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

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.

Authors

Institutions

Publication Details

Journal
International Journal of Innovative Research and Scientific Studies
Published
2025-05-26
DOI
https://doi.org/10.53894/ijirss.v8i3.7392
Primary Topic
Organizational and Employee Performance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Saada Khadragy, Dalia Hassan, Nadeen Selim, A. Hegazy et al.
International Journal of Innovative Research and Scientific Studies
Organizational and Employee Performance
article

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

Saada Khadragy, Dalia Hassan, Nadeen Selim, A. Hegazy, Naglaa Elgammal
article en

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.

International Journal of Innovative Research and Scientific StudiesVol. 8(3)
Gulf University (RS)
Openalex Percentile: Top 94%
Organizational and Employee Performance
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.