Abstract:
The study focuses on the conceptual development of beliefs based measures in technology
acceptance of online learning over traditional method, with respect to Sri Lankan higher education.
This research provides valuable insights on managerial interventions, investments and controls for
better organizational e-learning management that can lead to greater acceptance and effective
utilization. Unlike much preceding studies that has focused on only a limited aspect of beliefs based
measures, this research provides a more comprehensive conceptual structure that emphasizes the
effects of various unconventional exogenous elements such as innovativeness and eco-friendliness.
The research assesses the nomological validity of the conceptualization by integrating the theories,
technology acceptance model (TAM), theory of planned behaviour (TPB), unified theory of
acceptance (UTAUT) and diffusion of innovation theory (DIT) in a voluntary environment. To
produce more sturdy and innovative results, the research first confirms the influence of conventional
variables on online learning acceptance. Secondly, it emphasizes the influence of newly added
constructs. PhD university students in Colombo District, Sri Lanka being considered as the target
population and the model of this study will be tested with a field sample of 150 students (Population
is around 200). The population is stratified into 3 distinct categories (1. University of Colombo, 2.
Open University, Sri Lanka 3. MSU, Sri Lanka); thereafter subjects are drawn disproportionate to
their original numbers in the population. An instrument with 7-point likert scale measures, is used to
obtain responses. The structural equation model is applied to analyse the relationships demarcated in
the theoretical model of the study. Subsequently, the hypotheses linked with ‘‘factors associated with
technology acceptance of online learning, among the PhD university students in Colombo, Sri
Lanka’’ will be substantiated, by emphasising the relationship among prior factors, antecedent
factors and consequent factors. The factors which are highly influential to enhance the level of
technology acceptance of online learning will be filtered out at the end to allocate necessary
investments.
