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Session Type: Paper Session
This session brings together research on equity, accessibility, and inclusion in technology-enhanced education. Papers examine how AI and digital tools support learners with disabilities, address socioeconomic and racial disparities, and promote participation among underrepresented groups. Using adaptive systems, critical machine learning pedagogies, and inclusive design principles, these studies reveal how technologies can either amplify inequities or serve as equalizers. The papers chart pathways toward equitable digital learning environments that empower all learners through access, adaptability, and representation.
Adapting Interactive Digital Materials for Learners with Intellectual and Developmental Disabilities - Shamila Janakiraman, University of Hawai‘i at Mānoa; Robin Dazzeo, University of Hawaii - Manoa; Sandra Oshiro, University of Hawaii - Manoa
Adaptive AI for Science Text Accessibility in Students with Reading Disabilities - Richard Lamb, University of Georgia; Danielle Jo Malone, Purdue University; Tosha L. Owens, East Carolina University; Ikseon Choi, Emory University; Shruti Kundu, University of Georgia
Digital Technology as Amplifier and Buffer of SES-Achievement Gap: Evidence from Double Machine Learning - Yigu Liang, Beijing Normal University; Na Li, Beijing Normal University; Yingke Xu, Beijing Normal University; Wei Tian, Beijing Normal University
Middle school Black Girls’ Perspectives on Surveillance: Discourse Shifts in a Critical Machine Learning Project - Atefeh Behboudi, Vanderbilt University; Golnaz Arastoopour Irgens, Vanderbilt University
Promoting Science Learning Among At-Risk Students: The Impact of Exploratory Learning Utilizing Interactive Simulations - Janan Saba, Hebrew University of Jerusalem; Malak Abu Rmaileh, Hebrew University of Jerusalem; Tali Gal, Hebrew University of Jerusalem