Modeling Determinants of Challenge in Learning Statistics in Time of the COVID-19 Pandemic

Abstract

During the COVID-19 pandemic, there were a lot of challenges encountered by students in learning statistics online that affected their cognitive attitudes. This study aims to evaluate the different determinants that significantly influenced the engineering students' level of challenge in learning statistics in the new normal with the aid of a structured questionnaire by means of a Google form survey. Descriptive statistics and multiple linear regression analysis were employed to extract meaningful information from the gathered data. Results showed that the students' perception score for the level of challenge in learning statistics is 7.37 (1.99), which can be interpreted as "challenging." This implies that students face challenges as they learn statistics lessons amid the pandemic setup. The regression models constructed have revealed that "age", "sex", "learning environment", "money spent on internet load", "physical health", and "creativity of statistics lessons" are the significant causal factors of the level of challenge in learning statistics. Conclusively, statistics teachers must adjust and be considerate to their students in regard to their learning needs in line with the pandemic setup. The government also must provide a budget for seminars and training to college teachers concerning distance education. Furthermore, it is recommended that statistics teachers must create an interesting learning environment to fully catch students' attention despite challenges.