The implications of generative artificial intelligence on the 21st - century skills of pre-service and in-service teachers: A mixed methods study

Authors

DOI:

https://doi.org/10.20448/jeelr.v13i2.8807

Keywords:

21st-century skills, 4Cs, Generative artificial intelligence ChatGPT, In-service teachers, Pre-service teachers, United Arab Emirates.

Abstract

This study aims to investigate the impact of using generative artificial intelligence tools, such as ChatGPT, on the development of 21st-century skills among pre-service and in-service teachers in the United Arab Emirates. The study adopted a mixed quantitative and qualitative research methodology. The quantitative sample consisted of 240 pre-service and in-service teachers. The qualitative phase included semi-structured interviews with 35 pre-service and in-service teachers. The results of the statistical analysis showed that the averages of in-service teachers were statistically significantly higher than those of pre-service teachers in critical thinking, creative thinking, and collaboration skills, while no statistically significant differences were found in communication skills. The results also showed a moderate to high level of AI impact in supporting 21st-century skills among pre-service and in-service teachers. The interviews revealed that generative AI contributes to stimulating critical thinking through interactive dialogue and exploring creative alternatives that can be adapted to classroom needs. Interviews also showed that these tools support professional communication and collaboration, but also revealed concerns about overreliance on AI. The integrated results indicate that in-service teachers are more capable of employing AI practically in real classroom situations.

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Published

2026-06-12

How to Cite

Qiqieh, S., Alkhazalah, M. S., Alwaely, S. A., & Saleem, J. (2026). The implications of generative artificial intelligence on the 21st - century skills of pre-service and in-service teachers: A mixed methods study. Journal of Education and E-Learning Research, 13(2), 206–213. https://doi.org/10.20448/jeelr.v13i2.8807

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Section

Articles