Abstract:

The COVID-19 pandemic forced educators and students to switch to hybrid and online learning from traditional modes. Investigating the novel difficulties and benefits of hybrid learning in education is essential. Using primary samples, this paper used a parametric t-test to explore the impact of students' happiness, future hybrid learning, overall satisfaction, and long-term solutions to hybrid learning’s difficulties, benefits, and satisfaction. All the rules of parametric tests, such as equal variance, normality, and independence, are followed, and the reliability of variables is tested with the Cronbach alpha test (0.82). Our results found significant impacts of the above dependent variables on the independent variable (p<0.05). We also applied binary logistic regression to identify happiness with an accuracy of 79.8% and the suitability of hybrid learning for practical labs with an accuracy of 76.8%. Omnibus tests of model coefficients are used to test the fit of both models (p<0.05), and the Hosmer and Lemeshow tests proved a good fit for both models (p>0.05). Less difference is found between observed and predicted values. Nagelkerke’s R2 explained that a 36% change in happiness and a 35% change in the suitability of hybrid learning for practical labs could account for difficulties, benefits, and satisfaction.

Keywords:

Hybrid learning, probability, difficulty, logistic regression, t-test, student, happiness, benefit, satisfaction.