Analyzing Non-Cognitive Predictors of Secondary and Postsecondary Academic Achievement
thesisposted on 12.12.2020, 01:15 by Brianna Joy CermakBrianna Joy Cermak
A secondary data analysis was conducted using the High School Longitudinal Study of 2009 (HSLS:09) provided by the National Center for Education Statistics to assess the relationships between academic performance indicators (high school GPA, high school mathematics achievement, and college enrollment) and perceptions of utility value, self-efficacy, effort cost, school engagement, and intelligence theories (N = 5,789). Four data collection phases occurred
during HSLS:09-- 9th grade fall semester (BY), 11th grade spring semester (F1), undergraduate update in summer 2013 (U13), and a second follow-up in winter 2016 (F2).
The domain specificity and stability over time of each motivational construct was also assessed. Evaluating the domain specificity of a motivational construct helps us further understand the theoretical construction and appropriate measurement of these constructs. Motivational
constructs that are more stable over time are more likely to be more effective long-term predictors of academic performance. Paired t-tests were conducted to evaluate the domain specificity and stability of each motivational construct. Regression models were utilized to
assess motivational constructs’ ability to predict academic performance.
Effort cost was the only motivational construct that was not domain specific (t = 1.79, p = 0.07). Science self-efficacy was the only motivational construct determined to be stable over time (t = 1.19, p = 0.24). School engagement, BY science efficacy, mathematics effort, and F1 science
utility were significant predictors of increased academic performance for all academic performance indicators.