Bruce D. Burns

The Impact of Goal Specificity on Strategy Use and the Acquisition of Problem Structure

Theories of skill acquisition have made radically different predictions about the role of general problem-solving methods in acquiring rules that promote effective transfer to new problems. Under one view, methods that focus on reaching specific goals, such as means-ends analysis, are assumed to provide the basis for efficient knowledge compilation (Anderson, 1987). whereas under an alternative view such methods are believed to disrupt rule induction (Sweller, 1988). We suggest that the role of general methods in learning varies with both the specificity of the problem solver’s goal and the systematicity of the strategies used for testing hypotheses about rules. In the absence of a specific goal people are more likely to use a rule-induction learning strategy, whereas provision of a specific goal fosters use of difference reduction, which tends to be a non-rule-induction strategy. We performed two experiments to investigate the impact of goal specificity and systematicity of rule-induction strategies in learning and transfer within a complex dynamic system. The results of Experiment 1 indicated that during free exploration of a problem space, greater learning occurred if participants adopted more systematic strategies for rule induction, and that participants come to favor such strategies. Experiment 2 revealed that participants who were provided with a specific goal performed well on the initial problem but were impaired on a transfer test using a similar problem with a different goal. Instruction on a systematic rule-induction strategy facilitated solution for both the initial and transfer problems, but participants’ use of this strategy declined if they had a specific goal. Our results support Sweller’s (1988) proposal that general problemsolving methods applied to a specific goal foster acquisition of knowledge about an isolated solution path but da not provide an effective way of learning the overall structure of a problem space. We interpret these results in terms of dualspace theories of search through problem space.

FAM: Ein Fragebogen zur Erfassung aktuller Motivation in Lern- und Leistungssituationen

Zusammenfassung.Vorgestellt wird ein Fragebogen (FAM), der mit 18 Items vier Komponenten der aktuellen Motivation in (experimentellen) Lern- und Leistungssituationen erfasst, namlich Misserfolgsbefurchtung, Erfolgswahrscheinlichkeit, Interesse und Herausforderung. Die deutsche sowie eine amerikanische Version weisen zufriedenstellende Konsistenzen auf (6 Stichproben, N = 944). Aus verschiedenen Experimenten liegen bereits Validitatshinweise dazu vor, dass die vorweg erfassten Motivationskomponenten mit dem nachfolgenden Lernverhalten und der Lernleistung im Zusammenhang stehen. Im jetzigen Artikel werden zwei Experimente berichtet, die zeigen, dass die Leistungsprognosen von Herausforderung und Interesse auch von der Lernaufgabe sowie von der Zahl der Lerndurchgange abhangen. Beide FAM-Faktoren erlauben Leistungsvorhersagen beim selbstgesteuerten Verstandnislernen (vs. fragengefuhrten Faktenlernen) und bei Probanden, die viele (vs. wenige) Durchgange benotigen, um ein akzeptables Leistungsniveau zu erreic...

Randomness and inductions from streaks: “Gambler’s fallacy” versus ”hot hand“

Sometimes people believe that a run of similar independent events will be broken (belief in thegambler’s fallacy) but, other times, that such a run will continue (belief in the hot hand). Both of these opposite inductions have been explained as being due to belief in a law of small numbers. We argue that one factor that distinguishes these phenomena is people’s beliefs about the randomness of the underlying process generating the events. We gave participants information about a streak of events but varied the scenarios in such a way that the mechanism generating the events should vary in how random the participants would judge it to be. A manipulation check confirmed our assumptions about the scenarios. We found that with less random scenarios, the participants were more likely to continue a streak.

Goal specificity effects on hypothesis testing in problem solving

Previous research has found that having a nonspecific goal (NSG) leads to better problem solving and transfer than having a specific goal (SG). To distinguish between the various explanations of this effect requires direct evidence showing how a NSG affects a participants behaviour. Therefore we collected verbal protocols from participants learning to control a linear system consisting of 3 outputs by manipulating 3 inputs. This system was simpler than the one we had used previously, so in Exp. 1 we generalized our earlier goal specificity findings to this system. In Exp. 2 protocol analysis confirmed our prediction (based on dual-space theories of problem solving) that NSG participants focused on hypothesis testing whereas SG participants focused on the goal. However, this difference only emerged over time. We also replicated the goal specificity effect on performance and showed that giving participants a hypothesis to test improved performance.

The Effects of Speed on Skilled Chess Performance

Two types of mechanisms may underlie chess skill: fast mechanisms, such as recognition, and slow mechanisms, such as search through the space of possible moves and responses. Speed distinguishes these mechanisms, so I examined archival data on blitz chess (5 min for the whole game), in which the opportunities for search are greatly reduced. If variation in fast processes accounts for substantial variation in chess skill, performance in blitz chess should correlate highly with a players overall skill. In addition, restricting search processes should tend to equalize skill difference between players, but this effect should decrease as overall skill level increases. Analyses of three samples of blitz chess tournaments supported both hypotheses. Search is undoubtedly important, but up to 81% of variance in chess skill (measured by rating) was accounted for by how players performed with less than 5% of the normal time available.

The collider principle in causal reasoning: Why the Monty Hall dilemma is so hard

The authors tested the thesis that people find the Monty Hall dilemma (MHD) hard because they fail to understand the implications of its causal structure, a collider structure in which 2 independent causal factors influence a single outcome. In 4 experiments, participants performed better in versions of the MHD involving competition, which emphasizes causality. This manipulation resulted in more correct responses to questions about the process in the MHD and a counterfactual that changed its causal structure. Correct responses to these questions were associated with solving the MHD regardless of condition. In addition, training on the collider principle transferred to a standard version of the MHD. The MHD taps a deeper question: When is knowing about one thing informative about another?

Goal specificity and learning with a hypermedia program.

Problem solving research has found that a nonspecific goal (NSG) leads to better learning than a specific goal (SG). This effect can be understood in terms of dual-space search theories of problem solving. To apply the theory, we studied goal specificity effects with a hypermedia program in which participants had to learn about the outbreak of World War 1, either with the goal to find twenty dates (i.e., SG) or with the goal to explain the reasons for the war (i.e., NSG). As expected, compared to the SG-group, the NSG-group correctly answered more factual questions about the text during the task, spent more time on average per page, and more often looked for extra information. In a final questionnaire with factual and inferential questions, the NSG-group still performed better than the SG-group. The NSG-group may also show better transfer of what they had learnt to a new situation.

Incentives improve performance on both incremental and insight problem solving

An increasing number of studies are showing a connection between emotion and motivation and cognitive processes. Most of these studies, however, have been correlational in nature, limiting the conclusions that can be drawn. We directly manipulated motivation through the use of an incentive and investigated its effects on insight and incremental problem solving. In four experiments we found that an incentive (the opportunity to leave the experiment early) increased problem-solving performance for all problems presented, regardless of problem type. Additionally, we found evidence that the incentive increased recall memory, indicating more thorough processing for participants in the incentive condition. This study provides evidence that incentives influence problem solving and implies that motivation should not be ignored when investigating cognitive processes.

Expertise in Complex Decision Making: The Role of Search in Chess 70 Years After de Groot

One of the most influential studies in all expertise research is de Groots (1946) study of chess players, which suggested that pattern recognition, rather than search, was the key determinant of expertise. Many changes have occurred in the chess world since de Groots study, leading some authors to argue that the cognitive mechanisms underlying expertise have also changed. We decided to replicate de Groots study to empirically test these claims and to examine whether the trends in the data have changed over time. Six Grandmasters, five International Masters, six Experts, and five Class A players completed the think-aloud procedure for two chess positions. Findings indicate that Grandmasters and International Masters search more quickly than Experts and Class A players, and that both groups today search substantially faster than players in previous studies. The findings, however, support de Groots overall conclusions and are consistent with predictions made by pattern recognition models.

Rewarding Multitasking: Negative Effects of an Incentive on Problem Solving under Divided Attention.

Research has consistently shown negative effects of multitasking on tasks such as problem solving. This study was designed to investigate the impact of an incentive when solving problems in a multitasking situation. Incentives have generally been shown to increase problem solving (e.g., Wieth and Burns, 2006), however, it is unclear whether an incentive can increase problem solving while attentional resources are divided. Participants were either given an incentive or not and asked to complete incremental and insight problems while either in a dual-task or single task condition. After solving the problems participants were given a surprise memory test. Results showed that the incentive only led to increases in problem solving in the single task condition but not the dual-task condition. Furthermore, results showed that an incentive in the dual-task condition led to an increase in recall of irrelevant information. These findings indicate that an incentive cannot ameliorate the detrimental effects of multitasking when problem solving and may even lead to an increase in irrelevant information processing.