Perceived ease of use and usefulness as determinants of the use of web based survey by students for research

Abstract

The rapid digitalisation of academic environments has fundamentally altered the manner in which students approach data collection. This study investigates perceived ease of use and perceived usefulness as determinants of the use of web based survey tools by students, within the interpretive framework of the Technology Acceptance Model. Employing a descriptive survey research design, data were collected from 157 students at the Faculty of Management Science, University of Benin, through a proportionate stratified random sampling technique. The data were analysed by means of descriptive statistics, and frequency distributions and simple percentages were used to summarise the perceptions of respondents. The study is explicitly descriptive in orientation, for the Technology Acceptance Model is employed as an interpretive and organisational lens rather than as a formally tested causal model. The binary response format of the instrument does not support the regression or structural equation modelling that would be required to test the predictive hypotheses of the model, and no claim to have tested those relationships is advanced. The reliability of the instrument was established through the test and retest method, which yielded an overall Cronbach alpha of 0.78 and thereby indicated satisfactory internal consistency. The findings reveal a high level of awareness, at 77.1 percent, regarding web based survey tools, and they indicate that students adopt these technologies principally for their capacity to reduce physical stress, to minimise cost, and to provide rapid data turnaround. The study identifies significant barriers, among them non response bias, a deficiency in the advanced technical skills required for survey customisation, and growing concern over data privacy. The study concludes that, although perceptions of ease and usefulness are high, institutional intervention is required to improve the methodological rigour of student led online research, and it recommends that future studies employ continuous scale instruments and inferential methods in order to test the predictive pathways of the model formally within this population