The Dual Nature of Generative AI in Inclusive Education: Investigating the Role of AI in Students with Disabilities’ Empowerment, Dependence, and Academic Participation

Abstract

Generative AI has made its way into classrooms and university campuses before the completion of studies necessary to understand its impact on students with disabilities, a group which might benefit the most from such technology. The present paper aims to develop a structural model illustrating how AI carries positive and negative consequences in the context of inclusive education. This will be facilitated through the development of two parallel paths along which AI impacts students with disabilities, the empowerment path and the dependence path. The former relies on the fact that AI is accessible to students, makes it possible for them to obtain additional assistance while studying, which leads to increasing their learning efficiency and engagement into different academic processes. The latter path assumes that students of higher education institutions, being dependent on the use of AI tools, have to offload cognitive processes making them weaker learners. Finally, the paper examines the role of AI literacy in the mediation of the relationship between accessibility of AI and dependence on it. The relevance of the paper is justified by the presented academic literature review for 2022 and afterwards, as well as the design of ten hypotheses and the explanation of the methodology to be applied using SmartPLS 4 software for the analysis of primary data obtained from surveys of students with disabilities in India. The paper includes full examinations of the measurement model and structural hypotheses. Moreover, the conceptions of Self-Determination Theory and Cognitive Load Theory will be presented to justify each hypothesis of the study. The final part of the paper will depict the summary of the findings and determine the significance of studying the AI impact on the inclusive teaching process.