A Theory of Planned Behaviour-Based Analysis of IT Specialisation Choices in a South African Historically Disadvantaged Institution

Nqobile Thobile Mpulo, Khumbuzile Mzobe, Zinhle Mkhize, Kudakwashe Maguraushe

Abstract

Decisions to specialise in Information Technology (IT)-based courses have notably gained prominence in shaping academic pathways among students, more specifically within historically disadvantaged institutions (HDIs) within South Africa, influenced by persistent socio-economic factors. While research has examined factors influencing career decisions, including specialisation decisions, in IT, there has been minimal use of theory-based frameworks, particularly within resource-constrained contexts of higher education. In this regard, this research aims to investigate the factors influencing IT students' specialisation decisions at a historically disadvantaged institution in South Africa, applying the Theory of Planned Behaviour as the framework for this inquiry. The research employed a cross-sectional design and was conducted among 104 second- or third-year Information Technology students recruited through stratified random sampling. The research findings revealed that attitudes toward IT specialisation decisions have had the greatest influence, relative to subjective norms, while perceived behaviour control has had relatively less influence. Overall, 34.1% of the variation in specialisation decisions was accounted for in the study. As this study draws on the Theory of Planned Behaviour to examine specialisation decisions in IT at historically disadvantaged institutions in South Africa, it aims to make a relevant contribution within the field of informatics education.

Keywords

Informatics Education; Historically Disadvantaged Institutions; HDIs; IT Specialisation Choice; Student Career Decision-Making; Theory of Planned Behavior

Full Text:

PDF

References

Ajzen, I. (2002). Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. Journal of Applied Social Psychology, 32(4), 665–683. https://doi.org/10.1111/j.1559-1816.2002.tb00236.x

Ajzen, I. (2020). The theory of planned behavior: Frequently asked questions. Human Behavior and Emerging Technologies, 2(4), 314–324. https://doi.org/10.1002/hbe2.195

Brown, S. D., & Lent, R. W. (2019). Social cognitive career theory at 25: Progress in studying the domain, satisfaction, and career self-management models. Journal of Vocational Behavior, 115, 103316. https://doi.org/10.1016/j.jvb.2019.06.004

Cardador, M. T., Jensen, K. J., Lopez-Alvarez, G., & Cross, K. J. (2024). An analysis of factors influencing intra-major specialization choice among second-year women engineering students. Journal of Women and Minorities in Science and Engineering, 30(2), 1–34. https://doi.org/10.1615/JWomenMinorScienEng.2022042788

Eccles, J. S., & Wigfield, A. (2020). From expectancy-value theory to situated expectancy-value theory. Contemporary Educational Psychology, 61, 101859. https://doi.org/10.1016/j.cedpsych.2020.101859

Gieure, C., Benavides-Espinosa, M. M., & Roig-Dobón, S. (2020). The entrepreneurial process: The link between intentions and behavior. Journal of Business Research, 112, 541–548. https://doi.org/10.1016/j.jbusres.2019.11.088

Jonck, P., & Swanepoel, E. (2019). Investigating career guidance implementation between historically advantaged and disadvantaged schools. The Journal for Transdisciplinary Research in Southern Africa, 15(1), a637.
https://doi.org/10.4102/td.v15i1.637

Khir, N. H. M., Mahmud, Z. S., Aziz, S. S. A., Shah, M. S. Z. O., & Zakaria, N. A. (2023). Factors of decision-making in science stream course in higher learning education. International Journal of Academic Research in Progressive Education and Development, 12(1), 1–10. https://doi.org/10.6007/IJARPED/v12-i1/16092

König, S., & Freitas, L. B. (2023). Stereotype threat in learning situations? An investigation of vocabulary learning in language minority students. European Journal of Psychology of Education. https://doi.org/10.1007/s10212-022-00618-9

Kortak, M. E. (2018). Factors that influence university students’ program choices: The case of IBSU, Tbilisi, Georgia. Journal of Education in Black Sea Region, 4(1), 93–107. https://doi.org/10.31578/jebs.v4i1.157

La Barbera, F., & Ajzen, I. (2020). Control interactions in the theory of planned behavior: Rethinking the role of subjective norm. Europe’s Journal of Psychology, 16(3), 401–417. https://doi.org/10.5964/ejop.v16i3.2056

Levaillant, M., Levaillant, L., Lerolle, N., Vallet, B., & Hamel-Broza, J.-F. (2020). Factors influencing medical students’ choice of specialization: A gender-based systematic review. EClinicalMedicine, 28, Article 100589. https://doi.org/10.1016/j.eclinm.2020.100589

Mahmud, A., Akter, M. N., Ashrafuzzaman, M., & Nipa, S. A. (2023). Factors affecting accounting students’ perceptions of the public accounting profession in Bangladesh. European Journal of Accounting, Auditing and Finance Research, 11(9), 58–84. https://doi.org/10.37745/ejaafr.2013/vol11n95884

Miller, I., Lopez-Alvarez, G., Cardador, M. T., & Jensen, K. J. (2024). Determinants of intra-major specialization and career decisions among undergraduate biomedical engineering students. Biomedical Engineering Education, 4, 305–318. https://doi.org/10.1007/s43683-023-00133-3

Mutanga, M. B., Piyose, P. X., & Ndovela, S. L. (2023). Factors affecting career preferences and pathways: Insights from IT students. Journal of Information Systems and Informatics, 5(3), 1111–1122. https://doi.org/10.51519/journalisi.v5i3.556

Ndovela, S. L., & Mutanga, B. M. (2024). Academic factors influencing students’ career choices in the IT field: Insights from South African IT students. Indonesian Journal of Information Systems, 6(2), 107–116. https://doi.org/10.24002/ijis.v6i2.8293

Pillay, A. L. (2020). Prioritising career guidance and development services in post-apartheid South Africa. African Journal of Career Development, 2(1), a9. https://doi.org/10.4102/ajcd.v2i1.9

Queirós, A., Faria, D., & Almeida, F. (2017). Strengths and limitations of qualitative and quantitative research methods. European Journal of Education Studies, 3(9), 369–387. https://doi.org/10.5281/zenodo.887089

Redmond, F. (2022). With a rise in computing disciplines comes a greater choice of computing degrees in higher education. Proceedings of the 22nd Koli Calling International Conference on Computing Education Research (Koli Calling 2022), 1–11. https://doi.org/10.1145/3564721.3565946

Sarikhani, Y., Ghahramani, S., Bayati, M., Lotfi, F., & Bastani, P. (2021). A thematic network for factors affecting the choice of specialty education by medical students: A scoping study in low and middle income countries. BMC Medical Education, 21, Article 99. https://doi.org/10.1186/s12909-021-02539-5

Struminskaya, B., & Gummer, T. (2021). Risk of nonresponse bias and the length of the field period in a mixed-mode general population panel. Journal of Survey Statistics and Methodology, 10(1), 161–182.
https://doi.org/10.1093/jssam/smab011

Sumo, D. Z., Zhang, L., & Davis Sumo, P. (2023). Career choice for ICT among Liberian students: Insights into career motivations, job security, and job availability. Heliyon, 9, e16445. https://doi.org/10.1016/j.heliyon.2023.e16445

Thiem, K. C., & Dasgupta, N. (2022). From pre-college to career: Barriers facing historically marginalized students and evidence-based solutions. Social Issues and Policy Review, 16(1), 212–251. https://doi.org/10.1111/sipr.12085

Young, D. K., Carpenter, D., & Maasberg, M. (2018). An examination of factors that influence students’ IT career decisions. Journal of Computer Information Systems, 58(3), 253–263. https://doi.org/10.1080/08874417.2016.1235473