Abstract
First-year programs are essential for building a foundation of success and fostering student retention in higher education. However, the challenge lies in addressing diverse learning needs while maintaining student engagement and academic confidence. This workshop demonstrates how Universal Design for Learning (UDL) principles, combined with artificial intelligence (AI), can transform the first-year experience, resulting in improved outcomes and retention rates. Participants will explore specific strategies for integrating AI tools within UDL’s three pillars: Engagement: Using AI-powered learning platforms to deliver personalized content based on students’ interests, backgrounds, and goals, fostering intrinsic motivation and a sense of belonging; Representation: Leveraging AI to create multimodal instructional materials, such as generating text-to-speech and video captions, or translating content into multiple languages to ensure accessibility for all learners; Action/Expression: Implementing adaptive assessments and AI-driven feedback tools that allow students to demonstrate their knowledge through various formats, reducing anxiety and enhancing performance. Additionally, participants will learn to use predictive analytics to monitor student progress, identify at-risk individuals early, and implement targeted, timely interventions. Examples include AI dashboards that flag patterns of disengagement or underperformance and guide educators in providing personalized support. Through hands-on activities and real-world case studies, attendees will leave with a toolkit of resources and actionable plans for using UDL and AI to design first-year programs that not only support learning but also drive retention by cultivating equity, confidence, and connection.
Presenters
Alexis MacklinExecutive Director of the Center for Teaching, Research, and Learning, Academic Affairs, Carlow University, Pennsylvania, United States
Details
Presentation Type
Theme
KEYWORDS
UDL, First-Year, AI, Retention
