Classification of Motivational Dispositions: A Psychological Systems Perspective of Academic Behavior

Academic motivation is a complex psychological construct. It is multifaceted, hierarchical, dynamic, and developmental in nature. Students exhibit substantial heterogeneity in the ways in which academic motivation develops and manifests in short and long-term behavior. Much of the prior literature has considered motivated behavior in an academic subject like math to be the result of math motivation alone. This dissertation draws from the Eccles’ expectancy-value theory of achievement motivation, which posits that academic behavior is the result of subjective psychological perceptions of competence and task-value, in order to investigate the hierarchical and dynamic nature of motivational dispositions and their associations with academic behavior. In Chapter 2, I use variable and person-centered approaches to investigate the development of math and English self-concept of ability throughout adolescence and their dual role in the process of selecting a college major. I demonstrate that the relationship between math and English self-concept changes over time, from being positively correlated to uncorrelated to negatively correlated between sixth and twelfth grade. Cluster analyses uncover heterogeneity in the patterns of math and English self-concept that students hold, and these clusters are predictive of the college major that students eventually select. The cluster also reveal gender differences in self-concept hierarchies that ultimately relate to college major choice. In Chapter 3, I use longitudinal structural equation modeling to study the development of academic task-values in high school. I focus on the role of dimensional comparisons, which refer to cross-domain influences, across the domains of math, English, biology, and physical science. Results indicate that achievement relates to cross domain subjective task values (STV), and STV in 10th grade relates to cross domain STV in 12th grade. STVs in 12th grade relate to college major choice. In Chapter 4, I use cluster analysis and hierarchical logistic regression to investigate daily academic behavior in an undergraduate online course. I synthesize theories of motivated behavior and demonstrate that unique profiles of subjective task values and emotions relate to both expectations of task attainment and actual task attainment. In Chapter 5, I conclude with some critiques regarding the scientific study of motivation, such as problems with modeling latent constructs using linear models. I then present a dynamic systems approach from the physics to modeling human motivation

Classification of Motivational Dispositions: A Psychological Systems Perspective of Academic Behavior

Academic motivation is a complex psychological construct. It is multifaceted, hierarchical, dynamic, and developmental in nature. Students exhibit substantial heterogeneity in the ways in which academic motivation develops and manifests in short and long-term behavior. Much of the prior literature has considered motivated behavior in an academic subject like math to be the result of math motivation alone. This dissertation draws from the Eccles’ expectancy-value theory of achievement motivation, which posits that academic behavior is the result of subjective psychological perceptions of competence and task-value, in order to investigate the hierarchical and dynamic nature of motivational dispositions and their associations with academic behavior. In Chapter 2, I use variable and person-centered approaches to investigate the development of math and English self-concept of ability throughout adolescence and their dual role in the process of selecting a college major. I demonstrate that the relationship between math and English self-concept changes over time, from being positively correlated to uncorrelated to negatively correlated between sixth and twelfth grade. Cluster analyses uncover heterogeneity in the patterns of math and English self-concept that students hold, and these clusters are predictive of the college major that students eventually select. The cluster also reveal gender differences in self-concept hierarchies that ultimately relate to college major choice. In Chapter 3, I use longitudinal structural equation modeling to study the development of academic task-values in high school. I focus on the role of dimensional comparisons, which refer to cross-domain influences, across the domains of math, English, biology, and physical science. Results indicate that achievement relates to cross domain subjective task values (STV), and STV in 10th grade relates to cross domain STV in 12th grade. STVs in 12th grade relate to college major choice. In Chapter 4, I use cluster analysis and hierarchical logistic regression to investigate daily academic behavior in an undergraduate online course. I synthesize theories of motivated behavior and demonstrate that unique profiles of subjective task values and emotions relate to both expectations of task attainment and actual task attainment. In Chapter 5, I conclude with some critiques regarding the scientific study of motivation, such as problems with modeling latent constructs using linear models. I then present a dynamic systems approach from the physics to modeling human motivation

Selective importance in self-enhancement : Patterns of feedback adolescents use to improve math self-concept

We illustrate how early adolescents use different patterns of ability feedback to promote a positive self-concept of ability (SCA) in mathematics. Students can simultaneously use ability appraisals from parents and teachers, while also drawing information from peer, dimensional, and temporal comparisons. Although we find these five sources are equally important for promoting students’ positive SCA, on average, we use a pattern-centered approach to show that students who believe they are good at math often select certain feedback sources as more important to develop this belief. We find that students’ patterns of ability feedback are unstable, with evidence suggesting different patterns may emerge depending on the availability of ability feedback. Findings suggest early adolescents attempting to promote their own positive SCA in mathematics may know to seek different feedback sources depending on their individual circumstances. Implications are discussed through the lens of social comparison theory

Patterns of math and English self-concepts as motivation for college major selection

A variable and person-centered approach was applied to understand the development of cross domain self-concepts of ability, patterns of math and English self-concepts of ability throughout adolescence, and their associations with college major. An expectancy-value perspective was integrated with dimensional comparison theory to understand how math and English self-concepts of ability relate to one another over time and within a person. Regression analysis identified a positive association of math self-concept throughout adolescence with math-related majors and a negative association of English self-concept with math-related majors. Cluster analysis classified students into six to seven patterns of varying math and English self-concepts of ability. Stereotypical gender differences were observed in cluster membership, with women overrepresented in high English clusters and males over represented in high math clusters. Cluster membership was predictive of the math-related college majors. Students who were higher in math self concept of ability relative to English were overrepresented in math intensive majors. Findings support the importance of considering intraindividual hierarchies and ipsative relationships when studying the development of self-concept of ability and academic choices

The System of Academic Task Values: The Development of Cross-Domain Comparisons of Values and College Major Choice

This study synthesizes theories of achievement motivation to better understand the development of academic task values in high school students and their relation to college major selection. We utilize longitudinal structural equation modeling to understand how grades relate to task values, how task values across domains relate to one another over time, and how the system of task values relates to college major choice. In our sample of 1,279 high students from Michigan, we find evidence that task value for math negatively relates to task value for English and vice versa. We also find that task value for math and physical science positively relates to the math-intensiveness of selected college majors, whereas English and biology task value negatively relates to math-intensiveness of majors. Gender differences in college major selection are mediated by differences in task values. Our findings have implications for theories of achievement motivation and motivational interventions. (PsycInfo Database Record (c) 2023 APA, all rights reserved)