DEMOGRAPHIC FACTORS AS CORRELATES OF E-LEARNING COMPETENCIES OF COMPUTER EDUCATION LECTURERS IN COLLEGES OF EDUCATION IN SOUTH-EAST, NIGERIA
Abstract
The purpose of this study was to determine this demographic factors as correlates of e-learning competencies of computer education lecturers in colleges of education. The study adopted correlational survey research design. The study was carried out in South-East geopolitical zone, Nigeria using government owned colleges of education in the state. The population for the study was thirty one (31) computer education lecturers/instructors from the three (3) government owned colleges of education in South-East, Nigeria. The entire population was studied due to the fact that it is manageable. Hence, total population sampling technique was used. The instrument that was used for the study was a structured questionnaire titled “Demographic factors as Correlates of e-Learning Competencies of Computer Education Lecturers (DCeCCEL) questionnaire”. The research instrument was subjected to face validation by three experts. Two experts in the Department of Computer & Robotics Education and one in the Department of Industrial Technical Education, all in Faculty of Vocational and Technical Education (VTE), University of Nigeria, Nsukka. The internal consistency of the questionnaire was determined using Cronbach Alpha reliability test which yielded co-efficient of 0.89. The instrument for data collection was administered by the researchers. The data collected was analyzed using Point Bi-serial Correlation. The null hypotheses were tested using Point Bi-serial correlation for hypotheses one to four and multiple regressions for hypothesis five at 0.05 level of significance. The findings from the study revealed a very weak relationship among age, marital status, gender, educational qualification and e-learning competencies of computer education lecturers’. In addition, the findings on hypothesis tested revealed that there was no significant difference among computer education lecturers’ age, marital status, gender, educational qualification and their e-learning competencies. It was therefore concluded that lecturers should always use e-learning resources for academics and research needs irrespective of any demographic factors
Keywords:
Demographic factors, E-learning, competencies, correlatesDownloads
Published
DOI:
https://doi.org/10.5281/zenodo.15356952Issue
Section
How to Cite
License
Copyright (c) 2025 Onyeidu S O, Ibezim N E, Asogwa U U
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
References
Abadina, F. O. and Mba, C. B. (2014). Influence of Socio economic and demographic factors on
reading attitude of primary school pupils in Ibadan. Journal of the Nigerian Library
Association, 47(12), 11- 25.
Agrawal, R. (2003). Social Intelligence and Teacher Effectiveness. Unpublished Doctoral Dissertation. Bundelkhand University.
Akinbote, O. (2001). The Nigerian Primary school teachers: Angels of instruction or devils of destruction? Nigerian Journal of Educational Philosophy, 7(1) 35-40.
Aninu, J. (2000). To catch up with the rest of the world Education Today. Journal of Science Teaching and Learning, 2(3), 2- 4.
Aminul, I. M., Rahim, N. A., Liang, T. C., and Momtaz, H. (2011). Effect of Demographic Factors on E-Learning Effectiveness in A Higher Learning Institution in Malaysia. International Education Studies. 4 (1), 112 – 118.
Bayraktar, S. (2002). A meta-analysis of the effectiveness of computer-assisted instruction in science education. Journal of Research on Technology in Education, 34, 173-188.
Beattie, J. C. (2001). Prohibiting marital status discrimination: A proposal for the protection of unmarried couples. Hastings Law Journal, 42, 1415–1453.
Bebell, D., and O'Dwyer, L. M. (2010). Educational outcomes and research from computing settings. Journal of Technology, Learning, and Assessment, 9 (1), 5-15.
Cavanaugh, C. S. (2001). The effectiveness of interactive distance education technologies in K–
12 learning: A meta-analysis. International Journal of Educational Telecommunications, 7, 73-88.
Charp, S. and Sylvia, P. (2003). Online learning in Virtual High School. International Journal of Instructional Media, 1, 8 - 10.
Cohen, V. L. (2001). Learning Styles in a Ninth-Grade High school Population. Journal of reaserch on Computing in Education, 33(4), 355 - 363.
Cohen, V. L. (2007). Learning styles in a technology rich environment. Journal of Research on Computing in Education, 1, 339-350
Cooper, K. C. (2000). Effective Competency Modeling and Reporting. New York: Amacom.
Delamare-Le-Deist, F. and Winterton, J. (2005). What is competence? Human Resource Development International, 8(1), 27- 46.
Dewar, T., and Whittington, D. (2000). Online learners and their learning strategies. Journal of Educational Computing Research, 23(4), 385–403.
Dormant, W. (2002). Evaluating E-learning Solution. Available from: http:/www.clomedia.com/content/templates/wp_clo_whitepaper.asp?articleid=36&zoneid=26.
Dur, R. E. (2005). An examination of readiness for self- directed learning and personnel variable at a large Midwestern electronics development and manufacturing corporation. (Doctoral dissertation, Florida Abstracts online. Dialog file number 35 Accession number 167625.
Ekundayo, O. S. (2010). Gender, marital status and religious affiliation as factors of assertiveness among Nigeria Education Majors. The Social Science, 5(6), 467- 470.
Federal Government of Nigeria (1988). Nigeria National Computer policy. Lagos : Nigerian tribune, April 11.
Fleischer, H. (2012). What is our current understanding of one-to-one computer projects: a systematic narrative research review. Educational Research Review, 7(1), 107-122.
Hall, B. and Snider, A. (2000). Glossary: The hottest buzz words in the industry. Journal of European Industrial Training, 20(5), 20-30.
Hassan, B. and Ogunkoya O. (2014). Demographic Variables and Job Performance: Any Link?
Acta Universitatis Danubius, 10(4), 1-8.
Ibezim, N. E. and Obi, C. A. (2011) Distributed Information Management in Federal Universities in Nigeria: Implications for Computer Education. International Journal of Educational Research (INJER), 11(1), 161-166.
Isaiah, O. & Ugboro, H. (2006). Organizational Commitment, Job Redesign, Employee Empowerment and Intent to Quit Among Survivors of Restructuring and Downsizing. IBAM. 232-257.
Ishaque, A., Rehman, S, U. Shareef, A. & Mahmood, A. (2010). Perceived leadership styles and organizational commitment. IJCRB. 4(1): 616-626.
Islahi, F. and Nasreen, A. (2013). Who Make Effective Teachers, Men or Women? An Indian Perspective. Universal Journal of Educational Research, 1(4), 285-293.
Jacob, F. J. and Tomoko, G. (2001). e-Education in Nigeria: Challenges and Prospects. Being text of a presentation at the 8th UN ICT Task Force Meeting. San Francisco, Ca:
Jossey-Bass.
Jegede, O. and Owolabi, J (2003). Computerization of Examination Results: A Case for Consideration in Colleges of Education. The Coll. Rev. 8, 151-158.
Kapp, K. M. (2003). Winning E-learning proposals: The Art of development and delivery. J. Ross publishing: New York.
Lucas, D. (2002). The scope of demography. Beginning Australian Population Studies. 34(2), 67 – 78.
McEvoy, G. M., and Cascio, W. F. (2007). Cumulative evidence of the relationship between employee age and job performance. Journal of Applied Psychology, 74, 11–17.
Mulder, M., Weigel, T., and Collins, K. (2006). The concept of competence concept in the development of vocational education and training in selected EU member states. A critical analysis. Journal of Vocational Education and Training, 59(1), 65-85.
Mungania, P. (2003). Seven E-learning barriers facing employees: Executive summary of dissertation. University of Louisville: US.
Nawaz, A. and Kundi, G. M. (2010). Demographic implications for the eLearning user perceptions in HEIs of NWFP, Pakistan. EJISDC. 41(5), 117.
Ng, T. W. H. and Feldman, D. C. (2009). How Broadly Does Education Contribute to Job Performance. Personnel Psychology, 62, 89–134.
Nwangwu, E. C. (2010). Challenges and New Responsibilities of Computer Education Teachers in Human Capital Development in Nigeria. Journal of Nigerian Educational Research Association, 15(1), 16-23.
Nwangwu, E. C. (2014). Video Editing and Production Skills Possessed by Computer Education Lecturers for Effective Instructional Delivery in Colleges ofEducation in South-East Zone of Nigeria. Computer Education Research Journal (CERJ), Vol. 1, 109-118.
OECD (Organisation for Economic Co-operation and Development). (2003). Key competencies for a successful life and well-functioning society. The definition and selection of key competencies: Executive summary. Summary of report by S.D. Rychen & L.H. Salganik (Eds.). Göttingen: Hogrefe and Huber Publishers. Retrieved from: www.oecd.org/dataoecd/47/61/35070367. pdf
Ogunkola, B. J. (2010). Students’ inherent characteristics, parents’ educational attainment and family size as predictor of academic achievement in integrated science. Research Journal of International Studies Issues, 16 (2), 11-19.
Ogwo, E., Onwe, C. E., and Maidoh, N. E. (2015). Problems Militating Against Computer Education and Its Effects on the Secondary School Curriculum in Umuahia North Local Government Area of Abia State, Nigeria. African Journal of Computing & ICT. 8(3), 2 – 7.
Ohanu, I. B. (2016). Demographic Variables as Correlates of Entrepreneurship intentions of electronic technology education students in Nigeria Universities. Unpublished Ph.D Thesis Department of Industrial Technical Education, University of Nigeria, Nsukka.
Okebukola, P. (2004). E-learning in varsities, others underway, NUC boss list strategies. The Guardian, 12th October, 2004. pgs 35,39.
Oyewole, G. O. and Popoola, S. O. (2015). Personal factors and work locus of control as
determinants of job performance of library personnel in Federal Colleges of Education
Nigeria. Retrieved from http://www.iclc.us/cliej/cl400p.
Palakurthi, M. A., and Parks, S.J. (2000).The effect of selected socio-demographic factors on
lodging demand in the U.S.A. International Journal of Contemporary Hospitality
manager. 12(2) 135-142.
Pellegrino, J. W., and Hilton, M. L. (Eds.). (2012). Education for life and work: Developing transferable knowledge and skills in the 21st century. National Research Council. Committee on Defining Deeper Learning and 21st Century Skills, Board on Testing and Assessment and Board on Science Education, Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press.
Popoola, S. O. and Akande, S. O. (2009).Demographic Variables aspiratory of library personnel’s perception of preservation of Information Resources in Nigeria Federal University Libraries. Gateway Library Journal. 12(2), 1-13.
Renwick, P. A., and Tosi, H. (2007). The effects of sex, marital status, and educational background on selection decisions. Academy of Management Journal, 21, 93–103.
Sarwar, A. and Azmat, A. (2013). Factors Having Impact on the Career Decisions: Study of Business Graduates in Pakistan. Business Management Dynamics, 2(7), 9 – 19.
Smolin, L. L and Lawless, K. A. (2003). Becoming literate in the technology age: New responsibilities and tools for teachers. Reading Teacher, 56, 570.
Tarus, J. K., Gichoya, D., & Muumbo, A. (2015). Challenges of implementing e-learning in Kenya: A case of Kenyan public universities. International Review of Research in Open and Distributed Learning, 16 (1), 120–141.
Tyagi, S. (2013). A Study of Teaching Effectiveness of Secondary School Teachers in Relation to their Demographic Characteristics, International Journal of Engineering and Innovative Technology (IJEIT), 3(1), 288-295.
Vijayalakshmi, G. (2002). Factors effecting teacher effectiveness. EduTracks 1(5), 35-38.
Zurita, G., and Nussbaum, M. (2004). Computer supported collaborative learning using wirelessly interconnected handheld computers. Computers & Education, 42 (1), 289-314
