International Journal of

ADVANCED AND APPLIED SCIENCES

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

Frequency: 12

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 Volume 13, Issue 7 (July 2026), Pages: 118-125

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 Original Research Paper

The impact of artificial intelligence on cognitive skill development in future professionals

 Author(s): 

Raissa Izmagambetova 1, Elena Agranovich 2, Aktolkyn Boranbayeva 3, *, Talasbek Aiman 3, Akilbayeva Gulnar 3, Ospanbekova Meirgul 4

 Affiliation(s):

1Department of Preschool Education and Social Pedagogy, Abai Kazakh National Pedagogical University, Almaty, Kazakhstan
2Department of Pedagogy and Methods of Primary Education, Kazakh National Women’s Teacher Training University, Almaty, Kazakhstan
3Department of Special Pedagogy, South Kazakhstan Pedagogical University Named After Uzbekali Zhanibekov, Shymkent, Kazakhstan
4Department of Pedagogy and Methods of Primary Education, Arkalyk Pedagogical University Named After Ybyrai Altynsarin, Arkalyk, Kazakhstan

 Full text

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 * Corresponding Author. 

   Corresponding author's ORCID profile:  https://orcid.org/0000-0001-6256-6999

 Digital Object Identifier (DOI)

 
https://doi.org/10.21833/ijaas.2026.07.011

 Abstract

This study aims to examine how the use of Generative AI affects the development of cognitive skills among future professionals in the multilingual and multicultural education system of Kazakhstan. To achieve this, a combination of quantitative survey data and qualitative insights from semi-structured interviews was used. The research sample consisted of 148 fourth-year students from Kazakh- and Russian-language communities. Quantitative data were analyzed using descriptive statistics and the non-parametric Kruskal–Wallis H test to evaluate differences in perceptions. The findings show that participants mainly viewed AI as a supportive cognitive resource that helped them engage in the learning process and personalize their learning experience. The highest scores were observed in the Cognitive and Motivational Drivers dimension, while the Self-Directed Learning dimension suggests that students approached AI-assisted learning with some caution. The results indicate the presence of a blended learning model in which students integrate modern technologies into their education while continuing to rely on traditional learning approaches. No statistically significant differences were found between the two language groups, indicating similar attitudes toward AI. However, the findings cannot be generalized because of the specific context and the limited scope of the study.

 © 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

Generative AI, Cognitive skill development, AI-assisted learning, Blended learning, Multilingual education

 Article history

Received 6 February 2026, Received in revised form 12 July 2026, Accepted 18 July 2026

 Acknowledgment

This research was conducted within the framework of the “Zhas Galym” grant project for 2024–2026, funded by the Science Committee of the Ministry of Education and Science of the Republic of Kazakhstan [grant number AP22684921]. 

 Compliance with ethical standards

 Ethical considerations

This study was conducted in accordance with established ethical standards for research involving human participants. Prior to participation, written informed consent was obtained from all participants at the beginning of the questionnaire form. Participants were informed about the purpose of the study, the voluntary nature of their participation, and their right to withdraw from the study at any stage without any negative consequences. To ensure confidentiality and privacy, all responses were collected anonymously, and no personally identifiable information was recorded. The collected data were used solely for academic and research purposes and were stored securely. Furthermore, the study protocol and research procedures were reviewed and approved by the Ethics Committee of the Kazakh National Women’s Pedagogical University (Approval No. 2024/47). 

 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:

Izmagambetova R, Agranovich E, Boranbayeva A, Aiman T, Gulnar A, and Meirgul O (2026). The impact of artificial intelligence on cognitive skill development in future professionals. International Journal of Advanced and Applied Sciences, 13(7): 118-125

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 References (23)

  1. Albadarin Y, Saqr M, Pope N, and Tukiainen M (2024). A systematic literature review of empirical research on ChatGPT in education. Discover Education, 3: 60. https://doi.org/10.1007/s44217-024-00138-2   [Google Scholar]
  2. Aydın Ö and Karaarslan E (2023). Is ChatGPT leading generative AI? What is beyond expectations? Academic Platform Journal of Engineering and Smart Systems, 11(3): 118-134. https://doi.org/10.21541/apjess.1293702   [Google Scholar]
  3. Bollaert L (2025). Artificial intelligence: Objective or tool in the 21st-century higher education strategy and leadership? Education Sciences, 15(6): 774. https://doi.org/10.3390/educsci15060774   [Google Scholar]
  4. Dave A (2025). The ethical implications of AI in education. Research Review Journal of Social Science, 5(1): 1-8. https://doi.org/10.31305/rrjss.2025.v05.n01.001   [Google Scholar]
  5. Deep PD and Chen Y (2025). The role of AI in academic writing: Impacts on writing skills, critical thinking, and integrity in higher education. Societies, 15(9): 247. https://doi.org/10.3390/soc15090247   [Google Scholar]
  6. Deroncele-Acosta A, Sayán-Rivera RME, Mendoza-López AD, and Norabuena-Figueroa ED (2025). Generative artificial intelligence and transversal competencies in higher education: A systematic review. Applied System Innovation, 8(3): 83. https://doi.org/10.3390/asi8030083   [Google Scholar]
  7. Fitria TN (2021). The use technology based on artificial intelligence in English teaching and learning. ELT Echo: The Journal of English Language Teaching in Foreign Language Context, 6(2): 213-223. https://doi.org/10.24235/eltecho.v6i2.9299   [Google Scholar]
  8. Haleem A, Javaid M, and Singh RP (2022). An era of ChatGPT as a significant futuristic support tool: A study on features, abilities, and challenges. BenchCouncil Transactions on Benchmarks, Standards and Evaluations, 2(4): 100089. https://doi.org/10.1016/j.tbench.2023.100089   [Google Scholar]
  9. Jacobsen LJ and Weber KE (2025). The promises and pitfalls of large language models as feedback providers: A study of prompt engineering and the quality of AI-driven feedback. AI, 6(2): 35. https://doi.org/10.3390/ai6020035   [Google Scholar]
  10. Japoshvili-Ghvinashvili M and Suleman N (2023). Assisting ELT teachers: Designing activities for the use of ChatGPT in teaching and learning. Pakistan Journal of Multidisciplinary Innovation, 2(1): 24-35. https://doi.org/10.59075/pjmi.v2i1.219   [Google Scholar]
  11. Kasneci E, Seßler K, Küchemann S et al. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103: 102274. https://doi.org/10.1016/j.lindif.2023.102274   [Google Scholar]
  12. Nasr NR, Tu CH, Werner J, Bauer T, Yen CJ, and Sujo-Montes L (2025). Exploring the impact of generative AI ChatGPT on critical thinking in higher education: Passive AI-directed use or human–AI supported collaboration? Education Sciences, 15(9): 1198. https://doi.org/10.3390/educsci15091198   [Google Scholar]
  13. Phua JTK, Neo HF, and Teo CC (2025). Evaluating the impact of artificial intelligence tools on enhancing student academic performance: Efficacy amidst security and privacy concerns. Big Data and Cognitive Computing, 9(5): 131. https://doi.org/10.3390/bdcc9050131   [Google Scholar]
  14. Roe J and Perkins M (2022). What are automated paraphrasing tools and how do we address them? A review of a growing threat to academic integrity. International Journal for Educational Integrity, 18: 15. https://doi.org/10.1007/s40979-022-00109-w   [Google Scholar]
  15. Samadhiya A, Kumar A, Mulat-Weldemeskel E, Luthra S, Garza-Reyes JA, and Yadav S (2025). Next-gen quality learning: How can AI technologies shape education 4.0 and 5.0 towards the SDGs from multiple stakeholders' perspective? The TQM Journal, 38(4): 806–834. https://doi.org/10.1108/TQM-11-2024-0441   [Google Scholar]
  16. Shahriar S and Dara R (2025). Priv-IQ: A benchmark and comparative evaluation of large multimodal models on privacy competencies. AI, 6(2): 29. https://doi.org/10.3390/ai6020029   [Google Scholar]
  17. Shiri M and Baigutov K (2024). Evaluating art students’ engagement with digital technologies in classroom settings. International Journal of Advanced and Applied Sciences, 11(11): 240-248. https://doi.org/10.21833/ijaas.2024.11.025   [Google Scholar]
  18. Shiri M and Baigutov K (2025). Exploring the influence of teachers' academic rank in advancing inclination to TPACK in art education: Case study: Faculty of Arts, Department of Art Education, Abai Kazakh National Pedagogical University, Kazakhstan. Social Sciences & Humanities Open, 11: 101252. https://doi.org/10.1016/j.ssaho.2024.101252   [Google Scholar]
  19. Shiri M, Baigutov K, Izmagambetova R, Abisheva O, and Ryssymbetov Y (2025). The impact of academic rank on teachers’ TPACK competence in art education. International Journal of Advanced and Applied Sciences, 12(3): 49-57. https://doi.org/10.21833/ijaas.2025.03.006   [Google Scholar]
  20. Sullivan M, Kelly A, and McLaughlan P (2023). ChatGPT in higher education: Considerations for academic integrity and student learning. Journal of Applied Learning & Teaching, 6(1): 31-40. https://doi.org/10.37074/jalt.2023.6.1.17   [Google Scholar]
  21. Zhai X (2023). ChatGPT for next generation science learning. XRDS: Crossroads, the ACM Magazine for Students, 29(3): 42-46. https://doi.org/10.1145/3589649   [Google Scholar]
  22. Zhong Y and Rosli MSB (2025). Generative artificial intelligence in higher education: Opportunities, challenges, and future directions. International Journal of Academic Research in Progressive Education and Development, 14(3): 301-312. https://doi.org/10.6007/IJARPED/v14-i3/25813   [Google Scholar]
  23. Zhou J, Müller H, Holzinger A, and Chen F (2024). Ethical ChatGPT: Concerns, challenges, and commandments. Electronics, 13(17): 3417. https://doi.org/10.3390/electronics13173417   [Google Scholar]