Towards the transformation of Communication Networks curriculum and assessment using Artificial Intelligence in a Higher Education setting

Towards the transformation of Communication Networks curriculum and assessment using Artificial Intelligence in a Higher Education setting

Dina Moloja & Elisha Markus

Issue: Vol. 7 No. 2 2026 Article 14 pp.216 -229
DOI : https://doi.org/10.38159/jelt.20267214 Published online 12th March 2026.

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ABSTRACT

The rapid advancement of Artificial Intelligence (AI) is transforming higher education and giving rise to new approaches to teaching complex modules such as Communication Networks. Therefore, traditional lecture-based methods and fixed assessments are increasingly misaligned with the digital era’s demand for flexible, skills-driven, and technologically adept graduates. This study explored the efficacy of integrating AI into teaching, learning, and assessment for a third-year Communication Networks module, with the broader goal of enhancing student engagement, critical thinking, and problem-solving skills. A conceptual qualitative methodology was employed, drawing on contemporary literature, expert opinion, and existing AI-driven education models. Anchored on constructivist learning theory, the study prioritizes student-centred learning and the active construction of knowledge. The analysis focuses on AI’s potential to support personalised learning pathways and more responsive teaching practices. The findings indicate that Intelligent Tutoring Systems, adaptive assessments, and data-driven learning dashboards offer substantial opportunities to improve learning experiences. These tools enable personalised instruction, provide instant feedback, and automate routine grading tasks, while identifying student learning gaps early. Recommendations include integrating these AI tools into Communication Networks curricula, ensuring staff training, and establishing ongoing evaluation mechanisms. This paper contributes to the scholarship of teaching and learning by presenting a theoretically grounded and practically applicable framework for AI integration in higher education. It demonstrates how AI can bridge the gap between traditional academic approaches and the evolving demands of the workplace, ultimately preparing graduates for a technologically advanced future.

Keywords: Artificial Intelligence, Communication Networks, Constructivist Pedagogy, Curriculum Transformation, Higher Education

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AUTHOR(S)

Dina Moloja serves as a Lecturer and Executive Coordinator for Community Engagement in the Department of Information Technology at the Central University of Technology. Beyond her formal roles, she is deeply passionate about research and knowledge creation. Her scholarly interests span across emerging and impactful fields such as Cloud Computing, Artificial Intelligence, Cybersecurity, Mobile Technologies, and the integration of Technology in Education. Over the years, she has actively contributed to the academic community by sharing her insights and findings at both national and international conferences. In addition to presenting her own work, she has also taken on leadership responsibilities such as chairing sessions, demonstrating her commitment not only to advancing research but also to fostering dialogue and collaboration among peers. Through her work, Dina strives to bridge the gap between technology, education, and community development, ensuring that her contributions extend beyond academia and into meaningful societal impact.

Professor Elisha Markus is a full Professor at the Department of Electrical, Electronic and Computer Engineering at the Central University of Technology, Free State, South Africa. His main interests include Robotics, Artificial Intelligence (AI), Internet of Things (IoT), Smart networks, control systems and assistive mobility. He has led several research projects such as cooperative control of multiple robotic systems, assistive mobility systems, IoTs and wireless communications. Others include the smart networks project, which aims to develop efﬁcient and secure networks for future smart systems, such as smart cities, smart grid, and smart water grid. He is the interim director of the Artificial Intelligence Hub at the Central University of Technology, part of the AI institute of South Africa. Prof Markus is a senior member of the Institute of Electrical Electronics Engineers (SMIEEE), member of the South African Institute of Electrical Engineers (MSAIEE) and is also registered with the Engineering Council of South Africa (ECSA).

TO CITE ARTICLE

Moloja, Dina, and Elisha Markus. “Towards the Transformation of Communication Networks Curriculum and Assessment using Artificial Intelligence in a Higher Education Setting” Journal of Education and Learning Technology 7, no.2 (2026): 216 -229. https://doi.org/10.38159/jelt.20267214