Measuring Institutions’ Adoption of Artificial Intelligence Applications in Online Learning Environments: Integrating the Innovation Diffusion Theory with Technology Adoption Rate
Summary. This study examines how governmental institutions in the Gulf region adopt artificial intelligence applications in online learning environments. Using innovation diffusion theory, researchers found that adoption properties like trialability, observability, and compatibility positively influence ease of doing business and technology export. The findings suggest government authorities should prioritize implementation factors based on their significance to improve service delivery and user accessibility.
Cite this article
Almaiah, M. A., Alfaisal, R., Salloum, S. A., Hajjej, F., Shishakly, R., Lutfi, A., Alrawad, M., Mulhem, A. A., Alkhdour, T., & Al-Maroof, R. S.. (2022). Measuring Institutions’ Adoption of Artificial Intelligence Applications in Online Learning Environments: Integrating the Innovation Diffusion Theory with Technology Adoption Rate. Electronics. https://doi.org/10.3390/electronics11203291
Almaiah, Mohammed Amin, et al. “Measuring Institutions’ Adoption of Artificial Intelligence Applications in Online Learning Environments: Integrating the Innovation Diffusion Theory with Technology Adoption Rate.” Electronics, 2022. https://doi.org/10.3390/electronics11203291.
Almaiah, Mohammed Amin, Raghad Alfaisal, Said A. Salloum, Fahima Hajjej, Rima Shishakly, Abdalwali Lutfi, Mahmaod Alrawad, Ahmed Al Mulhem, Tayseer Alkhdour, and Rana Saeed Al-Maroof. 2022. “Measuring Institutions’ Adoption of Artificial Intelligence Applications in Online Learning Environments: Integrating the Innovation Diffusion Theory with Technology Adoption Rate.” Electronics. https://doi.org/10.3390/electronics11203291.
@article{almaiah-2022-measuring-institutions-adoption-artificial-intelligence,
title = {Measuring Institutions’ Adoption of Artificial Intelligence Applications in Online Learning Environments: Integrating the Innovation Diffusion Theory with Technology Adoption Rate},
author = {Mohammed Amin Almaiah and Raghad Alfaisal and Said A. Salloum and Fahima Hajjej and Rima Shishakly and Abdalwali Lutfi and Mahmaod Alrawad and Ahmed Al Mulhem and Tayseer Alkhdour and Rana Saeed Al-Maroof},
journal = {Electronics},
year = {2022},
doi = {10.3390/electronics11203291},
url = {https://doi.org/10.3390/electronics11203291}
}
TY - JOUR TI - Measuring Institutions’ Adoption of Artificial Intelligence Applications in Online Learning Environments: Integrating the Innovation Diffusion Theory with Technology Adoption Rate AU - Mohammed Amin Almaiah AU - Raghad Alfaisal AU - Said A. Salloum AU - Fahima Hajjej AU - Rima Shishakly AU - Abdalwali Lutfi AU - Mahmaod Alrawad AU - Ahmed Al Mulhem AU - Tayseer Alkhdour AU - Rana Saeed Al-Maroof JO - Electronics PY - 2022 DO - 10.3390/electronics11203291 UR - https://doi.org/10.3390/electronics11203291 ER -
Details
- DOI
- 10.3390/electronics11203291
- Countries
- Malaysia, United Kingdom
- Regions
- Asia, Europe
- Categories
- broadband-and-digital, innovation-theory, general-innovation
- Added
- 2026-04-28