Reclaiming Cognitive Skills in Electrical Technology: Addressing AI Dependence in South African Technical Schools

  • Nzaliseko Dayi Department of Technology and Vocational Education, Faculty of Humanities, Tshwane University of technology, South Africa
  • Mshali Thokozani Isaac Department of Technology and Vocational Education, Faculty of Humanities, Tshwane University of technology, South Africa
Keywords: Artificial intelligence, Cognitive skills, Electrical technology, Practical Assessment Task (PAT), Technical education

Abstract

This study investigated the growing dependence on artificial intelligence (AI) tools among learners studying electrical technology in South African technical schools and its influence on cognitive and critical thinking skills. The purpose of this study was to examine how excessive dependence on AI affects learners’ problem-solving skills and practical competence, which are important for meeting the demands of the Electrical Technology curriculum and the broader technical industry in South Africa. A quantitative research approach was adopted using a descriptive survey design. Simple random sampling was used to select 120 electrical technology learners from four technical high schools across Gauteng Province, South Africa. The data were collected using structured questionnaires and online surveys focusing on learners’ use of AI, engagement in problem-solving, and performance in Electrical Technology Practical Assessment Tasks (PATs). Furthermore, this data was analyzed using descriptive and inferential statistics. Findings revealed that the majority of learners mostly relied on AI to complete written tasks and PATs, resulting in reduced critical thinking, limited conceptual understanding of electrical concepts, and poor practical performance. The study recommends the integration of digital ethics, guided AI use, and cognitive-based teaching strategies to foster independent reasoning and ensure learners acquire practical skills aligned with industry expectations.

Downloads

Download data is not yet available.

Author Biography

Mshali Thokozani Isaac, Department of Technology and Vocational Education, Faculty of Humanities, Tshwane University of technology, South Africa

Departent of Technology and Vocational Education: Senior Lecturer 

References

Aymen, D., & Zakarya, B. (2024). The influence of artificial intelligence on students' critical thinking (Center of Abdelhafid Boussouf-Mila). https://theses-algerie.com/2843586674412184/memoire-de-master/centre-universitaire-abdel-hafid-boussouf---mila/www.centre-univ-mila.dz/?lang=en

Buddhadev, S. S. (2025). Skill-based learning in the 21st century: The future of education. TMP Universal Journal of Law, Business, and Management, 1(1). https://doi.org/10.69557/ebg8jq83

Burger, Y., & van Zyl, R. (2020). Resilient transformation of studio-based teaching and learning in creative and design disciplines towards cognitive apprenticeship. In Proceedings of the Asian Association of Schools of Business International Conference 2020. https://doi.org/10.29086/978-0-9869936-5-7/2020/AASBS04

Challoumis, C. (2024). The imperative of skill development in an AI revolution. In Proceedings of the XIX International Scientific Conference (132–168). https://www.researchgate.net/profile/Constantinos-Challoumis-Konstantinos-Challoumes/publication/387399165

Cherki El Idrissi, S. (2025). Enhancing or hindering? The influence of generative AI on critical thinking and collaborative learning. https://aisel.aisnet.org/amcis2025/is_education/is_education/34

Silva, A. F. A. da. (2024). Critical thinking and artificial intelligence in education (Universidade NOVA de Lisboa). NOVA Research Portal. http://hdl.handle.net/10362/174680

Dayi, N., Mtshali, T. I., & Sephokgole, R. D. (2026). Evaluating the GET electrical technology syllabus for transition into FET specialisations in Gauteng technical schools. Jurnal Inovasi Teknologi Pendidikan, 13(1), 70–81. https://doi.org/10.21831/jitp.v13i1.90695

Department of Higher Education and Training. (2022). Curriculum and assessment policy statement (CAPS): Electrical technology. Government Printer.

Dzhumatovich, A. S., & Salimrouhi, E. (2025). Simulation-based education as a tool for enhancing the quality of medical education. Journal of Preventive and Complementary Medicine, 4(1), 45–59. https://doi.org/10.22034/jpcm.2025.511432.1214

George, A. S., Baskar, T., & Srikaanth, P. B. (2024). The erosion of cognitive skills in the technological age: How reliance on technology impacts critical thinking, problem-solving, and creativity. Partners Universal Innovative Research Publication, 2(3), 147–163. https://doi.org/10.5281/zenodo.11671150

Ghosh, L., & Ravichandran, R. (2024). Journal of Digital Learning and Education, 4(1), 41–49. http://journal.moripublishing.com/index.php/jdle

Guo, Y., & Wang, Y. (2025). Exploring the effects of artificial intelligence application on EFL students' academic engagement and emotional experiences: A mixed-methods study. European Journal of Education, 60(1), e12812. https://doi.org/10.1111/ejed.12812

Hernandez-de-Menendez, M., Escobar Díaz, C. A., & Morales-Menendez, R. (2020). Engineering education for smart 4.0 technology: A review. International Journal on Interactive Design and Manufacturing, 14(3), 789–803. https://doi.org/10.1007/s12008-020-00672-x

Hosseini, M., Horbach, S. P., Holmes, K., & Ross-Hellauer, T. (2025). Open science at the generative AI turn: An exploratory analysis of challenges and opportunities. Quantitative Science Studies, 6, 22–45. https://doi.org/10.1111/bjet.13334

Huang, F. (2025). Exploring a new model of undergraduate vocational education. Vocation, Technology & Education, 2(1). https://doi.org/10.54844/vte.2025.0869

Jain, V., & Mitra, A. (2025). Bridging the digital literacy gap: Effective collaboration between institutes of higher education and the workforce for technology integration. In Institutes of Higher Education (IHE) and Workforce Collaboration for Digital Literacy (71–90). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3373-0004-7.ch003

Jia, X. H., & Tu, J. C. (2024). Towards a new conceptual model of AI-enhanced learning for college students: The roles of artificial intelligence capabilities, general self-efficacy, learning motivation, and critical thinking awareness. Systems, 12(3), Article 74. https://doi.org/10.3390/systems12030074

Khlaif, Z. N., Alkouk, W. A., Salama, N., & Abu Eideh, B. (2025). Redesigning assessments for AI-enhanced learning: A framework for educators in the generative AI era. Education Sciences, 15(2), Article 174. https://doi.org/10.3390/educsci15020174

Kovalchuk, V., Maslich, S. V., Tkachenko, N. M., Shevchuk, S. S., & Shchypska, T. P. (2022). Vocational education in the context of modern problems and challenges. Journal of Curriculum and Teaching, 11(8), 329–338. https://doi.org/10.5430/jct.v11n8p329

Lestari, N., Winarsih, M., & Kusumawardani, D. (2023). The use of meaningful learning in distance learning. JTP: Jurnal Teknologi Pendidikan, 25(1), 42–53. https://doi.org/10.21009/jtp.v25i1.33701

Levin, I., Marom, M., & Kojukhov, A. (2025). Rethinking AI in education: Highlighting the metacognitive challenge. BRAIN: Broad Research in Artificial Intelligence and Neuroscience, 16(1, Suppl. 1), 250–263. https://doi.org/10.70594/brain/16.S1/21

Mattsson, S., Fast-Berglund, Å., Li, D., & Thorvald, P. (2020). Forming a cognitive automation strategy for Operator 4.0 in complex assembly. Computers & Industrial Engineering, 139, Article 105360. https://doi.org/10.1016/j.cie.2018.08.011

Mishra, M., Gorakhnath, I., Lata, P., Rani, R., & Chopra, P. (2022). Integration of technological pedagogical content knowledge (TPACK) in classrooms through a teacher's lens. International Journal of Health Sciences, 6(Suppl. 3), 12505–12512. https://doi.org/10.53730/ijhs.v6nS3.9536

Mohajan, H. K. (2020). Quantitative research: A successful investigation in natural and social sciences. Journal of Economic Development, Environment and People, 9(4), 50–79. https://doi.org/10.26458/jedep.v9i4.679

Novikov, P., & Kiseleva, A. (2024). Over-reliance on technology in foreign language learning: Case study of LLB undergraduates. In INTED2024 Proceedings (2962–2966). IATED. https://doi.org/10.21125/inted.2024.0803

Peter, O. I., Gabraiel, A. B., & Johnson, O. O. (2020). Gender differences in achievement, interest and retention of students exposed to fabrication and welding engineering craft practice through cognitive apprenticeship instructional technique in Nigeria. Educational Research and Reviews, 15(4), 194–202. http://files.eric.ed.gov/fulltext/EJ1252708.pdf

Revesai, Z. (2025). Generative AI dependency: The emerging academic crisis and its impact on student performance—A case study of a university in Zimbabwe. Cogent Education, 12(1), Article 2549787. https://doi.org/10.1080/2331186X.2025.2549787

White, S. K. (2025). Reverse engineering the K–12 science education experience through integrated STEM curriculum design (Doctoral dissertation, Purdue University).

Wu, R., & Yu, Z. (2024). Do AI chatbots improve students' learning outcomes? Evidence from a meta-analysis. British Journal of Educational Technology, 55(1), 10–33. https://doi.org/10.1111/bjet.13334

Yavich, R. (2025). Will the use of AI undermine students' independent thinking? Education Sciences, 15(6), Article 669. https://doi.org/10.3390/educsci15060669

Published
2026-07-29
How to Cite
Dayi, N., & Isaac, M. T. (2026). Reclaiming Cognitive Skills in Electrical Technology: Addressing AI Dependence in South African Technical Schools. Studies in Learning and Teaching, 7(2). https://doi.org/10.46627/silet.v7i2.867
Abstract viewed = 37 times