The Use of AI-Driven Automation to Enhance Student Learning Experiences in the KSA: An Alternative Pathway to Sustainable Education

Ibrahim Mutambik ()
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Ibrahim Mutambik: Department of Information Science, College of Humanities and Social Sciences, King Saud University, P.O. Box 11451, Riyadh 11437, Saudi Arabia

Sustainability, 2024, vol. 16, issue 14, 1-21

Abstract: The relevance of virtual learning platforms has been increasingly recognised, and their merit in contributing to sustainable education is ever growing. Depending on the context, the benefits of these virtual platforms were revealed during the COVID-19 pandemic. Moreover, their impact has lingered on post-COVID-19, and virtual learning is now considered a viable option for continuing and sustainable education. Therefore, many countries have taken advantage of these virtual platforms to maximise student engagement, as evidenced by the reports in the existing literature. However, while these studies have explored how this can best be achieved, there are very few studies which have examined how the use of virtual platforms can help to deliver an educational approach that prepares young people to address the many and complex sustainability challenges of the future, i.e., the delivery of sustainable education. This study addresses this gap in the literature by exploring the question of how AI-powered automation can enhance student learning experiences in the Kingdom of Saudi Arabia (hereafter, KSA) as an alternative pathway for sustainable education. Data were collected from 1991 undergraduate and postgraduate students across 10 different Saudi universities using an online survey. The data were analysed using advanced structural equation modelling (SEM) to examine the relationship between student readiness and the (AI-powered) automation of administrative processes. The findings highlight the transformative potential of AI as an alternative pathway to sustainable education and for streamlining learning management system (LMS) operations. The implications of this study extend beyond the immediate instructional context, offering strategic direction for educators, LMS designers, policymakers, and institutional leaders in harnessing AI to equip individuals with the knowledge, skills, values, and attitudes necessary to contribute to a sustainable future.

Keywords: e-learning; learning management system (LMS); AI automation; student readiness; Student Online Learning Readiness (SOLR); sustainable education (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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