Angel Mary F
ESL teacher, Ministry of Preschool and School Education of the Republic of Uzbekistan.
Rupkatha Journal, Vol. 18, Issue 2, 2026. https://doi.org/10.21659/rupkatha.v18n2.09
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Abstract
This study analyses the role of Artificial Intelligence (AI) as a scaffolding for language impairment. Drawing on psycholinguistic theories by Levelt and Dell, a comparative study of AI-generated prompts and the language of the impaired is conducted. Following a corpus-based approach, this study employs comparative and qualitative methods to analyse language components, including mean length of utterance (MLU), type-token ratio (TTR), lexical diversity, and syntactic structure. Data on the language-impaired are collected from corpora in AphasiaBank. The research examines how AI serves as support for impaired language. It also highlights the significance of AI as an auxiliary resource for experts in education, psychology, and impairment.
Keywords:Artificial Intelligence, Aphasia, Mean Length Utterance, Type-token Ratio.
| Conflicts of Interest: The author/s declared no conflicts of interest. Funding: No funding received. Article History: Received: 14 October 2025. Revised: 08 June 2026. Accepted: 19 June 2026. First published: 26 June 2026. Copyright: © 2026 by the author/s. License: License Aesthetix Media Services, India. Distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Published by: Aesthetix Media Services, India Citation: Jeevaraj, A. E. (2026). A Posthuman Autopathographical Study of Paul Kalanithi’s When Breath Becomes Air. Rupkatha Journal, 18(2). https://doi.org/10.21659/rupkatha.v18n2.06 |
