Interface 2027  

The University of Florida Center for Teaching Excellence invites UF and non-UF faculty, staff, Teaching Assistants (TAs), Graduate Teaching Assistants (GAs), post-docs, and educators to submit proposals for a 30 or 50-minute session at the 2027 Interface Conference, to be held in the Hilton Conference Center on Tuesday, April 27 and Wednesday, April 28, 2027.

The Interface Teaching Conference is a dynamic two-day event designed to support and inspire educators both within and beyond the University of Florida. Day 1 will focus on teaching and learning with hands-on activities while day 2 will focus on research in teaching and learning. This annual gathering brings together faculty, staff, graduate assistants, post-docs, and academic leaders from diverse institutions to explore innovative strategies in teaching, learning, and research.  

This proposal submission is specifically for Day 1 breakout sessions, which will focus on teaching and learning through engaging, hands-on activities. 

Conference tracks: 

• Building Relationships through Innovative Teaching - Strengthen connection and engagement through student-centered teaching, active learning, experiential learning, interdisciplinary approaches, and innovative teaching strategies. 
• Technology in Teaching: Tools and Platforms - Integrate technology to enhance teaching and learning through AI tools, online course design, personalized and adaptive learning, and virtual learning strategies. 
• Retooling Assessment: Making Learning Visible in an AI World - Support student learning and growth through effective assessment, meaningful feedback, and data-informed revision. 
• Professional Development, Mentorship, and Leadership - Advance professional growth and institutional impact through faculty development, mentorship, community learning, and instructor well-being. 
• Resilience while Navigating a Changing Workforce Environment - Build resilience for instructors and students navigating changing academic and workforce conditions, including burnout, workload, career uncertainty, and AI's impact on employment.