Evaluating Computer Science Education in Light of the Fourth Industrial Revolution: Current Reality, Challenges, and Future Prospects

Authors

  • Halah Muayad Albarodi Department of Computer Science, College of Education for Pure Science, University of Mosul, Mosul, Iraq. .

DOI:

https://doi.org/10.31185/bsj.Vol21.Iss37.1137

Keywords:

Technology Acceptance in Iraq (TAM/UTAUT); 4IR Technology Adoption; Digital Education Readiness in Iraq

Abstract

The Fourth Industrial Revolution (4IR) introduces transformative technologies such as artificial intelligence (AI), the Internet of Things (IoT), cloud computing, and big data analytics, profoundly reshaping educational systems worldwide. In Iraq, systemic challenges, including outdated infrastructure and limited resources, hinder the integration of 4IR technologies in computer science education. This study evaluates the readiness of Iraqi computer science educators to adopt these technologies, employing the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) as theoretical frameworks. A comprehensive 31-item survey, comprising 28 closed-ended and 3 open-ended questions, was rigorously validated by experts and demonstrated acceptable reliability (Cronbach’s Alpha≈ 0.75 for closed-ended items). The survey was administered to 105 educators across Iraqi universities, with responses scored on a scale yielding a maximum of 95 points per participant. Findings reveal a high level of awareness (65% fully understand 4IR concepts) and strong intentions to adopt 4IR tools (70%), driven by robust perceived usefulness and ease of use (TAM) and performance and effort expectancy (UTAUT). However, adoption is curtailed by significant barriers, including inadequate infrastructure (70%), poor internet connectivity (75%), and insufficient technical support (68%). Statistical analyses, including Chi-Square tests and Spearman correlations, elucidate demographic influences and systemic constraints. The study underscores the urgent need for investments in digital infrastructure, professional development programs, and curriculum reforms to align Iraqi computer science education with 4IR demands. Recommendations include enhancing digital facilities, fostering peer collaboration, and updating curricula to incorporate AI and data science. Future research will expand to longitudinal studies, integrate qualitative methods, and explore policy impacts to inform educational strategies in Iraq and similar developing nations.

References

1. بعضي آسيا. (2022). الثورة الصناعية الرابعة. مجلة الاقتصاد والتنمية المستدامة، 5(2), 561-577.

2. Al-Azawei, A., P. Parslow, and K. Lundqvist. 2016. “Barriers to E-Learning in Iraq.” Journal of Education and Practice 7(15):132–38.

3. Alenezi, A. 2021. “Factors Affecting the Adoption of E-Learning in Higher Education.” Education and Information Technologies 26: 413-28.

4. Al-Gahtani, S. S., G. S. Hubona, and J. Wang. 2007. “The Acceptance of E-Learning in Saudi Arabia.” Journal of Computer Information Systems 48(2):73–82.

5. Almaiah, M. A., Al-Khasawneh, A., & Althunibat, A. (2020). Exploring the critical challenges and factors influencing the E-learning system usage during COVID-19 pandemic. Education and information technologies, 25(6), 5261-5280.‏

6. Al-Nuaimi, M., and M. Al-Emran. 2021. “Adoption of E-Learning in Iraqi Universities.” Technology, Knowledge and Learning 26:1–20.

7. Al-Rahmi, W. M., N. Yahaya, and M. M. Alamri. 2019. “Integrating Technology Acceptance Model with Innovation Diffusion Theory.” Sustainability 11(8):2239.

8. Ameen, N., Willis, R., Abdullah, M. N., & Shah, M. (2019). Towards the successful integration of e‐learning systems in higher education in Iraq: A student perspective. British Journal of Educational Technology, 50(3), 1434-1446.‏

9. Chen, L., P. Chen, and Z. Lin. 2020. “Artificial Intelligence in Education: A Review.” IEEE Access 8:75264–78.

10. Davis, F. D. 1989. “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology.” MIS Quarterly 13(3):319–40.

11. Kassab, M., DeFranco, J., & Laplante, P. (2020). A systematic literature review on Internet of things in education: Benefits and challenges. Journal of computer Assisted learning, 36(2), 115-127.

12. Kline, R. B. (2023). Principles and practice of structural equation modeling. Guilford publications.‏

13. Teo, T. 2011. “Factors Influencing Teachers’ Intention to Use Technology.” Computers & Education 56(3):711–21.

14. Venkatesh, V., M. G. Morris, G. B. Davis, and F. D. Davis. 2003. “User Acceptance of Information Technology: Toward a Unified View.” MIS Quarterly 27(3):425–78.

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Published

2026-03-01

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