Masikini Lugoma, Lethuxolo Yende, Pule Dikgwatlhe, Akhona Mkonde, Rorisang Thage, Lucky Maseko, Ngonidzashe Chimwani

Proceedings of the 19th International Multi-Conference on Society, Cybernetics and Informatics: IMSCI 2025, pp. 142-147 (2025); https://doi.org/10.54808/IMSCI2025.01.142

Masikini Lugoma
Mining, Minerals and Geomatics Engineering, University of South Africa, Johannesburg, South Africa

Lethuxolo Yende
Mining, Minerals and Geomatics Engineering, University of South Africa, Johannesburg, South Africa

Pule Dikgwatlhe
Mining, Minerals and Geomatics Engineering, University of South Africa, Johannesburg, South Africa

Akhona Mkonde
Mining, Minerals and Geomatics Engineering, University of South Africa, Johannesburg, South Africa

Rorisang Thage
Mining, Minerals and Geomatics Engineering, University of South Africa, Johannesburg, South Africa

Lucky Maseko
Mining, Minerals and Geomatics Engineering, University of South Africa, Johannesburg, South Africa

Ngonidzashe Chimwani
Mining, Minerals and Geomatics Engineering, University of South Africa, Johannesburg, South Africa

Cite this paper as:
Lugoma, M., Yende, L., Dikgwatlhe, P., Mkonde, A., Thage, R., Maseko, L., Chimwani, N. (2025). A Transdisciplinary Approach to Enhancing Online Engineering Education Through Learning Analytics. In N. Callaos, J. Horne, B. Sánchez, M. Savoie (Eds.), Proceedings of the 19th International Multi-Conference on Society, Cybernetics and Informatics: IMSCI 2025, pp. 142-147. International Institute of Informatics and Cybernetics. https://doi.org/10.54808/IMSCI2025.01.142

In the context of expanding digital education and persistent global disparities in access, this study explores how learning analytics (LA) can enhance teaching effectiveness and student success in open and distance learning (ODeL) environments. Focusing on Mineral Exploitation IA, a first-year engineering module offered in a South African university’s Diploma in Mining Engineering program, the study exemplifies the use of data-driven methodologies to address systemic educational challenges such as low pass rates, high dropout rates, and poor learner retention.
This case study employs an interdisciplinary and mixed-methods research design, integrating educational data mining (EDM), behavioral analytics, and comparative analysis to assess student engagement, performance, and demographic context. Drawing on data extracted from the institution’s Moodle learning management system, the study examines how students interact with online materials (e.g., video content, discussion forums), complete assessments, and vary in performance across geographic and socioeconomic boundaries.
Findings reveal that students from remote or under-resourced regions—primarily in developing countries—face significant challenges in accessing digital platforms, often due to infrastructural and technological limitations. These constraints negatively impact their participation and performance, highlighting the interdependence of technological, pedagogical, and socio-economic systems in ODeL contexts.
Methodologically, the study aligns with an applied research paradigm, while demonstrating adaptive methodological flexibility. It incorporates a comparative framework that crosses disciplinary boundaries—drawing from education, data science, development studies, and digital communication. In doing so, it situates learning analytics not merely as a technical tool, but as a transdisciplinary research instrument capable of responding to context-specific educational realities.
The study recommends targeted pedagogical interventions, including the integration of low-bandwidth, high-accessibility tools such as WhatsApp-based academic support and e-tutoring. These interventions reflect a culturally and technologically responsive design logic, emphasizing methodological pragmatism rooted in lived student experiences.
By connecting data-informed research, methodological innovation, and context-sensitive teaching practices, this study contributes to the growing field of transdisciplinary education research. It argues for a shift from content-centred instructional design toward learner-responsive, equity-oriented strategies. It demonstrates how the thoughtful use of learning analytics can foster inclusive and effective online learning environments.