E-learning, assessment competency, and academic performance: A structural equation modeling approach

Abstract

E-learning practices and the competency in assessment should facilitate one’s academic performance. The main purpose of this study is to explore the degree of influence of e-learning practices and competency in assessment on academic achievement of students. This study is a quantitative approach using survey method involving the process of data collection through the administration of constructed instruments. The population of the study involves student teachers from the three selected universities in Selangor and Perak. Sample selection is drawn using random sampling technique. A total of 460 student teachers are selected. The questionnaire for e-learning practices is adapted from OLES (Renee, 2011) and the competency in assessment comes from Zahari (2018). The structural equation modeling (SEM) analysis is used to test the hypothesized relationship. The results show that e-learning practices, knowledge in assessment, skills in assessing, and attitude in assessment significantly influence students’ academic achievement. E-learning practices emerge as the strongest predictor of student achievement, with a significant standardized regression coefficient of 0.39. This is followed by skills in assessing (0.27), knowledge in assessment (0.09), and lastly attitude in assessment (0.08). The core findings of the study have some implications for higher education and practice, measurement and theory development, and future research.

Keywords

• e-learning
• assessment competency
• academic performance
• structural equation model