3rd TAGRA

This study investigates how an artificial intelligence (AI)-DevSecOps framework can support the modernization of major-specific ICT education and the alignment of course content with contemporary industry requirements. A comparative case study was conducted for the “Computer Networks” course at the University of Central Asia using teaching materials from the fall semesters of the 2022/2023 and 2025/2026 academic years. A corpus-based lexical analysis was performed using a 444-term computer-networking glossary as specialized vocabulary. The number of glossary terms with non-zero occurrences increased from 97 to 173, corresponding to a 1.78-fold increase in the breadth of specialized terminology represented in the course materials. The framework also incorporated cybersecurity-related subtopics into a 15-week sequence and supported the iterative development of presentations, practical assignments, and quizzes with generative AI and DevSecOps practices. The findings indicate substantial expansion of course-content coverage; however, the study does not establish a causal effect on student learning or employment outcomes. The results suggest that an AI-DevSecOps approach can support curriculum modernization by combining AI-assisted content development, practical cybersecurity activities, and continuous alignment with industry-oriented ICT competencies.