Ordered Logistic Regression Model on How Logical and Rewarding is Learning Statistics Online


  • Leomarich F. Casinillo Department of Mathematics, Visayas State University, Baybay City, Leyte, Philippines




Statistics Education, Logical and Rewarding, Influencing Determinants, Ordered Logistic Regression, College Students


Statistics education amid the new normal faced a lot of challenges and barriers where students cannot seriously experience the logical and rewarding nature of statistics. This research article aimed to describe the logical and rewarding nature of statistics experienced by students in the new normal and elucidate the causal determinants. The study dealt with secondary and cross-sectional data from the current study in the literature. Standard descriptive measures, frequency table, and chi-square test were calculated to summarize the selected variables, and ordered logistic regression was employed to capture the influencing factors of how logical and rewarding learning statistics is. Results showed that, on average, statistics learning during distance education is both logical and rewarding. The regression models revealed that the predictors of the logical nature of statistics are younger students, male students, money for the internet, and a conducive place for learning. Meanwhile, the predictors of the rewarding nature of statistics are male students, household assets, physical health, money for the internet, and a conducive place for learning. Conclusively, students with more resources and a comfortable place for learning are likely to perform better and satisfied with learning. Hence, students in distance education must be provided with suitable tools for learning, and a healthy and conducive environment for studying.


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How to Cite

Casinillo, L. F. (2023). Ordered Logistic Regression Model on How Logical and Rewarding is Learning Statistics Online. Asian Journal of Assessment in Teaching and Learning, 13(2), 1–9. https://doi.org/10.37134/ajatel.vol13.2.1.2023