The Importance of Representational Shift: An Investigation of the Cognitive Mechanisms and Individual Differences Underlying Math Performance
Year: 2019
Type: article
Abstract: 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.
Author: Allison S. Liu
Language: English
Subfield: Developmental and Educational Psychology
Field: Psychology
Domain: Social Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W2954465356