Multi-Level Barriers to Generative AI Adoption Across Disciplines and Professional Roles in Higher Education

1. 1Identify individual-level barriers such as perceived usefulness and ease of use
2. 2Investigate structural barriers such as institutional policies and resource allocation
3. 3Analyze the impact of disciplinary differences on generative AI adoption
4. 4Develop strategies to address these barriers and facilitate adoption

Researchers, educators, and administrators in higher education can benefit from understanding these barriers to facilitate effective adoption of generative AI across different disciplines and roles

💡 Barriers to generative AI adoption in higher education are complex and multi-level, requiring a nuanced understanding of individual, institutional, and disciplinary factors

🚨 Barriers to #GenAI adoption in higher ed are structurally produced, not just individual-level issues 🤖