LEVERAGING GENERATIVE ARTIFICIAL INTELLIGENCE (GENAI) TO TRANSFORM EFL INSTRUCTIONAL PRACTICES IN THE CONTEXT OF 21ST-CENTURY SKILLS

The research proposes the use of Generative Artificial Intelligence (GenAI) technologies to improve instructional practice in accordance with 21st-century skills among EFL teachers in Saudi Arabia. The study employed a descriptive quantitative design, utilizing a validated 32-item GenAI Utilization Scale with four dimensions: Critical Thinking and Problem Solving, Creativity and Innovation, Communication and Collaboration, and Digital and ICT Literacy. A total of 139 EFL teachers enrolled in graduate programs at King Khalid University served as the data source. Findings indicated that the general level of GenAI use is moderate (M = 3.00, 60.08%), with the highest and lowest scores in Communication and Collaboration and Digital and ICT Literacy, respectively. Gender-based conclusions revealed statistically significant differences in favor of male teachers (p < .05), and self-report of technology proficiency exhibited a strong positive correlation with GenAI use (p < .001). Nevertheless, they did not find any remarkable differences between school levels and years of experience. The results point to a period of transition in the use of GenAI, in which teachers use AI as a supportive, rather than a transformative, instructional resource. The paper highlights the significance of specific professional development to enhance teachers' digital integration in terms of competence, creativity, and critical thinking. In general, it provides empirical evidence that can inform

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Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-02
DOI
https://doi.org/10.5281/zenodo.18840865
Primary Topic
AI in Service Interactions
Type
article
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article

LEVERAGING GENERATIVE ARTIFICIAL INTELLIGENCE (GENAI) TO TRANSFORM EFL INSTRUCTIONAL PRACTICES IN THE CONTEXT OF 21ST-CENTURY SKILLS

Abdul Aziz Mohamed Mohamed Ali El Deen1*, Abdul Qader Emran2, Majed E. Alenazi3, Amr M. Mohamed4, Asem Mohammed Ibrahim5
Zenodo (CERN European Organization for Nuclear Research)
AI in Service Interactions
article

LEVERAGING GENERATIVE ARTIFICIAL INTELLIGENCE (GENAI) TO TRANSFORM EFL INSTRUCTIONAL PRACTICES IN THE CONTEXT OF 21ST-CENTURY SKILLS

Abdul Aziz Mohamed Mohamed Ali El Deen1*, Abdul Qader Emran2, Majed E. Alenazi3, Amr M. Mohamed4, Asem Mohammed Ibrahim5
article en

Abstract

The research proposes the use of Generative Artificial Intelligence (GenAI) technologies to improve instructional practice in accordance with 21st-century skills among EFL teachers in Saudi Arabia. The study employed a descriptive quantitative design, utilizing a validated 32-item GenAI Utilization Scale with four dimensions: Critical Thinking and Problem Solving, Creativity and Innovation, Communication and Collaboration, and Digital and ICT Literacy. A total of 139 EFL teachers enrolled in graduate programs at King Khalid University served as the data source. Findings indicated that the general level of GenAI use is moderate (M = 3.00, 60.08%), with the highest and lowest scores in Communication and Collaboration and Digital and ICT Literacy, respectively. Gender-based conclusions revealed statistically significant differences in favor of male teachers (p < .05), and self-report of technology proficiency exhibited a strong positive correlation with GenAI use (p < .001). Nevertheless, they did not find any remarkable differences between school levels and years of experience. The results point to a period of transition in the use of GenAI, in which teachers use AI as a supportive, rather than a transformative, instructional resource. The paper highlights the significance of specific professional development to enhance teachers' digital integration in terms of competence, creativity, and critical thinking. In general, it provides empirical evidence that can inform

Zenodo (CERN European Organization for Nuclear Research)
Imam Mohammad ibn Saud Islamic University (SA), Islamic University (BD)
Quality Education
Openalex Percentile: Top 42%
AI in Service Interactions
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