TITLE:
A Supply-Demand Alignment Study of Preservice Teacher Education Programs in the Context of Artificial Intelligence
AUTHORS:
Rui Yang
KEYWORDS:
Artificial Intelligence, Preservice Teachers, Teacher Education Programs, Supply-Demand Alignment
JOURNAL NAME:
Creative Education,
Vol.17 No.8,
August
25,
2026
ABSTRACT: The systemic transformation of the educational ecosystem driven by artificial intelligence technologies has imposed new demands on preservice teacher education. Based on a self-developed supply-demand alignment framework for preservice teachers’ AI literacy, this study employed a mixed-methods approach combining questionnaire surveys and semi-structured interviews to empirically examine the current status of preservice teachers’ AI literacy and the provision of teacher education programs. The questionnaire was distributed across multiple teacher education institutions, yielding 112 valid responses. Semi-structured interviews were conducted with 15 preservice teachers from diverse backgrounds, generating approximately 80,000 Chinese characters of qualitative data. The findings revealed an uneven development pattern across different dimensions of preservice teachers’ AI literacy. On the demand side, preservice teachers demonstrated a gradient profile characterized by positive AI awareness, moderate AI knowledge, limited AI competencies, and fragmented AI ethical understanding. On the supply side, teacher education programs showed several structural limitations, including sporadic classroom integration, insufficient practical platforms, and insufficient support for AI ethics education. The supply-demand alignment analysis identified four core gaps: perceived gaps in institutional support for AI awareness development, superficial knowledge provision, structural mismatches in competency development, and systemic neglect of AI ethics education. To address these gaps, this study proposes three strategies: developing a progressive AI curriculum framework, strengthening immersive practical training, and embedding continuous AI ethics education throughout teacher preparation. These recommendations aim to provide empirical evidence and practical pathways for the targeted optimization of preservice teacher education programs.