A Predicting Analysis of Academic Staff’s Motivation to Teach Online in a Nigerian University

This study examined the predictors of academic staff motivation for online teaching in a Nigerian University. Theory of Planned Behaviour served as the conceptual foundation for the study. A survey design was adopted and a total of one hundred and nine-five (195) academic staff participated in the study from a university that was purposefully chosen for the study. A questionnaire tagged ‘Academic Staff’s Motivation for Online Teaching Survey (SMOTS)’ adapted from Chi (2015) was used for data collection. The questionnaire consisted of six domains - demographics, online teaching consideration, perception of online teaching, motivation for online teaching concerning resources, motivation for online teaching with respect to external factors and general motivation to teach online. Data were analyzed using percentages and frequency distribution, mean, standard deviation, multiple regression analysis, Pearson Correlation, T-test, One-Way Analysis of Variance (ANOVA) and Multivariate Analysis of Variance (MANOVA). Results of the study revealed that the perception of online teaching and academic staff’s motivation for online teaching regarding external factors had a positive significant contribution to the general motivation of academic staff to teach online. Also, age was found to have a significant influence on academic staff’s motivation to teach online indicators (perception of teaching online, motivation to teach online regarding resources, and motivation to teach online regarding external factors). Hence, it was concluded that adequate consideration must be given to these identified contributing factors to motivation for online teaching among academic staff by those who design and implement online teaching initiatives in the university to sustain academic staff’s interest in online teaching over time. Equally, policy decisions on online teaching in the university should be based on clear objectives for the generality of the academic staff irrespective of age, gender, marital status, and faculty rank.