Dire et al
Greener Journal of Agricultural Sciences Vol. 7 (2), pp. 047-053, March 2017.
Manuscript Number: 101716170
Factors Influencing e-Readiness of Agricultural Extension Agents in Adamawa, Gombe and Taraba States Nigeria
Dire B*1, Ndaghu AA2, Giroh DY3, Onu JI 4 and Dauna Y5
1, 2, 3, 4,5Department of Agricultural Economics and Extension, School of Agriculture and Agricultural Technology, Modibbo Adama University of Technology, Yola. Adamawa State, Nigeria.
The study assessed the factors
influencing e-readiness of agricultural extension agents in Adamawa, Gombe and
Taraba States, Nigeria. The specific objectives include describe the socio-economic
characteristics of the agricultural extension agents and assess factors
influencing agricultural extension agents’ use of ICTs in the performance of
their duties. Primary data was used for the study and were collected through
the administration of questionnaires. A multistage-stage random sampling
technique was employed to proportionately select 254 agricultural extension
agents from Adamawa, Gombe and Taraba States Nigeria using Taro Yamane’s
formula. Data collected were analyzed using descriptive and the inferential statistics. The
results of the analysis revealed that majority of agricultural extension agents
were between the ages of 41 – 50 years and non below the age of 20 years. A large proportion of the agricultural extension
agents about 70% were male with only 30.71% female. Majority (91.34%) were
married all (100%) of the agricultural extension agents in the study area had
one form of formal education or the other with 45.7% and 1.57% of them had
Degree/Higher National Diploma (HND) and Masters Degrees respective. Majority
(77%) of the agricultural extension agents have been in service above 21 years
with a mean working experience of 6.5 years was. 61.42% had grade levels of
between 10 and 15 with 67.71% had an estimated average annual income of between
N20, 000.00 – N 60, 000.00 only. The factors influencing e-readiness
of agricultural extension agents as shown by the McFadden R2 in the Logit regression analysis explained
about 92% of the variation of independent variable with age, marital, education
status, years of experience, monthly income, number of ICT trainings and number
of ICTs available significant at 1%, 5%
and 10% levels of significance. The study recommends that, government should
develop a mechanism to encourage agricultural extension agents to improve
access or ownership to ICT facilities for their professional as well as
Key Words: Factors, Influencing, e-Readiness, Agricultural Extension Agents
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