Designing AI in education programs: Structures, enablers, and constraints in higher education in the United States
摘要
As artificial intelligence (AI) transforms education systems, higher education institutions are increasingly developing formal AI in Education (AIED) programs to prepare educators, researchers, and leaders for ethical and pedagogically grounded AI integration. This study investigates how AIED programs are structured and what factors enable or constrain their development. Drawing on semi-structured interviews with faculty teaching in AIED programs across U.S. universities, complemented by document analysis, this qualitative study explores programmatic design rationales, governance processes, and sustainability challenges. The findings reveal that AIED programs are predominantly postgraduate-level credentials, certificates and master’s degrees. Enabling factors included strong faculty leadership, multi-level institutional support, collaboration and partnerships, job market needs, staff support, and policy. Conversely, rapid technological evolution, faculty shortages, and program marketing and visibility emerged as significant constraints. These findings extend research on educational technology innovation and curriculum design by highlighting the need for systematic, interdisciplinary structures for AIED educator preparation. The paper concludes with implications for institutional strategy, faculty capacity-building, and policy mechanisms to foster sustainable AIED program ecosystems that balance technological responsiveness with enduring pedagogical and ethical principles.