Trends in Progression in Agriculture Career Among Students in Tertiary Institutions of Kakamega and Bungoma Counties, Kenya

Annah Nawambisa Manyasi; Stephen O. Odebero; Alice Chesambu Ndiema; James Bill Ouda

doi:10.51867/ajernet.4.2.86

Authors

Annah Nawambisa Manyasi PhD, AGED Student, Department of Agribusiness and Extension Management, School of Agriculture, Veterinary Science and Technology, Masinde Muliro University of Science and Technology, Kenya https://orcid.org/0000-0003-2081-6974
Stephen O. Odebero PhD, Professor, Department of Education Planning and Management, School of Education, Masinde Muliro University of Science and Technology, Kenya https://orcid.org/0000-0002-4063-5786
Alice Chesambu Ndiema PhD, AGED Student, Department of Agribusiness and Extension Management, School of Agriculture, Veterinary Science and Technology, Masinde Muliro University of Science and Technology, Kenya https://orcid.org/0000-0003-4153-5637
James Bill Ouda PhD, Senior Lecturer, Department of Education Psychology, School of Education, Masinde Muliro University of Science and Technology, Kenya https://orcid.org/0000-0002-0942-6169

DOI:

https://doi.org/10.51867/ajernet.4.2.86

Keywords:

Agriculture Career, Agriculture Program, Progression, Tertiary Institutions

Abstract

While agriculture is a major source of employment, it is notable that youths in developing countries are unemployed. In Kenya, agriculture is taught in the 8-4-4 syllabus and in the current competency-based curriculum. Despite the above facts, Kenya still requires human resources to drive the agricultural sector. The purpose of this study was to examine trends in progression in agriculture careers among students in tertiary institutions in Kakamega and Bungoma counties, Kenya, from 2016 to 2021. Correlational and cross-sectional research designs were used. Stratified random sampling was used to select agriculture students; purposive sampling was used to select universities, the Kenya Universities and Colleges Central Placement Service (KUCCPS), and technical and vocational education and training (TVET) institutions. Purposive sampling was used to select key informants, while quota sampling was employed to select focus group discussions. Using a pragmatic philosophical standing point as a lens, the study applied a mixed research strategy for data collection, coupled with mixed methods for triangulation. The sampling size was determined from Yamane (1967) formulae based on the study population. A sample size of (249) secondary school students, (24) university students, and (131) TVET institution students gives a sample size of 404 from a target population of 11928 students. A pilot study was done in Vihiga County. The data was collected using document content guides, questionnaires, focus group discussions, and interview guides. Due diligence was taken into consideration while collecting and processing the data to ensure both the reliability and validity of the study. Both descriptive and inferential techniques (trend analysis) were employed to analyze the data, which was presented using frequency tables and line graphs. The total KCSE agriculture enrolment in Kenya and total agriculture enrolment in TVET were strongly and positively correlated (r = 0.889, p = 0.018), and the average difference between the two was significant (t (5) = 18.978, p < 0.05). The total Kenya Certificate of Secondary Education (KCSE) agriculture enrolment in Bungoma and Bungoma agriculture progression to the universities in Kenya scores were weakly and positively correlated (r = 0.384, p = 0.453). while the average difference between the two is significant (t (5) = 14.095, p < 0.05). A weak but positive relationship existed between the total KCSE agriculture enrolment in Kakamega and the Kakamega agriculture progression to universities in Kenya scores (r = 0.154, p = 0.771). There is a significant difference between the two (t (5) = 17.825, p < 0.05). The results should inform policymakers and guide efforts toward the career progression of students in agriculture education.

References

Andre, L., Durksen, T., & Volman, M. L. (2017). Museums as avenues of learning for children: A decade of research. Learning Environments Research, 20, 47-76. https://doi.org/10.1007/s10984-016-9222-9 DOI: https://doi.org/10.1007/s10984-016-9222-9

Bloom, D., Finlay, J., Humair, S., Mason, A., Olaniyan, O., & Soyibo, A. (2010, June). Prospects for economic growth in Nigeria: A demographic perspective. In IUSSP Seminar on Demographics and Macroeconomic Performance. Paris, France.

Business Insider. (2013). College exposed: what majors are most popular, highest paying and most. Business Insider.

Chemjor, E. J. (2016). Factors influencing the choice of agriculture subject by boys and girls in public secondary schools in Kajiado county, Kenya (Doctoral dissertation, University of Nairobi).

Denzin, N. & Lincoln, Y. (2000). Handbook of qualitative research. London: SAGE.

Edziwa, X., & Blignaut, S. (2022). Graduate employability skills: the Voice of Agricultural Technical Vocational Education and Training (ATVET) students in Zimbabwe. South African Journal of Higher Education, 36(2), 99-114.

https://doi.org/10.20853/36-2-4501 DOI: https://doi.org/10.20853/36-2-4501

Ekwere U. E., (2014). Impact of Practical on Students' Choice of Agriculture Science in Secondary Schools in Abi Local Government Area of Cross Rive State. Seminar Paper submitted to the Department of Vocational and Special Education Faculty of Education University of Calabar. Nigeria

Garwe EC 2015: Trends in student enrolments in agricultural degree programmes in Zimbabwe. Global Journal of Educational Studies, 1(3), 45-49.

Jackson, D., & Wilton, N. (2017). Perceived employability among undergraduates and the importance of career self-management, work experience and individual characteristics. Higher Education Research & Development, 36(4), 747-762. https://doi.org/10.1080/07294360.2016.1229270 DOI: https://doi.org/10.1080/07294360.2016.1229270

Kazi, A. S., & Akhlaq, A. (2017). Factors affecting students' career choice. Journal of research and reflections in education, 2(2), 187-196.

Kennedy, U.O.J. (2011). Philosophical and sociological overview of vocational and technical education in Nigeria. American-Eurasian. Journal of Scientific Research, 6(1), 52-57.

Kenya National Qualifications Authourity. (2018). The Kenya National Qualifications Framework Handbook. https://www.knqa.go.ke/wp-content/uploads/2018/10/KNQF-Handbook-2018.pdf

KICD. (2021). Kenyan Curriculum Reviews. Nairobi: Jomo Kenyatta Foundations.

Kimberly, J. R., & Bouchikhi, H. (2016). Disruption on steroids: Sea change in the worlds of higher education in general and business education in particular. Journal of Leadership & Organizational Studies, 23(1), 5-12.

https://doi.org/10.1177/1548051815606434 DOI: https://doi.org/10.1177/1548051815606434

Kowalczyk, D, (2015). Descriptive Research Design: Definition, Examples & Types. Retrieved from http://study.com/academy/lesson/ descriptive-research-design- definition-examples-types.html. [Accessed: 4th December 2017].

Marcia, J. E. (1980). Identity in adolescence. In J. Adelson (Ed.), Handbook of Adolescent Psychology (pp. 109-137). Wiley.

Mberia, A., & Midigo, R. (2018). Understanding career choice dilemma in Kenya: Issues of informed choices and course availability. Journal of Education and Practice, 9(9), 35-40.

McLeod, S. (2018). Erik Erikson's Stages of Psychosocial Development. Retrieved from Simply Psychology: https://www.simplypsychology.org/Erik- Erikson.html

Muchiri J. M., Gilbert Abura Odilla G. A and Kathuri J. N., (2013). Students' Perception of Secondary School Agriculture: A Case of Meru Central District, Kenya. Asian Journal of Social Sciences & Humanities, 2(4), 129 -135.

Mugenda, A. G., & Mugenda, A. G. (2008). Social science research: Theory and principles. Nairobi: Acts Press.

National Science Board. (1998). Science and engineering indicators-1998. Arlington, VA: National Science

Obayelu,O. & Fadele,I.(2019).Choosing a career path in agriculture: A tough calling for youths in Ibadan metropolis, Nigeria. Agricultura Tropica et Subtropica,52(1) 27-37. https://doi.org/10.2478/ats-2019-0004

https://doi.org/10.2478/ats-2019-0004 DOI: https://doi.org/10.2478/ats-2019-0004

Ochuodho.J O., (2018), Status of the Higher Agricultural Education Sector in Kenya: A sector at crossroads. African Journal of Rural Development, 1(2), 171-178.

Olaitan S.O (2017). Policy initiatives for making agricultural education effective in the diversification of the economy of the nation. Journal of Agricultural Education Teacher's Association of Nigeria 1(1), 8-15.

Orodho, A.J., & Kombo, D.K. (2002). Research methods. Nairobi: Kenyatta University Institute of Open Learning.

Pelco, L. E., & Ball, C. T. (2018). Identity status, service-learning, and future plans. Journal of Higher Education and Engagement, 22(2), 103-125.

Porfeli, E. J., & Lee, B. (2012). Career development during childhood and adolescence. New Directions for Youth Development, 11-22. https://doi.org/10.1002/yd.20011 DOI: https://doi.org/10.1002/yd.20011

Praskova, A., Creed, P. A., & Hood, M. (2015). Career identity and the complex mediating relationships between career prepartory actions and career progress makers. Journal of Vocational Behavior, 145-153. https://doi.org/10.1016/j.jvb.2015.01.001 DOI: https://doi.org/10.1016/j.jvb.2015.01.001

Stitt, R. (2016). African American Women in STEM Fields. In C. Hudley (Ed.), Adolescent Identity and Schooling: Diverse Perspectives (pp. 107-122). New York: Routledge.

Sullivan, S. E., & Baruch, Y. (2009). Advances in career theory and research: A critical review and agenda for future exploration. Journal of management, 35(6), 1542-1571. https://doi.org/10.1177/0149206309350082 DOI: https://doi.org/10.1177/0149206309350082

Taber, K. S. (2018). The use of Cronbach's alpha when developing and reporting research instruments in science education. Research in science education, 48, 1273-1296. https://doi.org/10.1007/s11165-016-9602-2 DOI: https://doi.org/10.1007/s11165-016-9602-2

The Princeton Review. (2013). Top 10 college majors. The Princeton Review. https://www.princetonreview.com/college-advice/top-ten-college-majors

Tiraieyari, N., & Krauss, S. E. (2018). Predicting youth participation in urban agriculture in Malaysia: Insights from the theory of planned behavior and the functional approach to volunteer motivation. Agriculture and Human Values, 25(3), 637- 650. https://doi.org/10.1007/s10460-018-9854-8 DOI: https://doi.org/10.1007/s10460-018-9854-8

UNDP (2014). Assessing the socio-economic impacts of Ebola Virus Disease in Guinea, Liberia and Sierra Leone: The Road to Recovery. UNDP Africa Reports 267621, United Nations Development Programme (UNDP).World Bank, (2013). World Development Indicators: Participation in Education.

World Bank. (2012). World Development Report 2012: Gender Equality and Development. World Bank. http://hdl.handle.net/10986/4391

https://doi.org/10.1596/978-0-8213-9575-2 DOI: https://doi.org/10.1596/978-0-8213-9575-2