The Impact of AI and LMS Integration on the Future of Higher Education: Opportunities, Challenges, and Strategies for Transformation

Nayef Shaie Alotaibi ()
Additional contact information
Nayef Shaie Alotaibi: College of Languages and Translation, Imam Mohammad bin Saud Islamic University, Riyadh 43211, Saudi Arabia

Sustainability, 2024, vol. 16, issue 23, 1-21

Abstract: The integration of artificial intelligence (AI) and learning management systems (LMS) is revolutionising higher education, offering unprecedented opportunities for personalised learning, adaptive assessments, and data-driven decision-making. This review investigates the impact of AI–LMS integration on educational quality, student success, and institutional performance in higher education. In addition, this review not only examines the technological integration but also evaluates how AI–LMS systems contribute to sustainable development in higher education through reduced resource consumption, improved accessibility, and enhanced educational equity. Following the PRISMA 2020 guidelines, a comprehensive search of the Scopus database yielded 60 relevant studies published between 2014 and 2023. The review reveals significant benefits of AI–LMS integration, including enhanced student engagement, personalised learning paths, and improved learning outcomes. Key applications include AI-powered conversational agents, adaptive assessments, and learning analytics. However, challenges such as data privacy concerns, algorithmic bias, and the need for faculty training were also identified. The findings highlight strategies for effective AI–LMS implementation, emphasising the importance of ethical considerations and addressing the digital divide. Results demonstrate that AI–LMS integration can significantly enhance educational quality and student performance when implemented thoughtfully. The review also uncovers areas requiring further research, including long-term impacts on learning outcomes, scalability of AI–LMS solutions, and strategies for ensuring equitable access. Future studies should focus on longitudinal assessments of AI–LMS effectiveness, the development of ethical frameworks for AI in education, and the exploration of AI–LMS applications in diverse educational contexts. This review provides valuable insights for higher education institutions seeking to leverage AI–LMS integration to transform teaching and learning practices.

Keywords: artificial intelligence; learning management systems; higher education; educational technology; personalised learning (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:

Downloads: (external link)
https://www.mdpi.com/2071-1050/16/23/10357/pdf (application/pdf)
https://www.mdpi.com/2071-1050/16/23/10357/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:16:y:2024:i:23:p:10357-:d:1530325

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().