Perspectives and Experiences of Education Stakeholders: A Quantitative Study on the Adoption of Artificial Intelligence in Executive Training Using Structural Equation Modeling

Atoubi, El Mostafa and Jahidi, Rachid (2024) Perspectives and Experiences of Education Stakeholders: A Quantitative Study on the Adoption of Artificial Intelligence in Executive Training Using Structural Equation Modeling. Intelligent Information Management, 16 (02). pp. 104-120. ISSN 2160-5912

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Abstract

The recent increase in the use of artificial intelligence has led to fundamental changes in the development of training and teaching methods for executive education. However, the success of artificial intelligence in regional centers for teaching and training professions will depend on the acceptance of this technology by young executive trainees. This article discusses the potential benefits of adopting AI in executive training institutions in Morocco, specifically focusing on CRMEF Casablanca Settat. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al., 2003), this study proposes a model to identify the factors influencing the acceptance of artificial intelligence in regional centers for teaching professions and training in Morocco. To achieve this, a structural equation modeling approach was used to quantitatively describe the impact of each factor on AI adoption, utilizing data collected from 173 young executive trainees. The results indicate that perceived ease of use, perceived usefulness, trainer influence, and personal innovativeness influence the intention to use artificial intelligence. Our research provides managers of CRMEFs with a set of practical recommendations to enhance the implementation conditions of an artificial intelligence system. It aims to understand which factors should be considered in designing an artificial intelligence system within regional centers for teaching professions and training (CRMEFs).

Item Type: Article
Subjects: Eprints AP open Archive > Multidisciplinary
Depositing User: Unnamed user with email admin@eprints.apopenarchive.com
Date Deposited: 28 Mar 2024 05:30
Last Modified: 28 Mar 2024 05:30
URI: http://asian.go4sending.com/id/eprint/2062

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