Publication

Abstract : It has been a trending strategy to incorporate Artificial Intelligence (AI) into academic programs and to create student's interest. In this study we investigate how AI specialization and terminology effect program selection, specifically with students who are not enrolled in a STEM program. A mixed-methods approach, combining quantitative surveys and qualitative interviews, was employed to analyze enrollment patterns, career perceptions, and the decision-making process of students across four categories: AI, STEM and NonSTEM, STEM and no AI, Non-STEM and no AI. We find that programs that have AI components attract more applications and enrollments, and are perceived as more relevant by students, to the current needs of industry and as a path to upward mobility throughout their career. Programs that offered specialization in AI got better career importance, program relevance, placement rate and student satisfaction scores. The barriers for non-STEM students, like perceived gaps of technical skills, are identified, and there is a solution proposed, as foundational AI training before experience with their career interest is suggested. Out of these points, it becomes clear that the educational institutions need to evolve the course of their curriculum and marketing strategy based on the evolving requirements of the AI driven world, whereby the educational institution will always stay ahead in such a dynamic educational environment. This research serves to improve understanding of the strategic role of AI in determining the future of higher education and therefore, the corresponding implications for interdisciplinary learning and employability.