ONLINE INSTRUCTIONAL DELIVERY AND ACADEMIC STAFF PRODUCTIVITY IN PUBLIC UNIVERSITIES IN CROSS RIVER STATE, NIGERIA
Keywords:
Online, Instructional, Delivery, Academic staff, Productivity, Universities.Abstract
This study sought to investigate the relationship between online instructional delivery and academic staff productivity in public Universities in Cross River State, Nigeria. To achieve this purpose, one composite research question was raised and later transformed to research hypothesis to guide the study. Ex-post factor design was adopted for the study. The population of the study was made up of all the academic staff that participates in online instructional delivery in the two Universities in the study area. Accidental sampling technique was adopted in the study. A Sample of 100 academic staff that delivered instructions using online method in the two public universities in the study area. The researcher self-developed questionnaire titled “Online Instructional Delivery and Academic Staff Productivity in Universities Questionnaire (OIDASPUQ) was used for data collection. The instrument was validated and subjected to reliability test using Cronbach Alpha reliability statistics. The result of the reliability test yielded an index of 0.72 which was adjudged well enough for data collection. Multiple regression statistics was used for data analysis at 0.05 level of significance. The results of the study revealed that online instructional delivery is anchored by some web-based applications: YouTube, Zoom, Google meet, Skype and Microsoft team which jointly predict academic staff productivity in public Universities in Cross River State, Nigeria. It was concluded that online instructional delivery predictive variables jointly predict academic staff productivity in universities. Base on the findings, it was recommended among others that, management of universities should improve on online instructional delivery architecture in collaboration with National University Commission via building of strong web-based applications and effective assessment to promote academic staff productivity in universities.
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