Pre-condition model to enhance the success of online teaching and learning in higher education

Abstract

The swift transition to online teaching and learning (OTL) during the COVID-19 pandemic revealed substantial deficiencies in institutional preparedness and elicited apprehensions regarding the long-term viability of online delivery beyond emergencies. Existing research has focused on what students and teachers go through during implementation; not enough pre-conditions are required for OTL to work. This study addresses this gap by developing a data-driven precondition model aimed at enhancing the success of OTL in higher education. The study employs survey data collected from students and professors at the Durban University of Technology Business School, utilising exploratory factor analysis and structural equation modelling to identify and validate critical attributes and relationships. The findings show five main aspects influencing OTL readiness: structural barriers, training readiness, institutional support, online engagement, and learning flexibility. Structural barriers influence outcomes indirectly through the mediating roles of training readiness and institutional support. The study proposes a layered pre-condition model that positions infrastructure as foundational, readiness and support as enabling factors, while engagement and flexibility serve as outcome variables. The model presents a practical framework for institutional preparedness evaluation before implementation. It also supports a transition from reactive adoption to more planned and sustainable online education strategies.