The Evolution of Agricultural Programs Towards Learning: A Look into Gender Disproportions in TVET Colleges

Ramongwane Daniel Sephokgole; Moses Makgato; Sammy Khoza

doi:10.36312/esaintika.v7i3.1175

Authors

Ramongwane Daniel Sephokgole Tshwane University of Technology https://orcid.org/0000-0002-3600-0411
Moses Makgato Tshwane University of Technology
Sammy Khoza Tshwane University of Technology https://orcid.org/0000-0003-1545-8148

DOI:

https://doi.org/10.36312/esaintika.v7i3.1175

Keywords:

Technical and vocational education and training (TVET) colleges, Agricultural programmes, Learning evolution, Gender disproportions

Abstract

The current training needs in agricultural program learning should contribute to the evolution of training in South African Technical and Vocational Education and Training (TVET) colleges. It is ironic that while other countries have advanced into a new era of educational innovation, the South African TVET colleges lag behind in technological development. The survey research approach allows for data measurements and statistical analysis. The study sought to determine whether the agricultural training in TVET colleges is evolving and progressing to integrate technology into the learning process. The three TVET college campuses with 482 participants were purposefully and conveniently sampled due to their experience in agricultural programmes. The findings were presented using the AVOVA analysis that is based on theory of technology integration. According to the study's findings, TVET colleges have evolved in how they train students in agricultural programmes. The study revealed that agriculture lecturers could use technological tools frequently when training the students. However, the results revealed that lack of learning resources affects the use of technology during agriculture training. The evolution would have been better if there had been an inclusion of phases such as technology integration exploration, experimentation with technology integration, technology integration adoption, and advanced technology integration. The study suggests that the gender factor should be considered as a barrier during the technological integration phases to accommodate all the students.

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References

Aina, A. Y., & Ogegbo, A. A. (2022). Investigating TVET college educators’ experiences while transitioning from the traditional classroom to the virtual classroom during the COVID-19 pandemic. Perspectives in Education, 40(1). https://doi.org/10.18820/2519593X/pie.v40.i1.8

Aini, Q., Budiarto, M., Putra, P. O. H., & Rahardja, U. (2020). Exploring E-learning Challenges During the Global COVID-19 Pandemic: A Review. Jurnal Sistem Informasi, 16(2), 47–65.

Aker, J. C. (2011). Dial “A” for agriculture: A review of information and communication technologies for agricultural extension in developing countries. Agricultural Economics, 42(6), 631–647. https://doi.org/10.1111/j.1574-0862.2011.00545.x

Alam, A. (2022). Educational Robotics and Computer Programming in Early Childhood Education: A Conceptual Framework for Assessing Elementary School Students’ Computational Thinking for Designing Powerful Educational Scenarios. 2022 International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN), 1–7. https://doi.org/10.1109/ICSTSN53084.2022.9761354

Almukhambetova, A., & Kuzhabekova, A. (2020). Factors affecting the decision of female students to enrol in undergraduate science, technology, engineering and mathematics majors in Kazakhstan. International Journal of Science Education, 42(6), 934–954. https://doi.org/10.1080/09500693.2020.1742948

Antony Jacob, M. S. J. (2012). The Genesis and Evolution of Community Colleges in Papua New Guinea. In A. W. Wiseman, A. Chase-Mayoral, T. Janis, & A. Sachdev (Eds.), International Perspectives on Education and Society (pp. 343–374). Emerald Group Publishing Limited. https://doi.org/10.1108/S1479-3679(2012)0000017017

Balsmeier, B., & Woerter, M. (2019). Is this time different? How digitalization influences job creation and destruction. Research Policy, 48(8), 103765. https://doi.org/10.1016/j.respol.2019.03.010

Bradford, J. S. (2016). College Choice: Perceptions of First-year Students in the College of Agricultural Sciences and Natural Resources at Oklahoma State University [Thesis, Oklahoma State University]. https://shareok.org/handle/11244/49049

Buabeng-Andoh, C. (2012). Factors Influencing Teachers’ Adoption and Integration of Information and Communication Technology into Teaching: A Review of the Literature. International Journal of Education and Development Using Information and Communication Technology, 8(1), 136–155.

Büyüköztürk, ?., Çakmak, E. K., Akgün, Ö. E., Karadeniz, ?., & Demirel, F. (2017). Bilimsel ara?t?rma yöntemleri [Scientific research methods] (23. bask?). Pegem Akademi.

Chang, V., Baudier, P., Zhang, H., Xu, Q., Zhang, J., & Arami, M. (2020). How Blockchain can impact financial services – The overview, challenges and recommendations from expert interviewees. Technological Forecasting and Social Change, 158, 120166. https://doi.org/10.1016/j.techfore.2020.120166

Chiloane, G., De Jager, T., & White, C. (2022). The Application of Technology-Assisted Teaching Methods by Engineering TVET College Lecturers to Promote Academic Success. The International Journal of Learning in Higher Education, 29(2), 55–70. https://doi.org/10.18848/2327-7955/CGP/v29i02/55-70

Chirumalla, K. (2021). Building digitally-enabled process innovation in the process industries: A dynamic capabilities approach. Technovation, 105, 102256. https://doi.org/10.1016/j.technovation.2021.102256

Cley, M. D., Warner, W. J., Stair, K. S., Flowers, J. L., & Croom, D. B. (2015). Technology Usage of Tennessee Agriculture Teachers. Journal of Agricultural Education, 56(3), 35–51. https://doi.org/10.5032/jae.2015.03035

Dakhi, O., Jama, J., Irfan, D., Ambiyar, A., & Ishak, I. (2020). Blended learning: A 21st century learning model at college. International Journal of Multi Science, 1(08), Article 08.

De Vera, J. L., Andrada, M. D., Bello, A., & De Vera, M. G. (2020). Teachers’ Competencies in Educational Technology Integration on Instructional Methodologies in the New Normal. Lukad: An Online Journal of Pedagogy, 1(08), 61–80.

Dlamini, M., Ngwenya, S., & Dlamini, B. (2004). Reasons Girls Choose Agriculture or Other Science and Technology Programs in Swaziland. Journal of International Agricultural and Extension Education, 11(3). https://doi.org/10.5191/jiaee.2004.11308

Downes, J. M., & Bishop, P. (2012). Educators Engage Digital Natives and Learn from Their Experiences with Technology: Integrating Technology Engages Students in Their Learning. Middle School Journal, 43(5), 6–15. https://doi.org/10.1080/00940771.2012.11461824

Freer, T. J. (2015). Modernizing the Agricultural Education and Training Curriculum (AID-OAA-L-12-00002; pp. 1–22). United States Agency for International Development (USAID). https://pdf.usaid.gov/pdf_docs/PBAAK865.pdf

García-Morales, V. J., Garrido-Moreno, A., & Martín-Rojas, R. (2021). The Transformation of Higher Education After the COVID Disruption: Emerging Challenges in an Online Learning Scenario. Frontiers in Psychology, 12, 616059. https://doi.org/10.3389/fpsyg.2021.616059

Goh, E., & Sigala, M. (2020). Integrating Information & Communication Technologies (ICT) into classroom instruction: Teaching tips for hospitality educators from a diffusion of innovation approach. Journal of Teaching in Travel & Tourism, 20(2), 156–165. https://doi.org/10.1080/15313220.2020.1740636

Green, J., & Thorogood, N. (2018). Qualitative methods for health research (4th edition). SAGE.

Henderson, M., Selwyn, N., & Aston, R. (2017). What works and why? Student perceptions of ‘useful’ digital technology in university teaching and learning. Studies in Higher Education, 42(8), 1567–1579. https://doi.org/10.1080/03075079.2015.1007946

Herren, C. D., Cartmell, D. D., & Robertson, J. T. (2011). Perceptions of Influence on College Choice by Students Enrolled in a College of Agricultural Sciences and Natural Resources. NACTA Journal, 55(3), 54–60.

Jung, J., Maeda, M., Chang, A., Bhandari, M., Ashapure, A., & Landivar-Bowles, J. (2021). The potential of remote sensing and artificial intelligence as tools to improve the resilience of agriculture production systems. Current Opinion in Biotechnology, 70, 15–22. https://doi.org/10.1016/j.copbio.2020.09.003

Jurgens, J. C. (2010). The Evolution of Community Colleges. College Student Affairs Journal, 28(2), 251–261.

Kotrlik, J. W., Redmann, D. H., & Douglas, B. B. (2003). Technology Integration By Agriscience Teachers In The Teaching/Learning Process. Journal of Agricultural Education, 44(3), 78–90. https://doi.org/10.5032/jae.2003.03078

Kpolovie, P. J., Joe, A. I., & Okoto, T. (2014). Academic Achievement Prediction: Role of Interest in Learning and Attitude towards School. International Journal of Humanities Social Sciences and Education, 1(11), 73–100.

Kwon, K., Ottenbreit-Leftwich, A. T., Sari, A. R., Khlaif, Z., Zhu, M., Nadir, H., & Gok, F. (2019). Teachers’ Self-efficacy Matters: Exploring the Integration of Mobile Computing Device in Middle Schools. TechTrends, 63(6), 682–692. https://doi.org/10.1007/s11528-019-00402-5

Li, S., Yamaguchi, S., Sukhbaatar, J., & Takada, J. (2019). The Influence of Teachers’ Professional Development Activities on the Factors Promoting ICT Integration in Primary Schools in Mongolia. Education Sciences, 9(2), 78. https://doi.org/10.3390/educsci9020078

Marczyk, G., DeMatteo, D., & Festinger, D. (2005). Essentials of research design and methodology (pp. xi, 290). John Wiley & Sons Inc.

McLaughlin, K. (2018). Kazakhstan Country Gender Assessment (0 ed.). Asian Development Bank. https://doi.org/10.22617/TCS179181

Meijer, S. S., Catacutan, D., Ajayi, O. C., Sileshi, G. W., & Nieuwenhuis, M. (2015). The role of knowledge, attitudes and perceptions in the uptake of agricultural and agroforestry innovations among smallholder farmers in sub-Saharan Africa. International Journal of Agricultural Sustainability, 13(1), 40–54. https://doi.org/10.1080/14735903.2014.912493

Moloi, T. S., & Salawu, M. K. (2022). Institutionalizing Technologies in South African Universities towards the Fourth Industrial Revolution. International Journal of Emerging Technologies in Learning (iJET), 17(03), 204–227. https://doi.org/10.3991/ijet.v17i03.25631

Mouritsen, M. L., Davis, J. T., & Jones, S. C. (2016). ANOVA Analysis of Student Daily Test Scores in Multi-Day Test Periods. Journal of Learning in Higher Education, 12(2), 73–82.

Mtshali, T. I., & Msimango, S. M. (2023). Factors Influencing Construction Technology Teachers’ Ability to Conduct Simulations Effectively. Jurnal Penelitian Dan Pengkajian Ilmu Pendidikan: E-Saintika, 7(1), Article 1. https://doi.org/10.36312/esaintika.v7i1.1079

Neuman, W. L. (2014). Social research methods: Qualitative and quantitative approaches (7. ed., Pearson new internat. ed). Pearson.

Pierpaoli, E., Carli, G., Pignatti, E., & Canavari, M. (2013). Drivers of Precision Agriculture Technologies Adoption: A Literature Review. Procedia Technology, 8, 61–69. https://doi.org/10.1016/j.protcy.2013.11.010

Raby, R. L., & Valeau, E. J. (2018). Community Colleges and Global Counterparts: Defining a Higher Educational Sector. In R. Latiner Raby & E. J. Valeau (Eds.), Handbook of Comparative Studies on Community Colleges and Global Counterparts (pp. 9–30). Springer International Publishing. https://doi.org/10.1007/978-3-319-50911-2_49

Ray, P. P. (2017). Internet of things for smart agriculture: Technologies, practices and future direction. Journal of Ambient Intelligence and Smart Environments, 9(4), 395–420. https://doi.org/10.3233/AIS-170440

Sarantakos, S. (2005). Social research (3rd ed). Palgrave Macmillan.

Singh, K., Peshin, R., & Saini, S. K. (2010). Evaluation of the agricultural vocational training programmes conducted by the Krishi Vigyan Kendras (Farm Science Centres) in Indian Punjab. Journal of Agriculture and Rural Development in the Tropics and Subtropics (JARTS), 111(2), Article 2.

Sokhulu, L. H. (2021). Students’ experiences of using digital technologies to address their personal research needs during the COVID-19 lockdown. African Identities, 19(4), 436–452. https://doi.org/10.1080/14725843.2020.1801384

Strong, R., Ho, S. P., Odom, S. F., & Irby, T. L. (2013). A Course Focused on the Critical Issues in Agriculture: Students’ Acceptance and Use of Mobile Learning. NACTA Journal, 57(4), 57–64.

Taimalu, M., & Luik, P. (2019). The impact of beliefs and knowledge on the integration of technology among teacher educators: A path analysis. Teaching and Teacher Education, 79, 101–110. https://doi.org/10.1016/j.tate.2018.12.012

Tian, H., Wang, T., Liu, Y., Qiao, X., & Li, Y. (2020). Computer vision technology in agricultural automation—A review. Information Processing in Agriculture, 7(1), 1–19. https://doi.org/10.1016/j.inpa.2019.09.006

Trukhachev, V., Bobrishev, A., Khokhlova, E., Ivashova, V., & Fedisko, O. (2019). Personnel training for the agricultural sector in terms of digital transformation of the economy: Trends, prospects and limitations. International Journal of Civil Engineering and Technology, 10(1), 2145–2155.

Vanclay, F., Baines, J. T., & Taylor, C. N. (2013). Principles for ethical research involving humans: Ethical professional practice in impact assessment Part I. Impact Assessment and Project Appraisal, 31(4), 243–253. https://doi.org/10.1080/14615517.2013.850307

Volery, T., & Lord, D. (2000). Critical success factors in online education. International Journal of Educational Management, 14(5), 216–223. https://doi.org/10.1108/09513540010344731

Zhang, L., Huang, Y., Yang, X., Yu, S., & Zhuang, F. (2022). An automatic short-answer grading model for semi-open-ended questions. Interactive Learning Environments, 30(1), 177–190. https://doi.org/10.1080/10494820.2019.1648300

Zinn, B., Raisch, K., & Reimann, J. (2019). Analysing training needs of TVET teachers in South Africa: An empirical study. International Journal for Research in Vocational Education and Training, 6(2), 174–197. https://doi.org/10.13152/IJRVET.6.2.4