Akademik Veri Yönetim Sistemi
Journal of Engineering Education Transformations, cilt.39, sa.Special Issue 1, ss.3-19, 2025 (Scopus)
This research investigates the factors influencing the adoption of GenAI in computer engineering (CE) education within the Middle East and North Africa (MENA) region. The gap in the adoption of GenAI seems to be less pronounced between northern and southern countries compared to other digital technologies. Nevertheless, the academic community has not fully explored the institutional, cultural, and geopolitical factors affecting GenAI adoption. Utilising Harold Linstone's multiple perspectives theory (1981-2019), this study analyses the technical, organisational, and personal viewpoints of 50 CE educators working in higher education institutions in the MENA area. Through an abductive thematic analysis of the interviews and sentiment analysis, the research provides a comprehensive understanding of the GenAI-powered Educational Ecosystem for CE (AEECE) by detailing the essential processes, applications, outcomes, and interactions among the key stakeholders in this ecosystem, including educators, students, university administration, regulators, industry partners, and employers. From a technical standpoint, our findings indicate that GenAI is transforming CE in the region, particularly concerning coding and programming competencies for project management, content creation, and cybersecurity analytics. Other technical insights included innovative practical applications, comprehension of AI's opaque aspects, and limitations in resources. From an organisational viewpoint, we identified that aligning AI investments with the national vision is crucial, as is the need for curriculum reform and addressing resource disparities among various geopolitical contexts. On a personal level, it was noted that educators stepping back from their role as learning facilitators and an excessive reliance on GenAI can undermine critical thinking skills, highlighting the importance of ethical usage and implementation of GenAI applications.