Open AccessTHE EFFECT OF PUBLIC POLICY ON THE DEMAND FOR HIGHER EDUCATION IN PAKISTAN: CASE OF COVID-19
Author(s) -
Muhammad Ibrahim Shah,
Noor Jehan,
Amreena Begum,
Ghazala Naheed Beig,
Waheedullah
Publication year - 2021
Publication title -
humanities and social sciences reviews
Language(s) - English
Resource type - Journals
ISSN - 2395-6518
DOI - 10.18510/hssr.2021.9419
Subject(s) - cronbach's alpha , novelty , preparedness , adaptability , originality , government (linguistics) , psychology , covid-19 , higher education , medical education , business , marketing , political science , medicine , social psychology , economics , management , creativity , infectious disease (medical specialty) , law , service (business) , linguistics , philosophy , disease , pathology
Purpose of the study: This research was conducted in the peak days of the Covid-19 pandemic. The intention was to know the effect of public policy of online classes on demand for higher studies.
Methodology: The data was collected online through Google forms via direct requests in different students groups. The probability that a student will continue studies if online classes were continued was the dependent variable and hence a "1" response and a "0" response otherwise, so logistic regression was applied.
Main Findings: If there is a preparedness problem for online classes, there would be a decrease in another admission, while ease of adaptability will increase admissions. A unit increase in tuition fees significantly negatively affects the probability of admissions in the online system. A male student, a day scholar student, has more probability of continuing studies in the online system.
Applications of this study: This study is very fruitful in devising educational policy and government guidance. Online classes were a new thing for the majority of the students and institutions, and our results can be of great help in the future course of action.
Novelty/Originality of this study: The study developed a perceptive questionnaire about online classes, and it was found to be reliable based on Cronbach alpha value of .82. We run Principal Component Analysis on a reliable scale and three components were extracted in the process i.e. ease of adaptability, system-related and preparedness problem.