Digital skills impact on university students’ academic performance: An empirical investigation

Abstract

E-learning adoption strategies are rising alongside the growth and accessibility of e-learning technologies that cater to the needs of a diverse range of learners. Meanwhile, most e-learning models and approaches try to find the optimal match between e-learning components and the determinants for enhancing e-learning and learner performance. Learners' digital skills are important determinants for elearning success, which was not widely tested in prior research. Therefore, this paper aims to provide further insight into digital skills and their impact on students’ performance in the e-learning system. A comprehensive model was proposed incorporating digital skills dimensions (common digital skills, educational digital skills, and advanced digital skills) as independent variables and students’ academic performance (academic effectiveness, academic efficiency, academic satisfaction) as dependent variables, and data were collected from university students. After that, the study hypotheses and model were tested using regression analysis. The results reveal that the respondents possess satisfying common and educational digital skills, and less advanced digital skills. While their academic effectiveness and efficiency meet expectations, and their academic satisfaction is moderate. In addition, the findings show that the regression analysis supports the hypothesized relationships between independent and dependent variables in the research model; where digital skills dimensions positively impact students’ academic performance. Specifically, the results indicate that achieving the highest student academic performance requires a combination of digital skills application to be possessed by those students; mainly common digital communicating and application skills, educational digital problem-solving skills, digital safety skills, educational information and data processing skills, and some aspects of advanced digital skills such as application applications development, augmented reality, and database management systems. These results support the research model and show that this model provides good explanations for the variance in the student's academic performance. In addition, this study recommends further questions for more independent variables that may impact a student's academic performance dimensions.