 5-year-olds learned from the cross-domain evidence and were able to transfer their new expectations about psychosomatic causality to a novel task.Keywords: domain-general and domain-specific causal learning, Bayesian models, naive theories, ambiguous evidence, psychosomatic causes Supplemental materials: http://dx.doi.org/10.1037/0012-1649. 43.5.1124.supp By the time children are 5 years old, they understand causal relationships in a variety of domains (Flavell, Green, & Flavell, 1995;Gelman & Wellman, 1991;Gopnik & Meltzoff, 1997;Inagaki & Hatano, 1993;Kalish, 1996;Perner, 1991;Shultz, 1982;Spelke, Breinlinger, Macomber, & Jacobson, 1992). Many researchers have suggested that children's causal knowledge can be best characterized as a set of naive theories: abstract, coherent representations of causal structure that support prediction, intervention, explanation, and counterfactual claims (Carey, 1985;Gopnik, 1988;Gopnik & Meltzoff, 1997;Harris, German, & Mills, 1996;Hickling & Wellman, 2001;Keil, 1989;Perner, 1991;Sobel, 2004;Wellman, 1990;Wellman, Hickling, & Schult, 1997). The view that children's causal representations resemble scientific theories (the theory theory) suggests both that patterns of evidence should affect children's causal commitments and that children's causal commitments should affect their interpretation of evidence. Indeed, this dynamic relationship between domain-appropriate causal beliefs and evidence has been taken as a defining feature of theories (e.g., Gopnik & Meltzoff, 1997).However, despite the expectation that theory and evidence should interact, developmental psychologists have been largely divided between accounts of causal reasoning emphasizing either domain-specific causal knowledge or domain-general learning from data. Thus, some researchers have suggested that children's naive theories might be generated by domain-specific modules (Leslie, 1994;Scholl & Leslie, 1999) or innate concepts in core domains (Carey & Spelke, 1994;Keil, 1995), whereas other researchers have focused on children's ability to learn causal rel...

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Identifying patterns and relationships among the responses of seventh-grade students to the science process skill of designing experiments

Germann

Aram

Burke³

1996

J. Res. Sci. Teach.

101

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The development of reasoning skills, higher-level thinking skills, and science process skills are some of the benefits students can realize by participating in inquiry in the science laboratory. We used student responses to the Alternative Assessment of Science Process Skills (AASPS) developed by the Missouri Department of Education and the Department of Educational Assessment to develop the Science Process Skills Inventory (SPSI). The SPSI was then used to analyze student efforts at writing experimental designs. Our goal was to gain insight into factors that may be related to students successfully designing experiments. The instrument guides teachers and researchers in assessing seven main components of experimental designs. Each component consists of elements unique to the specific laboratory exercise. Subsequent to its development, the instrument was used to score 364 student responses to the "design an experiment" portion of an alternative assessment instrument for science process skills. Results indicate that explicit, incremental development of the science process skills of formulating hypotheses and identifying variables, together with model examples, may be a means to facilitate student success in designing science experiments. Implications for the classroom and for research are discussed.

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Dual Space Search During Scientific Reasoning

Cited by 848 publications

References 58 publications

Positive transfer and negative transfer/antilearning of problem-solving skills.

Positive transfer and negative transfer/antilearning of problem-solving skills.

Can being scared cause tummy aches? Naive theories, ambiguous evidence, and preschoolers' causal inferences.

Identifying patterns and relationships among the responses of seventh-grade students to the science process skill of designing experiments

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