Statistical modelling of the impact of online courses in higher education on sustainable development
International Journal of Sustainability in Higher Education
; 24(2):404-425, 2023.
Article
Dans Anglais
| ProQuest Central | ID: covidwho-2233007
ABSTRACT
Purpose>The concept of sustainable development (SD) is a popular response to society's need to preserve and extend the life span of natural resources. One of the 17 goals of the SD is "education quality” (Fourth Goal of Sustainable Development [SDG-4]). Education quality is an important goal because education is a powerful force that can influence social policies and social change. The SDG-4 must be measured in different contexts, and the tools to quantify its effects require exploration. So, this study aims to propose a statistical model to measure the impact of higher education online courses on SD and a structural equation model (SEM) to find constructs or factors that help us explain a sustainability benefits rate. These proposed models integrate the three areas of sustainability social, economic and environmental.Design/methodology/approach>A beta regression model suggests features that include the academic and economic opportunities offered by the institution, the involvement in research activities and the quality of the online courses. A structural equation modelling (SEM) analysis allowed selecting the key variables and constructs that are strongly linked to the SD.Findings>One of the key findings showed that the benefit provided by online courses in terms of SD is 62.99% higher than that of offline courses in aspects such as transportation, photocopies, printouts, books, food, clothing, enrolment fees and connectivity.Research limitations/implications>The SEM model needs large sample sizes to have consistent estimations. Thus, despite the obtained estimations in the proposed SEM model being reliable, the authors consider that a limitation of this study was the required time to collect data corresponding to the estimated sample size.Originality/value>This study proposes two novel and different ways to estimate the sustainability benefits rate focused on SDG-4, and machine learning tools are implemented to validate and gain robustness in the estimations of the beta model. Additionally, the SEM model allows us to identify new constructs associated with SDG-4.
Education--Higher Education; Sustainable development; Beta regression; Structural equation modelling; Sustainability; Online education; Artificial intelligence; Odds; Teaching; Higher education; Students; Computer assisted instruction--CAI; Life span; Values; Regression models; Questionnaires; Economic models; Statistical models; Social change; Machine learning; Statistical analysis; Books; Distance learning; Natural resources; COVID-19; Environmental education; Education; Pandemics; Clothing; Variables; Quality of education; Online instruction; Multivariate statistical analysis; Social interactions; Coronaviruses; Mathematical models; Environmental aspects
Texte intégral:
Disponible
Collection:
Bases de données des oragnisations internationales
Base de données:
ProQuest Central
Type d'étude:
Études expérimentales
/
Étude pronostique
langue:
Anglais
Revue:
International Journal of Sustainability in Higher Education
Année:
2023
Type de document:
Article
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