Correlational study on virtual learning environment and students' academic performance at Tabuk University Saudi Arabia

Abstract

The aim of this study is to investigate the non-traditional student perceptions of the VLE based on the Keller’s ARCS model of motivational design and how the components of this model correlate to students’ academic performance. The study population consists of students from the Faculty of Arts at Tabuk University (UT) in the KSA with three specializations (Arabic, Islamic studies and languages), who study on the distance learning system and use the virtual classes. The study sample consisted of 324 non-traditional students. The quantitative approach was used in this study. The study employed stratified proportionate sampling to select the sample of 324 undergraduate students of Tabuk University. In order to collect data from this sample, the study used a questionnaire as a data collection tool consisting of 51 items. The content validity of this questionnaire was verified by twelve experts and computation of content validity ratio (CVR = 91.8%). The Principle Components Analysis (PCA) was conducted on a pilot study to reveal the basic components, as it became clear that there are 6 dimensions with 31 items (attention 4-items, relevance 8-items, confidence 4-items, satisfaction 5-items, appraisal 4-items, and academic performance 6-items), and 68.47% of variance. Cronbach’s alpha used to test the realibility of the questionnaire, indicates a high level of internal consistency. In order to collect the data, the final version of the questionnaire was translated into Arabic and to ensure the translation was correct, it was presented to experts. The questionnaire was then distributed to the students using Google Form by uploading it onto UT-LMS in coordination with the university's technical support. After obtaining student responses, SPSS was used to analyse the data. In order to obtain the results of this study, the descriptive analysis and the Confirmatory Factor Analysis (CFA) were used. The results indicated that the validity of the scale and its reliability consist of six dimensions and its components can be used in future studies to measure students’ academic performance in virtual learning environments. Multiple Regression Analysis (MRA) showed that there are four important predictions of students' academic performance (Satisfaction, Relevance, Confidence, and Appraisal). Of these four, satisfaction appeared to be the strongest indicator, while attention did not appear as an important indicator of students’ academic performance. T-test was applied and the result showed that there was no statistically significant difference between male and female in terms of students' academic performance. In addition, one-way ANOVA analysis indicated that there were no statistically significant difference between the three groups (Islamic, Arabic and Linguistic Studies) in terms of academic performance.