Quantile Regression Analysis for Students’ Difficulty Level in Learning Statistics Online

Abstract

Statistics learning in the time of distance education makes students uneasy due to the difficulties in the learning environment and processes. This article aims to analyze the level of difficulty faced by students in statistics distance education and captures the causal factors affecting it. Cross-sectional secondary data were used from a current study in literature and described by standard statistical measures. The study utilized the level of difficulty in learning statistics during online setup as the dependent variable in the form of a scale of 1 to 10. The study used standard descriptive measures. Moreover, this study also use quantile regression models were constructed. Results depicted that students were facing "difficulty" as they learn statistics during distance education. The quantile regression revealed that the learning environment, inaccessible places (rural areas), and more family members are the statistically significant factors that influence the difficulty level in learning statistics online. This implies that due to the distractive place of learning, students cannot focus and penetrate their lessons. In addition, students were struggling with communication technology and internet access wherein it is vital in classroom engagement and the acquisition of learning resources. Hence, the study suggests that students must be supported by the government in regard to their learning needs and teachers must promote a positive and interesting educational environment. Furthermore, teachers must undergo training and workshops on how to be equipped in teaching statistics online.