Theses and Dissertations


Issuing Body

Mississippi State University


Jarosz, Andrew F.

Committee Member

Moss, Jarrod

Committee Member

Bradshaw, Gary

Committee Member

Allen, Laura K.

Committee Member

Pratte, Michael

Date of Degree


Document Type

Dissertation - Open Access


Applied Psychology

Degree Name

Doctor of Philosophy (Ph.D)


College of Arts and Sciences


Department of Psychology


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.