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The Importance of Representational Shift: An Investigation of the Cognitive Mechanisms and Individual Differences Underlying Math Performance

Liu, Allison (2019) The Importance of Representational Shift: An Investigation of the Cognitive Mechanisms and Individual Differences Underlying Math Performance. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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College dropout is a significant issue that particularly plagues students with poor math preparation. Many studies have attempted to understand the factors that contribute to math performance and create training interventions that can effectively improve math achievement. However, few studies have investigated these questions within populations similar to the lower achieving adults who are most at risk to drop out from college. Further, few have looked at many potential mechanisms at once to determine how each contributes to math performance. In this dissertation, we investigated the relationships between a number of cognitive and individual difference measures and different types of math performance. We also evaluated the effectiveness of an estimation-based training program that targeted one of these cognitive mechanisms to determine the factors that predict progress during the intervention and the mechanisms that explain math improvements. Importantly, we recruited participants with relatively low math skill level to better examine the underlying math foundations in adults who are most likely to struggle with math in college. Across both studies, we find evidence of a representational shift that supports higher math performance in procedural and complex math; specifically, in higher math-skilled individuals, procedural math relies more on mechanisms that involve non-symbolic number representations, while complex math draws upon mechanisms that involve primarily symbolic number representations.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Liu, Allisonasl36@pitt.eduasl360000-0003-1075-2575
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairSchunn,
Committee MemberAnsari,
Committee MemberFiez,
Committee MemberLibertus,
Date: 30 January 2019
Date Type: Publication
Defense Date: 13 August 2018
Approval Date: 30 January 2019
Submission Date: 31 August 2018
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 113
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Psychology
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: individual differences, math achievement, math performance, number representations, symbolic integration
Date Deposited: 31 Jan 2019 00:04
Last Modified: 31 Jan 2019 00:04


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