AI in Special Language Education: A Case Study of ChatGPT Utilization among Jordanian Students with ADHD

Raeda Ammari, Majd S. Abushunar, Esraa Hantouleh, Ahmad M. Al Omari, Emad Abdulla Hannah

doi:10.32038/ltrq.2026.56.01

European KnowledgeDevelopment Institute

Original Research

AI in Special Language Education: A Case Study of ChatGPT Utilization among Jordanian Students with ADHD

Language Teaching Research Quarterly, Volume 56, Pages 1-20, https://doi.org/10.32038/ltrq.2026.56.01

Abstract
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This study carried out a quantitative analysis to investigate the use of ChatGPT in teaching English vocabulary to students with ADHD in Jordan. The sample consisted of 100 students with ADHD from 40 schools. The data were collected using three instruments. A pre-test and post-test assessed students’ vocabulary proficiency level over six months to evaluate students’ vocabulary development. A questionnaire was constructed to evaluate students’ attitudes toward using ChatGPT, while another questionnaire was administered to 20 English teachers from participating schools to measure the impact of ChatGPT and the challenges of integrating it into the educational environment. The assessment tests revealed an improvement in students’ vocabulary performance. The students’ questionnaire indicated that students with ADHD perceived ChatGPT as an effective tool for learning vocabulary, particularly due to the immediate feedback. The teachers’ questionnaire revealed that teachers considered ChatGPT as a valuable instructional tool. Teachers highlighted the main barriers to its effective implementation, such as limited resources and insufficient teacher training. The study concluded that ChatGPT has substantial potential to enhance English vocabulary learning among students with ADHD, but adequate educational support and teacher training are required.

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Keywords

AI; Vocabulary Teaching; ADHD; ChatGPT; Special Language Education

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Author(s) Information

Raeda Ammari

Raeda M. Ammari is an Associate Professor specializing in linguistics and discourse studies. She earned a BA in English Literature from Al-Ahliyya Amman University, followed by an MSc and PhD in Linguistics from the University of Jordan. She currently teaches at Amman Arab University. Her research interests include corpus linguistics, discourse analysis, and sociolinguistics. Dr. Ammari has published studies on social media discourse, cooperative learning, synonym usage, and political language in news reports. She participates in academic workshops at various schools and serves as a reviewer for the IJAES.

Majd S. Abushunar

Majd Abushunar obtained her Ph.D. degree in English Language and Linguistics from the University of Jordan. She is currently a full-time lecturer at The Hashemite University, where she teaches a variety of English language and linguistics courses. Her research interests include psycholinguistics, phonology, morphology, sociolinguistics, corpus linguistics, and discourse analysis. She has published several research papers in international journals focusing on phonological analysis, language acquisition, EFL learning, and linguistic analysis. In addition to teaching and research, she actively participates in academic workshops and community-service initiatives related to English language education.

Esraa Hantouleh

She is an English language instructor and a researcher in the field of Linguistics at the University of Jordan. She also has a strong background in Machine Learning. Her work focuses on exploring how Artificial Intelligence and Machine Learning can be integrated into English as a Foreign Language (EFL) learning. In addition, she is interested in examining various aspects of Semantics and Pragmatics, including politeness, metaphor, polysemy, and persuasion.

Ahmad M. Al Omari

Ahmad Al-Omari is a skilled and dedicated professional in the field of computer information systems. He earned his bachelor’s and master’s degrees in computer information systems from Yarmouk University. Ahmad's research interests include, but are not limited to, deep learning, machine learning, data science, and computer vision.

Emad Abdulla Hannah

Emad is the Managing Partner and Chief Consulting Officer at Competence Management Consulting (CMC), with over 18 years of professional experience in business consulting and organizational development. He holds a BSc in Mechanical Engineering, an MBA specializing in growth and marketing, and an international trade diploma from FITT. His expertise includes strategy, leadership, business transformation, export readiness, and market systems. Emad supports organizations in developing practical growth strategies and strengthening internal capabilities. He also specializes in applying artificial intelligence in business to enhance productivity, innovation, digital transformation, and strategic decision-making across diverse organizational and market contexts.

Publisher’s Note

The claims, arguments, and counter-arguments made in this article are exclusively those of the contributing authors. Hence, they do not necessarily represent the viewpoints of the authors’ affiliated institutions, or EUROKD as the publisher, the editors and the reviewers of the article.

Acknowledgements

The authors would like to thank all the students and faculty members who participated in this study for their valuable time and contributions.

Funding

The authors declare that no funding was received for this research.

CRediT Authorship Contribution Statement

Raeda Ammari: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Writing-Review & Editing

Majd S. Abushunar: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Writing-Review & Editing

Esraa Hantouleh: Methodology, Supervision, Validation, Writing-Review & Editing

Ahmad M. Al Omari: Software, Supervision, Visualization, Writing-Review & Editing

Emad Abdulla Hannah: Supervision, Validation, Writing-Review & Editing

Generative AI Use Disclosure Statement

Grammarly was used for language editing and clarity improvement. The authors reviewed and take full responsibility for the content.

Ethics Declarations

World Medical Association (WMA) Declaration of Helsinki–Ethical Principles for Medical Research Involving Human Participants

The study was carried out in accordance with ethical principles. Permission was obtained from the school administration, and participants’ confidentiality was ensured. Moreover, informed consent was obtained from all participating students and teachers before collecting the data.

Competing Interests

There are no competing interests.

Data Availability

The data are not publicly available because they contain confidential participant information. Access to the data is restricted to comply with the ethical conditions under which the study was approved.