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The role of knowledge representations in rule transfer on a novel problem-solving task

Although the independent roles of working memory capacity (WMC) and knowledge in problem solving have been thoroughly researched, there is significantly less work that has explored how WMC and knowledge interact during problem solving. The present study investigated how the quality of knowledge representations contribute to rule transfer in a problem-solving context and how WMC might contribute to the subsequent failure or success in transferring the relevant information. Participants were trained on individual figural analogies rules and then asked to rate how similar they thought the rules were to determine how stimulispecific or abstract their rule representations were. Their rule representation score, along with other measures (WMC and fluid intelligence measures) were used to predict accuracy on a set of test items, of which half included only the trained rules, and the other half were comprised of entirely new rules. Results indicated that the training did improve performance on the test items and that WMC largely explained the ability to transfer rules. Although the rule representations scores did not predict accuracy on the trained items, the results suggest that rule representations may be important for inductive reasoning or pattern recognition, rather than explaining transfer. Furthermore, rule representations uniquely explained performance on the figural analogies task, even after accounting for WMC and fluid intelligence. Altogether, these results indicate that WMC plays a large role in knowledge transfer, even when transferring to a more complex problem-solving context, and that rule representations may be important for novel problem solving.

Identiferoai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-6446
Date13 May 2022
CreatorsRaden, Megan J
PublisherScholars Junction
Source SetsMississippi State University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceTheses and Dissertations

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