African Multidisciplinary Journal of Sciences and Artificial Intelligence
Vol 1 No 1 (2024): African Multidisciplinary Journal of Sciences and Artificial Intelligence

Perceived Availability, Accessibility, Usability, Training and Competence in Ict Resources as Predictors of Universities Biology Lecturers’ Productivity in North East, Nigeria

Jefferson Geoffrey (Unknown)



Article Info

Publish Date
31 Jul 2024

Abstract

This study examined the perceived availability, accessibility, usability, training and competence in ICT resources by rank predict universities Biology lecturers’ perceived productivity and perceived availability, accessibility, usability, training and competence in ICT resources by rank and gender predict universities Biology lecturers’ perceived productivity. The study adopted the correlation research design. The study was carried out only in Federal Universities in North-East zone Nigeria. The zone is made up of six states namely Adamawa, Bauchi, Borno, Gombe, Taraba and Yobe states. The population for the study comprised of 629 Biology lecturers. Sample of 315 Biology lecturers were drawn from Federal Universities in North east, Nigeria for the study as suggested by (Nwana 2005). 50% of the population was drawn as sample size for the study. Samples for the study were obtained from the six universities by Proportional stratified sampling technique. The actual selection of elements was done using simple random sampling technique. The instrument used for data collection was titled “ICT Resources and University Biology Lecturers Perceived Productivity Questionnaire” (IRUBLPQ). The questionnaire used modified Likert scale response options of Very High Level (VHL), High Level (HL), Moderate Level (ML), and Low Level. The research instrument was validated by three experts. The experts were in Biology, Mathematics and Physics. The reliability of the instrument was determined using Cronbach Alpha method to determine the internal consistency of the items of the questionnaire. Reliability Coefficient of 0.74 was obtained for 10 items from perceived availability, accessibility, usability, training and competence instrument. Universities Biology lecturers’ perceived productivity instrument with 30 items gave a reliability coefficient of 0.77. The data for this study were collected by six research assistants, one for each of the six federal universities in the North East, Nigeria. Mean and standard deviation were used to answer the research questions. Hypotheses one to two were tested using multiple regression analysis. The hypotheses were tested at 0.05 level of significance. The findings of the study revealed perceived availability, accessibility, usability, training and competence in ICT resources by rank do not significantly predict universities Biology lecturers perceived productivity in North East, Nigeria. (R2 = 0.02, F = F = 2.455, P = 0.25) and perceived availability, accessibility, usability, training and competence in ICT resources by gender do not significantly predict universities Biology lecturers’ perceived productivity in North East, Nigeria. (R2 = 0.03, F = 2.94, P = 0.1). Based on the findings of the study, since evidence from the P- value revealed that perceived availability, accessibility, usability, training and competence in ICT resources do not significantly predict the university Biology lecturers perceived productivity in north east, Nigeria’ based on rank. Therefore, university Biology lecturers should be encouraged to incorporate ICT resources in their teaching irrespective of rank. Also results from the study revealed perceived availability, accessibility, usability, training and competence in ICT resources do not predict university Biology lecturers’ perceived productivity of in north east, Nigeria based on gender. Therefore, both male and female university Biology lecturers should be encouraged to be engaged in ICT resources during their research and teaching programs.

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Journal Info

Abbrev

AMJSAI

Publisher

Subject

Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Environmental Science Materials Science & Nanotechnology

Description

African Multidisciplinary Journal of Sciences and Artificial Intelligence aims to publish high-quality, peer-reviewed scholarship that advances scientific knowledge and fosters multidisciplinary integration across the sciences, engineering, health, agriculture, environmental studies, and artificial ...