Self-Efficacy and Self-Regulation as Predictors of Academic Motivation among Undergraduate Students in the United States

Problem Some undergraduate students demonstrate lack of academic motivation which negatively affects engagement and perseverance in higher education (Busse & Walter, 2017; Rizkallah & Seitz, 2017; Dresel & Grassinger, 2013). Amotivated students are more likely to drop out of school and disengage from learning activities or underachieve (Wang & Pomerantz, 2009). Although the lack of academic motivation is correlated with deficiency in self-regulation and self-efficacy, relatively little studies have been conducted to examine the impact of these factors on academic motivation particularly in the U.S. This study constructed a hypothesized model to investigate the role of self-regulation and self-efficacy in academic motivation. Method The sample consisted of 349 undergraduate students enrolled in U.S. universities. Participants were recruited via the online-tool QuestionPro. The students completed the Academic Motivation Scale (AMS) and Motivated Strategies for Learning Questionnaire (MSLQ) online providing input about their academic motivation, self-regulation, and self-efficacy. Structural equation modeling was used to evaluate the impact of self-regulation and self-efficacy on academic motivation. Results Analysis of the data indicated that the initial model did not fit the data. The Chi-square value was 271.569, df = 40, p = .000, and poor fit indices were found (GFI = .875, NFI = .874, CFI = .889, RMSEA = .129. SRMR= .090). Therefore, an exploratory analysis was conducted, and modifications made based on modification indices and theory in order to improve the fit indices. The adjusted model showed acceptable fit between the theoretical covariance matrix and the empirical covariance matrix (GFI = .918, NFI = .913, CFI = .928, RMSEA = .108, and SRMR = .072) indicating that the data fit the hypothesized model. The overall adjusted model explained 41% of the variance of academic motivation, in which self-efficacy (β = .45; p < .01) was a better predictor of academic motivation than self-regulation (β = .24; p < .01). There was significant correlation between self-regulation and self-efficacy (r = .69, p < .01) Conclusion Self-regulation and self-efficacy can predict students’ academic motivation. Self-efficacy was the best predictor of academic motivation. Students who reported high beliefs in their capabilities and control over their effort showed high levels of intrinsic motivation. In addition, advanced levels of metacognitive strategies, time and study environment, and effort regulation predict high levels of academic motivation. Further research should be conducted to determine other factors that may contribute to students’ academic motivation. This study offers recommendations for future research and professional practice.