Integrating AI to Address Generational Characteristics and Educational Needs - Andreeva, Antonina; Tuchkevich, Evgenia (Journal of Teaching and Learning)

(untitled) (University of Windsor, 2025)
In contemporary higher education, the master's level plays a critical role in developing high-level professionals, particularly among Generation-Z students. This stage is marked by significant psychological, social, and professional development, requiring innovative educational strategies that align with the unique traits of this digital-native cohort. Integrating artificial intelligence (AI) technologies, such as adaptive-learning systems, intelligent tutoring, and automated-feedback mechanisms, offers transformative potential to address these needs. This study investigates the intersection of generational characteristics and AI integration in master's education through a convergent parallel mixed-methods design, combining quantitative surveys with qualitative interviews of 300 master's students across various disciplines. The findings reveal predominantly positive attitudes toward AI, with 78% of students recognizing its ability to enhance personalized learning and engagement. However, concerns about data privacy (54%) and reduced human interaction (48%) highlight the need for an ethical and balanced implementation. Grounded in constructivist and activity theories, this research underscores the potential of AI to foster autonomy, self-determination, and personalized educational experiences while addressing generational expectations for immediacy and interactivity. Practical recommendations are provided for educators and policymakers to implement AI effectively, ensuring that it supplements human-centred teaching practices. These insights contribute to the global discourse on AI integration in higher education, and its implications for enhancing lifelong learning and professional growth.