Title: Enhancing curriculum benchmarking by leveraging NLP: a case study of higher education in Tanzania

Authors: Elia Ahidi Elisante Lukwaro; Rogers Balalusesa; Khamisi Kalegele; Devotha G. Nyambo

Addresses: ICT Department, The Open University of Tanzania, Dar es salaam, Tanzania; ICSE Department, Nelson Mandela African Institution of Science and Technology, Arusha, Tanzania ' ICT Department, The Open University of Tanzania, Dar es salaam, Tanzania ' ICT Department, The Open University of Tanzania, Dar es salaam, Tanzania ' ICSE Department, Nelson Mandela African Institution of Science and Technology, Arusha, Tanzania

Abstract: The fast expansion of higher education institutions and the discrepancy between skill sets and labour market demands have heightened stakeholders' concerns regarding the quality of education. Syllabi are the focal points of this study, as they act as the bridge between education and the skills or competencies required to demonstrate the relationship between the acquired education and the required market competencies. Benchmarking, which has its roots in business, is now widely used in education as a mechanism for evaluating educational metrics and practices and comparing them among institutions or with those of competitors with the aim of improving performance. This paper benchmarks the quality of syllabi using an NLP-based model, namely the sentence bidirectional encoder representations from transformers (SBERT). By utilising the course book to refine the SBERT model, which is a variation of 'all-MiniLM-L6-v2', an experiment is carried out to investigate the most effective parameter metric for model training. With an accuracy score of 92.64%, the model performance score demonstrates a high level of ability to discern conceptual and semantic relationships between sentences, leading to successful syllabi benchmarking outcomes. This work offers a perceptive mechanism to address the mismatch between educationally acquired skills and industry demands.

Keywords: higher education; natural language processing; NLP; benchmarking; SBERT; performance; hyperparameter optimisation; Tanzania.

DOI: 10.1504/IJTEL.2026.155133

International Journal of Technology Enhanced Learning, 2026 Vol.18 No.3, pp.249 - 269

Received: 12 Aug 2024
Accepted: 07 Sep 2024
Published online: 28 Jul 2026 *

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