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This study investigates the relationship between sustainable development and the adoption of artificial intelligence (AI) in higher education. The primary objective is to identify the key factors representing sustainable development and to integrate these factors into a structural equation model to understand their impact on AI adoption. The research framework incorporates elements from the Sustainable Development Goals (SDGs), focusing on quality education, innovation, reduced inequalities, and responsible consumption and production. These elements are aligned with theoretical models such as the DeLone and McLean Information System Success Model, the Technology Acceptance Model (TAM), and the Unified Theory of Acceptance and Use of Technology (UTAUT). Data was collected through a questionnaire administered to students from various higher education institutions in the Gulf region. A sample of 549 students participated in the survey, providing insights into their perceptions, motivations, and expectations regarding AI in education. The structural equation modeling was employed to explore the collected data and test the proposed hypotheses. Preliminary results indicate that innovation and quality education are the most influential factors driving AI adoption in higher education. Students who perceive AI as a means to enhance educational quality and foster innovative learning environments show a higher propensity to adopt AI technologies. Additionally, factors related to reduced inequalities and responsible consumption and production also play significant roles, but to a lesser extent. The study reveals that while all sustainable development factors contribute to AI adoption, the emphasis on innovation and quality education significantly outweighs other factors. This research contributes to the ongoing discourse on sustainable education by elucidating the interplay between sustainable development principles and AI adoption. The findings offer valuable insights for researchers, policymakers, and educational institutions aiming to promote AI integration in higher education. By understanding the key drivers of AI adoption, stakeholders can develop targeted strategies to foster a more inclusive, innovative, and sustainable educational landscape.

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Exploring AI Adoption for Sustainable Development Goals: Theoretical Frameworks and Influencing Factors in Higher Education Within the Gulf Region

  • 章节

  • 发表日期：

    2025年

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  • Adel Bessadok,
  • Amen Alrobai

摘要

This study investigates the relationship between sustainable development and the adoption of artificial intelligence (AI) in higher education. The primary objective is to identify the key factors representing sustainable development and to integrate these factors into a structural equation model to understand their impact on AI adoption. The research framework incorporates elements from the Sustainable Development Goals (SDGs), focusing on quality education, innovation, reduced inequalities, and responsible consumption and production. These elements are aligned with theoretical models such as the DeLone and McLean Information System Success Model, the Technology Acceptance Model (TAM), and the Unified Theory of Acceptance and Use of Technology (UTAUT). Data was collected through a questionnaire administered to students from various higher education institutions in the Gulf region. A sample of 549 students participated in the survey, providing insights into their perceptions, motivations, and expectations regarding AI in education. The structural equation modeling was employed to explore the collected data and test the proposed hypotheses. Preliminary results indicate that innovation and quality education are the most influential factors driving AI adoption in higher education. Students who perceive AI as a means to enhance educational quality and foster innovative learning environments show a higher propensity to adopt AI technologies. Additionally, factors related to reduced inequalities and responsible consumption and production also play significant roles, but to a lesser extent. The study reveals that while all sustainable development factors contribute to AI adoption, the emphasis on innovation and quality education significantly outweighs other factors. This research contributes to the ongoing discourse on sustainable education by elucidating the interplay between sustainable development principles and AI adoption. The findings offer valuable insights for researchers, policymakers, and educational institutions aiming to promote AI integration in higher education. By understanding the key drivers of AI adoption, stakeholders can develop targeted strategies to foster a more inclusive, innovative, and sustainable educational landscape.