The Impact of ChatGPT on the Development of Vocabulary Knowledge of Saudi EFL Students
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Abstract
This research was piloted to systematically compare the impact of ChatGPT-generated exercises versus traditional exercises on Saudi EFL students’ vocabulary size and the strength of word families. It aimed to answer the following questions: 1) To what extent does the integration of ChatGPT-generated exercises impact Saudi EFL students’ vocabulary size of word families? 2) To what extent does the integration of ChatGPT-generated exercises impact Saudi EFL students’ vocabulary size and strength of word families? This research holds significance because it provides educators with empirical results of the impact of ChatGPT’s role and function on the second language vocabulary development process. Sixty male Saudi students at Jouf University were selected by stratified random sampling. The design of this research is experimental. Consequently, samples were randomly assigned to different experimental conditions and groups (i.e., control and treatment groups). Computer-Adaptive Test of Size and Strength, as developed by Laufer and Goldstein (2004), was administered to both groups at the beginning and end of their studies in the IELP course with an interval of four months. The collected results from all participants (N=60) from both groups and in both intervals (i.e., pre-test and post-test) were clearly and concisely imported to Statistical Package for the Social Sciences SPSS. Multivariate Analysis of Variance was conducted. Results revealed that Saudi EFL students’ vocabulary deve…
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ChatGPT is open accessible, has extensive linguistic capabilities, and can simulate human-like dialogue across topics, providing immersive learning experiences that foster deeper cognitive processing.
“Among these tools, ChatGPT has garnered significant attention due to its open accessibility, extensive linguistic capabilities, and ability to simulate human-like dialogue across a wide range of topics, thereby providing immersive learning experiences that foster deeper cognitive processing (Mugableh, 2024;Zhang & Huang, 2024).”
From Integrating ChatGPT for vocabulary learning and retention: A classroom-based study of Saudi EFL learners (2025) · cites this paper as Mugableh, 2024
Mugableh (2024) found that ChatGPT-generated exercises produced substantial gains in vocabulary size and lexical depth compared with traditional vocabulary instruction in the Saudi EFL context.
“In the Saudi EFL context, Mugableh (2024) compared ChatGPT-generated exercises with traditional vocabulary instruction, reporting substantial gains in vocabulary size and lexical depth, further affirming ChatGPT's potential as a vocabulary learning tool in structured classroom environments.”
From Integrating ChatGPT for vocabulary learning and retention: A classroom-based study of Saudi EFL learners (2025) · cites this paper as Mugableh (2024)
Cites
ChatGPT for Language Teaching and Learning
Kohnke, L., Moorhouse, B. L., & Zou, D. (2023) · RELC Journal · doi:10.1177/00336882231162868 · Cited by 1,371 · see citing works
Developing and exploring the behaviour of two new versions of the Vocabulary Levels Test
Schmitt, N., Schmitt, D., & Clapham, C. (2001) · Language Testing · doi:10.1177/026553220101800103 · Cited by 1,211 · see citing works
Research Methods, Design, and Analysis
Christensen, L. B., Johnson, R. B., & Turner, L. A. (2010) · Cited by 769 · see citing works
Impact of ChatGPT on learners in a L2 writing practicum: an exploratory investigation
Yan, D. (2023) · Education and Information Technologies · doi:10.1007/s10639-023-11742-4 · Cited by 713 · see citing works
Testing Vocabulary Knowledge: Size, Strength, and Computer Adaptiveness.
Laufer, B., & Goldstein, Z. (2004) · Language Learning · doi:10.1111/j.0023-8333.2004.00260.x · Cited by 705 · see citing works
Assessing Second Language Vocabulary Knowledge: Depth Versus Breadth
Wesche, M., & Paribakht, T. S. (1996) · The Canadian Modern Language Review · doi:10.3138/cmlr.53.1.13 · Cited by 673 · see citing works
Flanagin, A., Bibbins-Domingo, K., Berkwits, M., & Christiansen, S. L. (2023) · JAMA · doi:10.1001/jama.2023.1344 · Cited by 420 · see citing works
Májovský, M., Černý, M., Kasal, M., Komarc, M., & Netuka, D. (2023) · Journal of Medical Internet Research · doi:10.2196/46924 · Cited by 301 · see citing works
Xiao, Y., & Zhi, Y. (2023) · Languages · doi:10.3390/languages8030212 · Cited by 289 · see citing works
Using AI to write scholarly publications
Hosseini, M., Rasmussen, L. M., & Resnik, D. B. (2024) · Accountability in Research · doi:10.1080/08989621.2023.2168535 · Cited by 286 · see citing works
The creation and validation of a listening vocabulary levels test
McLean, S., Kramer, B., & Beglar, D. (2015) · Language Teaching Research · doi:10.1177/1362168814567889 · Cited by 248 · see citing works
Using chatbots to scaffold EFL students’ argumentative writing
Guo, K., Wang, J., & Chu, S. K. W. (2022) · Assessing Writing · doi:10.1016/j.asw.2022.100666 · Cited by 201 · cited 2× · see citing works
“For instance, Guo et al. (2022) integrated ChatGPT into argumentative writing classrooms for EFL students at Hong Kong University.”
BackgroundResultAssessing the Usability of ChatGPT for Formal English Language Learning
Shaikh, S., Yayilgan, S. Y., Klimova, B., & Pikhart, M. (2023) · European Journal of Investigation in Health, Psychology and Education · doi:10.3390/ejihpe13090140 · Cited by 183 · see citing works
Validating a Test to Measure Depth of Vocabulary Knowledge
Clapham, C. (2013) · Routledge eBooks · doi:10.4324/9780203053768-9 · Cited by 181 · see citing works
Educational Research and AI-Generated Writing: Confronting the Coming Tsunami
Tate, T. P., Doroudi, S., Ritchie, D., Xu, Y., & uci, M. W. (2023) · doi:10.35542/osf.io/4mec3 · Cited by 137 · see citing works
Word Families and Frequency Bands in Vocabulary Tests: Challenging Conventions
Kremmel, B. (2016) · TESOL Quarterly · doi:10.1002/tesq.329 · Cited by 116 · see citing works
Laufer, B., & Levitzky-Aviad, T. (2017) · Modern Language Journal · doi:10.1111/modl.12431 · Cited by 107 · see citing works
Milton, J., & Hopkins, N. (2006) · Canadian Modern Language Review/ La Revue canadienne des langues vivantes · doi:10.1353/cml.2006.0048 · Cited by 105 · see citing works
LIMITATIONS OF SIZE AND LEVELS TESTS OF WRITTEN RECEPTIVE VOCABULARY KNOWLEDGE
Stoeckel, T., McLean, S., & Nation, P. (2020) · Studies in Second Language Acquisition · doi:10.1017/s027226312000025x · Cited by 98 · see citing works
Vafaee, P., & Suzuki, Y. (2020) · Studies in Second Language Acquisition · doi:10.1017/s0272263119000676 · Cited by 88 · see citing works
Brown, D., Stoeckel, T., McLean, S., & Stewart, J. (2020) · Applied Linguistics · doi:10.1093/applin/amaa061 · Cited by 86 · see citing works
Longitudinal Developments in Vocabulary Knowledge and Lexical Organization
Dóczi, B., & Kormos, J. (2015) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780190210274.001.0001 · Cited by 52 · see citing works
ChatGPT conundrums: Probing plagiarism and parroting problems in higher education practices
Teel, Z. A., Wang, T., & Lund, B. D. (2023) · College & Research Libraries News · doi:10.5860/crln.84.6.205 · Cited by 31 · see citing works
The role of vocabulary breadth and depth in IELTS academic reading tests
Chen, C. (2020) · Reading in a Foreign Language · doi:10.64152/10125/66574 · Cited by 16 · see citing works
English L2 Vocabulary Learning and Teaching
Zwier, L. J., & Boers, F. (2022) · Routledge eBooks · doi:10.4324/9781003172994 · Cited by 10 · see citing works
Zhang, J., Xu, J., Zhao, Z., Hei, X., & Choo, K. R. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2308.02678 · Cited by 6 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Does ChatGPT enhance student learning? A systematic review and meta-analysis of experimental studies
Deng, R., Jiang, M., Yu, X., Lu, Y., & Liu, S. (2025) · Computers & Education · doi:10.1016/j.compedu.2024.105224 · Cited by 531 · see citing works
Wang, J., & Fan, W. (2025) · Humanities and Social Sciences Communications · doi:10.1057/s41599-025-04787-y · Cited by 322 · see citing works
RetractedLo, C. K., Yu, P. L. H., Xu, S., Ng, D. T. K., & Jong, M. S. (2024) · Smart Learning Environments · doi:10.1186/s40561-024-00342-5 · Cited by 284 · see citing works
Li, B., Tan, Y. L., Wang, C., & Lowell, V. L. (2025) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2025.100445 · Cited by 180 · see citing works
Chen, S., & Cheung, A. (2025) · Educational Research Review · doi:10.1016/j.edurev.2025.100737 · Cited by 117 · see citing works
Alotaibi, H. M., Sonbul, S., & El‐Dakhs, D. A. S. (2025) · Humanities and Social Sciences Communications · doi:10.1057/s41599-025-04945-2 · Cited by 25 · see citing works
Abdelhalim, S. M., & Alsehibany, R. (2025) · Language Learning & Technology · doi:10.64152/10125/73635 · Cited by 17 · see citing works
“Mugableh (2024) focused on ChatGPT-generated exercises, whereas the present study emphasizes its role in teacher-guided, interactive learning.”
Alnaim, N. M., Alsanad, D. S., Albelali, S., Almulhem, M., Almuhanna, A., Attar, R. W., Alsahli, M. A., Albagmi, S., Bakhshwain, A. M., Almazrou, S. H., et al. (2024) · Nutrition and Health · doi:10.1177/02601060241273596 · Cited by 12 · see citing works
Spanish language learning in the AI era: AI as a scaffolding tool
Huang, S., & Cassany, D. (2025) · Journal of China Computer-Assisted Language Learning · doi:10.1515/jccall-2024-0026 · Cited by 13 · see citing works
Reshaping Higher Education in MENA with Generative AI
Abubaker, N. M. N., Kashani, S., Alshalwy, A. M., & Garib, A. (2024) · Advances in higher education and professional development book series · doi:10.4018/979-8-3693-3904-6.ch010 · Cited by 6 · see citing works
ChatGPT for EFL: Usage and Perceptions among BA and MA Students
Aljohani, W. A. (2024) · Open Journal of Modern Linguistics · doi:10.4236/ojml.2024.146059 · Cited by 4 · see citing works
Younes, Z. B. B., Hassan, I., Umar, M. M., Mustafa, N. H., Abdullah, A. T. H., & Azmi, M. N. L. (2024) · Arab World English Journal · doi:10.24093/awej/call10.1 · Cited by 3 · see citing works
ARTIFICIAL INTELLIGENCE-DRIVEN TESTING IN EFL/ESP CLASSROOMS
Zhyhadlo, O. Y., & Заярна, І. С. (2025) · Information Technologies and Learning Tools · doi:10.33407/itlt.v106i2.5957 · Cited by 2 · see citing works
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Глазунова, Т. В., Kuzmina, S. A., & Dovhaliuk, T. (2024) · Journal of Cross-Cultural Education · doi:10.31652/2786-9083-2024-3-25-37
Learning Vocabulary Through Concordancing Vs. Chatgpt; Machine Or Ai?
Heidari, H. (2025) · i-manager’s Journal on English Language Teaching · doi:10.26634/jelt.15.1.21399
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Lin, C.-M., Wu, Y.-J., & Liu, Y.-C. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6218783
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Yaprak, Z. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6539730
Chen, X. (2026) · Cogent Education · doi:10.1080/2331186x.2026.2667534 · Cited by 2 · see citing works
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Topal, İ. H. (2026) · Research Synthesis in Applied Linguistics · doi:10.1080/29984475.2026.2709139
AI-Assisted vocabulary learning in EFL contexts: A systematic review
Mela, A. J. L. (2026) · Revista Dialogus · doi:10.37594/dialogus.v1i17.2218
Student–AI interaction: unveiling the impact of AI agents on vocabulary learning – A meta-analysis
Gao, K.-W., Shi, X., & Zhang, J. (2026) · IRAL - International Review of Applied Linguistics in Language Teaching · doi:10.1515/iral-2025-0382 · Cited by 2 · see citing works
Immediate and Delayed Effects of ChatGPT-Enhanced Vocabulary Instruction on Saudi EFL Learners
Albaqami, S. E., & Alahmadi, A. (2026) · Information · doi:10.3390/info17090812
Üretken Yapay Zekâ, Yabancılara Türkçe Öğretiminde İşlevsel Bir İçerik Geliştirici Olabilir mi?
ARAMAK, K. (2026) · Dil Eğitimi ve Araştırmaları Dergisi · doi:10.31464/jlere.1885670
Alqaed, M. A. (2026) · International Journal of Computer-Assisted Language Learning and Teaching · doi:10.4018/ijcallt.423452
The cognitive-affective impact of generative AI on EFL/ESL learning: A meta-analysis
Hsu, L., & Wang, Y.-C. (2026) · Language learning & technology · doi:10.64152/10125/73714
Boosting Vocabulary Mastery: ChatGPT’s Role in Advancing EFL Learners’ Language Skills
Ghaithi, A. A., & Behforouz, B. (2026) · Education & Self Development · doi:10.26907/esd.21.3.02
- Authors
- Ibrahim Mugableh, A.
- Venue
- Arab World English Journal
- Publisher
- AWEJ Publishing
- Published
- 2024-04-24
- Volume
- 1
- Issue
- 1
- Pages
- 265-281
- ISSN
- 2229-9327 (ISSN-L)
- OpenAlex
- W4395020834
- Cited by
- 27
- References
- 26
- Citations by year
- 2026: 11 · 2025: 8 · 2024: 8
- FWCI
- 21.07
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- Arab World English Journal (publishedVersion)
- SocArXiv (OSF Preprints) (submittedVersion, cc-by-nd)
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Second Language Acquisition and Learning
- Physical Sciences › Computer Science › Information Systems › English Language Learning and Teaching
- Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
- Keywords
- ChatGPT, vocabulary size, word families, Saudi EFL learners, second language vocabulary acquisition
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