Self-Regulation and Academic Motivation as Predictors of Academic Achievement of Undergraduate Students in an Online Learning Environment
Problem Online learning is a form of distance education that occurs via the Internet (Adams, 2004; Carliner, 1999). The success of online learning depends on student-related factors such as acceptance, willingness, and motivation (Almaiah et al., 2019; Almaiah et al., 2020). When online learning systems are not utilized, students cannot realize the concomitant benefit of improved performance. Online learning has many positives, but it does present a problem when it comes to academic success. Motivation and self-regulation are two of the key factors for successful online learning given that students are subject to minimal supervision or guidance from teachers in an online environment. Lack of motivation and low levels of self-regulation can decrease students’ academic outcomes. It is, therefore, important to understand to what extent self-regulation and motivation impact academic success in an online learning environment, to better develop strategies to improve motivation, enhance self-regulation, and address the shortcomings they present to online learning. The focus of this study is the relationship between students’ self-regulation, academic motivation, and academic achievement in an online learning environment (Alafghani & Purwandari, 2019; Bandura, 1991; Panadero, 2017; Yusuf, 2011). Method A non-experimental quantitative research design was used to investigate the relationship between self-regulation, academic motivation, and academic achievement of undergraduate students in an online learning environment. QuestionPro hosted the survey. The data were collected using self-report questionnaires, and the sample population consisted of 300 undergraduate students taking online courses in the United States. The Online Self-Regulated Learning Questionnaire (OSLQ) and Academic Motivation Scale (AMS) were used to measure self-regulation and academic motivation, respectively. Structural Equation Modeling (SEM) was used to analyze the data, and Multigroup Structural Equation Modeling (MSEM) was used to understand gender differences between the variables. To achieve a valid interpretation of data, the data was collected, screened, and analyzed using SPSS and AMOS software. Results In the current study, 41% of participants were seniors, 60% were taking four or fewer online courses, and 68% had a GPA above 3.0. Results of this study indicated that the self-regulation of undergraduate students in an online learning environment were at moderate levels. The subscale reported a high level of help-seeking and environment structuring. Task strategies, time management, goal setting, and self-evaluations were at a moderate level. Academic motivation, intrinsic motivation, and extrinsic motivation scales and subscales were at moderate levels. However, extrinsic motivation identified (ExMD) reported a high level. Amotivation was at the lowest level of academic motivation. There was no correlation between self-regulation and academic motivation in the academic achievement of undergraduate students in an online learning environment. However, self-regulation and academic motivation showed a positive and statistically significant correlation and the final model accounted for approximately 3% of the variance of academic achievement. The analysis revealed no gender differences between male and female undergraduate students in an online learning environment regarding their self-regulation, academic motivation, and academic achievement. Conclusions The findings support the current research and forms the basis for future research studies of students’ academic motivation, self-regulation, and academic performance in the online environment. Future research should conduct longitudinal studies to track students’ self-regulation skills, motivation, and academic achievement in an online learning environment to better understand their development and impact on academic outcomes. Such research should also investigate the role of individual differences, such as personality traits and prior academic achievement, in the relationship between self-regulation, academic motivation, and academic achievement in online learning environments.
Academic Achievement, Motivation, Self-Regulation, Online Learning, Undergraduate Students, Educational Psychology, Online and Distance Education
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