Predictive Model for Student Academic Decline During Virtual Education in the COVID-19 Pandemic

Abstract

Academic decline has always been a primary concern for researchers in the field of education. Recently, the COVID-19 pandemic has shed new light on this phenomenon. This study aims to identify factors affecting academic decline during the COVID-19 pandemic and develop a model to predict academic decline during virtual education. The present research employed a mixed qualitative-quantitative methodology. The study population included all mothers, students, and teachers of middle and high school levels in the city of Sabzevar in 2021. A sample of 30 individuals was selected through purposive sampling due to data saturation, considering inclusion and exclusion criteria, and interviewed. Following the identification and validation of qualitative categories and factors, a questionnaire was designed and administered to 384 participants (mothers, students, and teachers of middle and high school levels). The unlimited population responded to the researcher-made 49-item questionnaire on the challenges of virtual education impacting academic decline during the COVID-19 pandemic. To test the research hypotheses, descriptive statistics and structural equation modeling (SEM) using SPSS 20 and PLS Smart software were utilized. The findings indicated that, following qualitative interviews, six main grounded theory categories emerged, encompassing 12 fundamental factors. These included two causal factors (lack of motivation and academic isolation), one central factor (academic decline), three contextual factors (quantity and quality of electronic devices, internet quality, and software and hardware deficiencies), three intervening factors (role pressure on parents, web usage culture, and learning environment), and two strategies (ineffective teaching and inappropriate assessment) and one outcome (reduced learning). Ultimately, the structural equation modeling validated the conceptual model designed based on grounded theory. The results indicated that 12 fundamental factors influenced academic decline during virtual education amidst the COVID-19 pandemic, leading to the development of a significant predictive model for academic decline in virtual education.