Enhancing Special Education Through Sociotechnological Integration of AI/ML-Powered IEPs

• In Event: AERA Graduate Student Research-in-Progress Roundtable Session 1
  In Roundtable Session: Applications of Artificial Intelligence (AI) in Teaching and Learning (Table 4)

Abstract

This research seeks to revolutionize the Individualized Education Plan (IEP) process for K-12 learners with diverse learning profiles. Leveraging artificial intelligence and machine learning (AI/ML) within the Expert IEP, a web-based application leveraging AI/ML to optimize existing IEPs, the study emphasizes sociotechnological frameworks, technology acceptance, and user experience (UX/UI) principles. TensorFlow and PyTorch, leading machine learning frameworks, are the backbone for developing and implementing AI/ML models within the Expert IEP application. The primary objective is to address the challenges faced by students who think and learn differently, often overlooked in integrating high-level technology. Existing studies suggest that technology exacerbates opportunity gaps for students with disabilities, contributing to widening disparities in education. This research emphasizes the intersection of technology, learning differences, and empowerment. A mixed-methods approach is employed, including collaborative development of the Expert IEP app with 20 IEP-classified students and their parents. The project delves into the phenomenological experiences of families involved in the IEP process through quantitative data collection methods in surveys and qualitative interviews. Preliminary findings from the beta version of Expert IEP indicate improved academic performance and increased parental confidence. The study anticipates uncovering nuanced insights into the sociotechnological factors influencing the acceptance and experience of AI/ML-powered IEPs.

Author

• Antoinette Banks, University of California - Davis