Transforming Assessment and Learning: Harnessing AI for Educational Excellence

Session Type: Paper Session

Abstract

This session explores the transformative potential of artificial intelligence (AI) in enhancing assessment and learning processes across educational contexts. Presentations highlight innovative applications of AI, including the development of effective learning time thresholds for early interventions, streamlining the complex creation of Individualized Education Programs (IEPs), and advancing K-12 assessment strategies. By addressing practical applications, challenges, and the commitment to inclusivity, this program aims to inform educators and policymakers about effective strategies for leveraging AI in pursuit of educational excellence. Attendees will gain insights into best practices for implementing AI-driven solutions to improve assessment quality and support diverse learners in dynamic educational environments.

Sub Unit

• SIG-Technology as an Agent of Change in Teaching and Learning

Chair

• Yin Hong Cheah, University of Idaho

Papers

• Improving Learning Efficiency: Harnessing AI to Optimize Learning Time - Haya Shamir, Waterford Institute; David Pocklington, Waterford Institute; Erik H. Yoder, Waterford Institute; Mikayla Tom, Waterford Institute; Alexander Houchins, Waterford.org

• Prototyping A Multi-Agent System to Enhance AI-Human Collaboration in IEP Development - Ling Zhang, University of Wyoming; Haidee A. Jackson, University of Texas - Permian Basin; Sohyun Yang, Fort Hays State University; Richard Carter, Indiana University; Jihong Zhang, University of Arkansas at Fayetteville; Jennifer A. Diliberto, University of North Carolina - Chapel Hill

• Transforming K-12 Assessment With AI: A Content Analysis Using the Technology Integration Model - Katia Ciampa, Widener University; Zora Wolfe, Widener University; Meagan Hensley, Widener University

Discussant

• Jeonghyun Lee, Georgia Institute of Technology