Author ORCID Identifier

https://orcid.org/0000-0002-8220-831X

Date Available

6-24-2022

Year of Publication

2021

Document Type

Doctoral Dissertation

Degree Name

Doctor of Philosophy (PhD)

College

Education

Department/School/Program

Educational, School, and Counseling Psychology

Advisor

Dr. Ellen L. Usher

Abstract

Self-efficacy, the beliefs learners hold about what they can do, develops largely from how learners perceive and interpret four main sources of information: mastery experiences, vicarious experiences, social persuasions, and physiological states. Although researchers have shown a relationship between these sources and math self-efficacy, less is known about the factors that may influence how early adolescent learners perceive and interpret information from these sources. The purpose of this dissertation was to investigate two possible factors (i.e., perfectionism, performance-related factors) that might predict how learners perceive efficacy-relevant information in the domain of math. Study 1 used a correlational design to investigate whether perfectionism was associated with how middle school students (N = 1,683) interpret information from the four hypothesized sources of self-efficacy. Participants completed a paper-based survey at two timepoints. Perfectionism was measured at Time 1. Self-efficacy and its sources were measured at Time 2. Structural equation modeling techniques were used to examine the relationship between factors. Students who held themselves to high standards (i.e., greater self-oriented perfectionism) reported higher levels of mastery experiences, positive vicarious experiences, positive social messages, and self-efficacy. Conversely, students who felt external pressure to be perfect (i.e., socially-prescribed perfectionism) reported lower levels of mastery experiences, vicarious experiences, and self-efficacy, as well as higher levels of negative physiological and affective states. The relationship between perfectionism and self-efficacy was partially mediated by students’ perceptions of mastery, suggesting that the relationship between perfectionism and math self-efficacy is partially explained by how perfectionism is related to students’ perceived mastery. Study 2 used a correlational design to investigate the relationship between performance factors (e.g., number correct, effort, difficulty) and adolescent students’ (N = 286) perceived mastery on a novel online math puzzle. Students completed two sets of three puzzles. Each puzzle displayed four equations in which emojis were used instead of traditional lettered notation (e.g., x, y, z) to represent unknown variables. Solutions were provided for the first three equations. Students’ task was to determine the value of each emoji and to use that information to solve the fourth equation. After each puzzle, students rated how difficult the puzzle was and how much effort they put forth. After the first puzzle set, students evaluated their perceived mastery on the task, task-specific math self-efficacy, and intrinsic motivation. They were also asked whether they wanted to reengage in the task. Students then completed a second set of puzzles. Path analyses revealed that when students perceived the task as difficult, they felt less successful. Conversely, when students reported exerting a high level of effort on the task, they felt more successful. Perceived mastery was directly and positively associated with task-specific math self-efficacy, intrinsic motivation, and performance on subsequent puzzles. Task-specific math self-efficacy was positively associated with intrinsic motivation, but negatively associated with subsequent performance. This dissertation extends the current literature on the sources of math self-efficacy in early adolescence by showing the ways in which perfectionism, task difficulty, and perceived effort are associated with how adolescent learners perceive and interpret efficacy-relevant information.

Digital Object Identifier (DOI)

https://doi.org/10.13023/etd.2021.229

Funding Information

This study was supported by the National Science Foundation Graduate Student Research Fellowship Program (NSF-GRFP; no. 1247392) in 2018-2021.

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