International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

Frequency: 12

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 Volume 13, Issue 3 (March 2026), Pages: 95-104

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 Original Research Paper

Evaluating the role of artificial intelligence (AI) in enhancing vocabulary retention in foreign language acquisition

 Author(s): 

Nisar Ahmad Koka 1, Basim Kana’an 1, Sheeba Hassan 2, Javed Ahmad 1, Nusrat Jan 2, Mohamad A. Khasawneh 3, Mohammad A. Tashtoush 3, 4, *

 Affiliation(s):

1Department of English, College of Languages and Translation, King Khalid University, Abha, Saudi Arabia
2Department of Linguistics, University of Kashmir, Jammu and Kashmir, India
3Faculty of Education and Arts, Sohar University, Sohar, Oman
4Department of Basic Sciences, Al-Huson University College, Al-Balqa Applied University, Salt, Jordan

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 * Corresponding Author. 

   Corresponding author's ORCID profile:  https://orcid.org/0000-0002-2436-8155

 Digital Object Identifier (DOI)

  https://doi.org/10.21833/ijaas.2026.03.010

 Abstract

This study examines the impact of Artificial Intelligence (AI) tools on vocabulary retention among foreign language learners in Saudi Arabia. A quasi-experimental design was used with 150 students divided into two groups: an experimental group that used AI-based learning tools and a control group that followed traditional teaching methods. The results show that students who used AI tools achieved significantly higher vocabulary retention and showed greater engagement than those in the control group. Moreover, students in the experimental group reported spending more time on learning activities and expressed higher satisfaction with their learning experience. These findings suggest that AI tools can improve traditional language education by providing personalized learning support for vocabulary acquisition. The study also highlights the potential long-term benefits of integrating AI into language learning and recommends further research to better understand its broader role in educational development.

 © 2026 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords

Artificial intelligence, Vocabulary retention, Language learning, Personalized learning, Student engagement

 Article history

Received 13 October 2025, Received in revised form 2 March 2026, Accepted 9 March 2026

 Funding

This research is supported by King Khalid University (Grant number: RGP2/681/46). 

 Acknowledgment

The authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through the Large Research Project under grant number RGP2/681/46. 

 Compliance with ethical standards

 Ethical considerations:

This study was approved by the Ethical Committee of the Deanship of Scientific Research at King Khalid University, Saudi Arabia (Ref. No. RGP2/681/46). All participants provided informed consent and were informed of their right to withdraw at any time. Data were collected anonymously, kept confidential, and used solely for research purposes, with appropriate measures taken to ensure data privacy in the use of AI-based tools. 

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

Koka NA, Kana’an B, Hassan S, Ahmad J, Jan N, Khasawneh MA, and Tashtoush MA (2026). Evaluating the role of artificial intelligence (AI) in enhancing vocabulary retention in foreign language acquisition. International Journal of Advanced and Applied Sciences, 13(3): 95-104

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 References (29)

  1. Abdulbaki S, Harrathi H, Khasawneh MA, and Tashtoush MA (2025). A comparative study of national, gender, and academic differences in smartphone addiction among students from Jordan, Saudi Arabia, Oman, and the UAE. International Journal of Advanced and Applied Sciences, 12(8): 101-109. https://doi.org/10.21833/ijaas.2025.08.010   [Google Scholar]

  2. Albalwi ASM (2023). Investigating the influence of learning-centred leadership on authentic instruction and the contribution to enhancing the learning culture: A case study of four Saudi Arabian primary schools. Ph.D. Dissertation, Newcastle University, Newcastle, UK.   [Google Scholar]

  3. Aldowsari BI and Aljebreen SG (2024). The impact of using a ChatGPT-based application to enhance Saudi students’ EFL vocabulary learning. International Journal of Language and Literary Studies, 6(4): 380-397. https://doi.org/10.36892/ijlls.v6i4.1955   [Google Scholar]

  4. Alenezi A (2023). Teacher perspectives on AI-driven gamification: Impact on student motivation, engagement, and learning outcomes. Information Technologies and Learning Tools, 97(5): 138-148. https://doi.org/10.33407/itlt.v97i5.5437   [Google Scholar]

  5. Al-Faqih MM (2015). English grammar achievement level among secondary school leavers in Saudi Arabia. Ph.D. Dissertation, Leeds Beckett University, Leeds, UK.   [Google Scholar]

  6. Aloufi F, Tashtoush MA, Shirawia N, Tashtoush R, and Az-Zo’Bi E (2024). Internet of Things in education: Teachers’ perspectives, practices and challenges. WSEAS Transactions on Computer Research, 12: 429-442. https://doi.org/10.37394/232018.2024.12.42   [Google Scholar]

  7. Beirat MA, Tashtoush DM, Khasawneh MA, Az-Zo’bi EA, and Tashtoush MA (2025). The effect of artificial intelligence on enhancing education quality and reduce the levels of future anxiety among Jordanian teachers. Applied Mathematics and Information Sciences, 19(2): 279-290. https://doi.org/10.18576/amis/190205   [Google Scholar]

  8. Chen YL, Hsu CC, Lin CY, and Hsu HH (2022). Robot-assisted language learning: Integrating artificial intelligence and virtual reality into English tour guide practice. Education Sciences, 12(7): 437. https://doi.org/10.3390/educsci12070437   [Google Scholar]

  9. Dimitriadou E and Lanitis A (2023). A critical evaluation, challenges, and future perspectives of using artificial intelligence and emerging technologies in smart classrooms. Smart Learning Environments, 10: 12. https://doi.org/10.1186/s40561-023-00231-3   [Google Scholar] PMid:40478141 PMCid:PMC9900563

  10. Duncan EM, Bennett T, and Gillies K (2020). Assessing effective interventions to improve trial retention: Do they contain behaviour change techniques? Trials, 21: 213. https://doi.org/10.1186/s13063-020-4151-4   [Google Scholar] PMid:32085717 PMCid:PMC7035706

  11. Farmer TW, Bierman KL, Hall CM, Brooks DS, and Lee DL (2021). Tiered systems of adaptive supports and the individualization of intervention: Merging developmental cascades and correlated constraints perspectives. Journal of Emotional and Behavioral Disorders, 29(1): 3-13. https://doi.org/10.1177/1063426620957651   [Google Scholar]

  12. Fu J (2009). A study of learning styles, teaching styles and vocabulary teaching strategies in Chinese primary school: How do they differ and how can they be integrated? Available online at: http://www.diva-portal.org/smash/get/diva2:228945/fulltext01    [Google Scholar]

  13. Garrison DR and Kanuka H (2004). Blended learning: Uncovering its transformative potential in higher education. The Internet and Higher Education, 7(2): 95-105. https://doi.org/10.1016/j.iheduc.2004.02.001   [Google Scholar] PMCid:PMC8236236

  14. Halabi M (2017). The role of the tutors in supporting learners in a higher education distance language learning programme environment in Saudi Arabia. Ph.D. Dissertation, University of Sheffield, Sheffield, UK.   [Google Scholar]

  15. Halkiopoulos C and Gkintoni E (2024). Leveraging AI in e-learning: Personalized learning and adaptive assessment through cognitive neuropsychology—A systematic analysis. Electronics, 13(18): 3762. https://doi.org/10.3390/electronics13183762   [Google Scholar]

  16. Hatamleh HA, Alsaadi O, Alkhafaji B, Khasawneh MA, and Tashtoush MA (2025). Game-based and AI-driven engagement strategies to combat demotivation in foreign language learning. International Journal of Advanced and Applied Sciences, 12(3): 119-130. https://doi.org/10.21833/ijaas.2025.03.013   [Google Scholar]

  17. Helsing D, Howell A, Kegan R, and Lahey L (2008). Putting the "development" in professional development: Understanding and overturning educational leaders' immunities to change. Harvard Educational Review, 78(3): 437-465. https://doi.org/10.17763/haer.78.3.888l759g1qm54660   [Google Scholar]

  18. Huang AY, Lu OH, and Yang SJ (2023). Effects of artificial intelligence–enabled personalized recommendations on learners’ learning engagement, motivation, and outcomes in a flipped classroom. Computers & Education, 194: 104684. https://doi.org/10.1016/j.compedu.2022.104684   [Google Scholar]

  19. Kirkwood A and Price L (2014). Technology-enhanced learning and teaching in higher education: what is ‘enhanced’ and how do we know? A critical literature review. Learning, Media and Technology, 39(1): 6-36. https://doi.org/10.1080/17439884.2013.770404   [Google Scholar]

  20. Lindsey RV, Shroyer JD, Pashler H, and Mozer MC (2014). Improving students’ long-term knowledge retention through personalized review. Psychological Science, 25(3): 639-647. https://doi.org/10.1177/0956797613504302   [Google Scholar] PMid:24444515

  21. Miao F and Holmes W (2021). AI and education: A guidance for policymakers. UNESCO Publishing, Paris, France.   [Google Scholar]

  22. O'Brien HL and Toms EG (2008). What is user engagement? A conceptual framework for defining user engagement with technology. Journal of the American Society for Information Science and Technology, 59(6): 938-955. https://doi.org/10.1002/asi.20801   [Google Scholar]

  23. Rudman LA, Glick P, and Glick PS (2021). The social psychology of gender: How power and intimacy shape gender relations. Guilford Publications, New York, USA.   [Google Scholar]

  24. Ruiz-Rojas LI, Salvador-Ullauri L, and Acosta-Vargas P (2024). Collaborative working and critical thinking: Adoption of generative artificial intelligence tools in higher education. Sustainability, 16(13): 5367. https://doi.org/10.3390/su16135367   [Google Scholar]

  25. Sajja R, Sermet Y, and Demir I (2025). End-to-end deployment of the educational AI hub for personalized learning and engagement: A case study on environmental science education. IEEE Access, 13: 55169-55186. https://doi.org/10.1109/ACCESS.2025.3554222   [Google Scholar]

  26. Sajja R, Sermet Y, Cikmaz M, Cwiertny D, and Demir I (2024). Artificial intelligence-enabled intelligent assistant for personalized and adaptive learning in higher education. Information, 15(10): 596. https://doi.org/10.3390/info15100596   [Google Scholar]

  27. Srinivasa KG, Kurni M, and Saritha K (2022). Harnessing the power of AI to education. In: Srinivasa KG, Kurni M, and Saritha K (2022). Learning, teaching, and assessment methods for contemporary learners: 311-342. Springer, Singapore, Singapore. https://doi.org/10.1007/978-981-19-6734-4_13   [Google Scholar]

  28. Teng MF and Reynolds BL (2024). Researching incidental vocabulary learning in a second language. Routledge, London, UK. https://doi.org/10.4324/9781003270782-1   [Google Scholar]

  29. Zheng Y and Xiao A (2024). A structural equation model of online learning: Investigating self-efficacy, informal digital learning, self-regulated learning, and course satisfaction. Frontiers in Psychology, 14: 1276266. https://doi.org/10.3389/fpsyg.2023.1276266   [Google Scholar] PMid:38274678 PMCid:PMC10809156