We can make it: A probabilistic analysis on the satisfaction in flexible learning

Abstract

When Higher Education Institutions shifted to online learning due to COVID-19, student satisfaction significantly dropped. Study aimed to determine which of the variables significantly influenced the satisfaction in flexible learning. This research employed quantitative design and used, stratified random sampling to determine the 205 respondents who answered the two adapted research questionnaires. Frequency, Spearman’s Correlation, and Binary Logistic Regression were used to statistically treat the data. The study confirmed that majority of the students had access to strong internet connection, and they used mobile data to access internet connection. Study revealed that most of the students used both smartphone and laptop to attend flexible learning. It is presented in this study that both modular learning and online learning were the learning modalities used in conducting flexible learning. Most of the instructors used Google Meet in conducting synchronous learning and LMS in the conduct of asynchronous classes. The study concluded a very weak, positive monotonic relationship between access to strong internet connection and student satisfaction in flexible learning and a very weak, positive monotonic relationship between type of internet connection and student satisfaction in flexible learning. Study posited that among the variables, only the access to strong internet connection has a significant influence on student satisfaction in flexible learning which means that when students have strong internet connection there is a likelihood that they will be satisfied in flexible learning. Further investigation is suggested to explore the result of the study employing a qualitative research design to give meaning on the experiences of students during the conduct of online learning.

Keywords

• binary logistic regression
• covid-19
• flexible learning
• quantitative design
• student satisfaction