An intelligent curriculum alignment model for digital skills integration in higher education: a data-driven approach to bridge academia-industry gaps

The rapid evolution of digital technologies has created significant misalignment between academic curricula and labor market demands for digital skills. This misalignment is especially critical in rapidly digitizing regions such as East Africa, where workforce readiness is critical for economic development. This study presents the development and validation of an intelligent curriculum alignment model that systematically analyzes university curricula, identifies digital competencies, and maps them to labor market requirements. The research employed a hybrid artificial intelligence approach combining web scraping, Natural Language Processing (NLP), and a Decision Tree classification algorithm to create a comprehensive solution. The skillset database was built from over 46,000 real-time job postings (focused on Nairobi, Kenya) and supports continuous updates to capture emerging trends. We evaluated the model using k-fold cross-validation and expert review to ensure robustness. The model achieved an overall accuracy of 88% in classifying curriculum skills as high- or low-demand, demonstrating strong performance with an exceptional recall (0.99) for high-frequency, in-demand skills. Receiver Operating Characteristic (ROC) analysis yielded an area under the curve of 0.94, and narrow 95% confidence intervals confirmed the stability of these metrics. The study utilized data from 46,514 job postings across 27 occupations, resulting in a skillset database of 9077 unique digital skills categorized by market demand. The intelligent model generates three key outputs: a Curriculum Analysis Report, a Digital Skills Index (DSI) scoring curriculum alignment on a 0–100 scale, and a Prescriptive Analytics Report providing data-driven recommendations for curriculum improvement. Key recommendations derived from this work include the continuous integration of high-demand digital skills, promotion of interdisciplinary digital literacy, active industry participation in curriculum design, and the formulation of comprehensive national digital skills strategies. The model’s inherent capacity for continuous adaptation positions it as a vital tool for preparing a workforce that is not only ready for current demands but also resilient and adaptable to future technological shifts. This research addresses critical gaps in educational responsiveness to technological change and provides a scalable framework for continuous curriculum optimization in the digital era.

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Publication Details

Journal
Discover Education
Published
2026-01-30
DOI
https://doi.org/10.1007/s44217-026-01180-y
Primary Topic
Educational Leadership and Innovation
Type
article
Field-Weighted Citation Impact
0.00
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article

An intelligent curriculum alignment model for digital skills integration in higher education: a data-driven approach to bridge academia-industry gaps

Duncan Nyale, Abrar Sharafat, Fidelis Mukudi, Simon Karume et al.
Discover Education
Educational Leadership and Innovation
article

An intelligent curriculum alignment model for digital skills integration in higher education: a data-driven approach to bridge academia-industry gaps

Duncan Nyale, Abrar Sharafat, Fidelis Mukudi, Simon Karume, Andrew Kipkebut
article en

Abstract

The rapid evolution of digital technologies has created significant misalignment between academic curricula and labor market demands for digital skills. This misalignment is especially critical in rapidly digitizing regions such as East Africa, where workforce readiness is critical for economic development. This study presents the development and validation of an intelligent curriculum alignment model that systematically analyzes university curricula, identifies digital competencies, and maps them to labor market requirements. The research employed a hybrid artificial intelligence approach combining web scraping, Natural Language Processing (NLP), and a Decision Tree classification algorithm to create a comprehensive solution. The skillset database was built from over 46,000 real-time job postings (focused on Nairobi, Kenya) and supports continuous updates to capture emerging trends. We evaluated the model using k-fold cross-validation and expert review to ensure robustness. The model achieved an overall accuracy of 88% in classifying curriculum skills as high- or low-demand, demonstrating strong performance with an exceptional recall (0.99) for high-frequency, in-demand skills. Receiver Operating Characteristic (ROC) analysis yielded an area under the curve of 0.94, and narrow 95% confidence intervals confirmed the stability of these metrics. The study utilized data from 46,514 job postings across 27 occupations, resulting in a skillset database of 9077 unique digital skills categorized by market demand. The intelligent model generates three key outputs: a Curriculum Analysis Report, a Digital Skills Index (DSI) scoring curriculum alignment on a 0–100 scale, and a Prescriptive Analytics Report providing data-driven recommendations for curriculum improvement. Key recommendations derived from this work include the continuous integration of high-demand digital skills, promotion of interdisciplinary digital literacy, active industry participation in curriculum design, and the formulation of comprehensive national digital skills strategies. The model’s inherent capacity for continuous adaptation positions it as a vital tool for preparing a workforce that is not only ready for current demands but also resilient and adaptable to future technological shifts. This research addresses critical gaps in educational responsiveness to technological change and provides a scalable framework for continuous curriculum optimization in the digital era.

Discover EducationVol. 5(1)
Kabarak University (KE), Kenya School of Government (KE)
Quality Education
Openalex Percentile: Top 73%
Educational Leadership and Innovation
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