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Factors influencing the use of media faculty members at Arab universities for artificial intelligence applications in teaching and research

Author

Listed:
  • Naglaa Elgammal
  • Dalia Hassan
  • Nadeen Selim
  • Asmaa Hegazy
  • Saada Khadragy

Abstract

Artificial Intelligence (AI) is changing higher education and scientific research. The main aim of the current paper is to explore factors that affect the use of AI by media faculty members at Arab universities for teaching and research purposes. The study depended on the “Technology Acceptance Model” (TAM) as a theoretical framework to explore the effect of perceived usefulness, perceived ease of use, and optimism on faculty attitudes, intentions, and the use of AI by the study sample. It employed a quantitative research design, utilizing an online questionnaire administered to a convenience sample of 216 media faculty members selected from various Arab universities. The results demonstrated that there was a moderate level of use of AI applications within the study sample. The results revealed that perceived utility and optimism about technology significantly influence attitudes toward AI applications in education and research. Furthermore, attitudes toward using AI applications in education and research influence both the intention to use and the actual use. However, perceived ease of use did not affect attitudes toward using AI applications in education and research, which partially supports the TAM hypotheses. The study suggests the need for training media faculty members on leveraging AI in teaching and research and developing AI ethics guidelines to govern this use.

Suggested Citation

  • Naglaa Elgammal & Dalia Hassan & Nadeen Selim & Asmaa Hegazy & Saada Khadragy, 2025. "Factors influencing the use of media faculty members at Arab universities for artificial intelligence applications in teaching and research," International Journal of Innovative Research and Scientific Studies, Innovative Research Publishing, vol. 8(3), pages 3800-3812.
  • Handle: RePEc:aac:ijirss:v:8:y:2025:i:3:p:3800-3812:id:7392
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