Perceived Determinants of Lecturers’ Adoption of Electronic Supervision for Agricultural Education Students' Research Projects in Universities in Southeast Nigeria
Abstract
This study identified the perceived determinants of e-supervision adoption for Agricultural Education students' research projects by lecturers in public universities in Southeast Nigeria. It was guided by four research questions with corresponding research questions. A descriptive survey research design was adopted. The population of the study was 45 lecturers of Agricultural Education in six public Universities in Southeast Nigeria. A census approach was adopted, hence there was no sampling. The instrument for data collection was a structured questionnaire. The questionnaire was validated by 5 experts and pilot-tested tested. Analysis of data from the pilot study indicated good reliability with a Cronbach’s alpha coefficient of 0.82. Data was collected from an online questionnaire designed using a Google form. A total of 38 valid responses were recorded, resulting in an 84.44% survey response rate. Data collected was analyzed using descriptive statistics such as mean and standard deviation. Findings revealed that the adoption of e-supervision for Agricultural Education research projects in universities is determined by some individual, technological, organizational, and environmental factors. Some key individual determinants found included ICT competence, interest, familiarity with digital tools, and prior experience. Technological factors found included perceived ease of use, system quality, and infrastructure, which were significant. In contrast, organizational factors like capacity-building initiatives, administrative support, and compatibility with existing academic structures played essential roles. Environmental factors, including power supply, financial considerations, and competitive pressure from colleagues, also influenced adoption. The researchers concluded that there is a need to invest in robust ICT infrastructure, provide ongoing training, and create conducive environments to encourage lecturers of Agricultural Education to adopt e-supervision. It was recommended among others that administrators and agencies of government in charge of the Universities in Southeast Nigeria should organize structured capacity-building programmes and develop user-friendly e-supervision systems.
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Ansong, E., Lovia Boateng, S., Boateng, R. & John E. (2017). Determinants of e-learning adoption in Universities: Evidence from a developing country. Journal of Educational Technology Systems, 46(1), 30-60.
Awodiji, O., Ayanwale, M., & Oyedoyin, M. (2022). Availability and utilisation of e-supervision for instruction facilities in the post-covid-19 era. E-Journal of Humanities Arts and Social Sciences, 126-139. https://doi.org/10.38159/ehass.2022sp31112
Bonett, D. G., & Wright, T. A. (2015). Cronbach's alpha reliability: Interval estimation, hypothesis testing, and sample size planning. Journal of organizational behavior, 36(1), 3-15.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
Djatmika, D., Prihandoko, L. A., & Nurkamto, J. (2022). Lecturer Supervisors’ Perspectives on Challenges in Online Thesis Supervision. In 67th TEFLIN International Virtual Conference & the 9th ICOELT 2021 (TEFLIN ICOELT 2021) (pp. 270-276). Atlantis Press. https://doi.org/10.2991/assehr.k.220201.048
Ezeugo, N. C., Metu, I. C., Eleje, L. I., Gertrude, N., Achebe, O., & Anachunam, C. (2022). Lecturers’ Acceptance and use of ICT for the Sustenance of Research Supervision Amidst Covid-19 Pandemic.
Grant, K., Hackney, R., & Edgar, D. (2014). Postgraduate research supervision: An'agreed'conceptual view of good practice through derived metaphors. International Journal of Doctoral Studies, 9, 43-60.
Hadullo, K., Oboko, R., & Omwenga, E. (2018). Status of e-learning quality in kenya: case of jomo kenyatta university of agriculture and technology postgraduate students. The International Review of Research in Open and Distributed Learning, 19(1). https://doi.org/10.19173/irrodl.v19i1.3322
Imperial College (2014). A practical guide to managing student projects. https://www.imperial.ac.uk/staff/educational-development/workshops/by-request/managing-student-projects/
Mbazu, E. C., Oladokun, B. D., & Mohammed, J. D. (2023). Awareness, Adoption and Perception of Lecturers toward the Use of Information and Communication Technology (ICT) in Nigeria. Howard Journal of Communications, 1-17.
Moakofhi, M., Phiri, T., Leteane, O., & Bangomwa, E. (2019). Using technology acceptance model to predict Lecturers’ acceptance of moodle: case of botswana university of agriculture and natural resources. Literacy Information and Computer Education Journal, 10(1), 3103-3113. https://doi.org/10.20533/licej.2040.2589.2019.0407
Onah, O., Ekenta, L. U., Gideon, N. M., Onah, E. N., & Obe, P. I. (2024). Examination of Innovative Educational Technologies for Electronic supervision for Postgraduate Research Projects in Nigerian Universities. International Journal of Agricultural Education & Research, 2 (1) 50, 61(50), 2.
Opoku, D. (2020). Determinants of e-learning system adoption among Ghanaian university Lecturers: An application of information system success and technology acceptance models. American Journal of Social Sciences and Humanities, 5(1), 151-168.
Osiesi, M., Azeez, F., Adeniran, S., Akomolafe, O., Obateru, O., Oke, C., … & Nwogu, G. (2023). Exploring the perceptions and experiences of university Lecturers on corrective feedback in students' research project supervision: a case for computer-mediated mode. Journal of Applied Research in Higher Education, 15(5), 1253-1275. https://doi.org/10.1108/jarhe-08-2022-0273
Rahmat, B. (2022). Principal challenges in implementing instructional supervision during the transition to the new normal. Jurnal Kepemimpinan Dan Pengurusan Sekolah, 7(3), 297-304. https://doi.org/10.34125/kp.v7i3.794
Raphael, C. and Mtebe, J. (2017). Pre-service teachers’ self-efficacy beliefs towards educational technologies integration in Tanzania. Journal of Learning for Development, 4(2). https://doi.org/10.56059/jl4d.v4i2.190
Tornatzky, L. G., & Fleischer, M. (1990). The Processes of Technological Innovation. Massachusetts: Lexington Books.
Vaiz, O., Minalay, H., Türe, A., Ülgener, P., Yaşar, H., & Bilir, A. M. (2021). The supervision in distance education: E-Supervision. The Online Journal of New Horizons in Education, 11(3), 137-140.
Vance, G., Burford, B., Shapiro, E., & Price, R. (2017). Longitudinal evaluation of a pilot e-portfolio-based supervision programmeme for final year medical students: views of students, supervisors and new graduates. BMC Medical Education, 17(1). https://doi.org/10.1186/s12909-017-0981-5
Wahyudi, J. (2023). The acceptance of a smartphone application for disaster: technology acceptance model approach. Iop Conference Series Earth and Environmental Science, 1180(1), 012002. https://doi.org/10.1088/1755-1315/1180/1/012002
Wu, Y. and Xu, J. (2022), “The application of computer-assisted corrective feedback in Chinese learning environment”, Academic Journal of Computing and Information Science, 5(6), 74-82, doi: 10.25236/AJCIS.2022.050611.
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