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dc.contributor.authorLytras, Miltiadis
dc.contributor.authorSerban, Andreea Claudia
dc.contributor.authorAlkhaldi, Afnan
dc.contributor.authorAldosemani, Tahani
dc.contributor.authorMalik, Sawsan
dc.date.accessioned2024-05-13T06:21:46Z
dc.date.available2024-05-13T06:21:46Z
dc.date.issued2024-08-31
dc.identifier.citationLytras, M. D., Serban, A., Alkhaldi, A., Aldosemani, T., & Malik, S. (2024). Chapter 9. What's next in higher education: The AI revolution 2030. In M. D. Lytras, A. Serban, A. Alkhaldi, T. Aldosemani, & S. Malik (Eds.), Digital transformation in higher education: Challenges and best practices (Part A). In Emerald Studies in Active and Transformative Learning in Higher Education. Emerald Publishing.en_US
dc.identifier.urihttp://hdl.handle.net/20.500.14131/1637
dc.description.abstractThis chapter explores the transformative impact of artificial intelligence (AI) on higher education, particularly in the context of accelerating technological and societal changes. As higher education institutions face the need to offer more flexible, adapted, and relevant academic programmes, AI presents significant opportunities and challenges. In the first part of this chapter, we elaborated on the characteristics of the evolution of AI, including the emerging AI landscape. One of our contributions in this concluding chapter is to conceptualise the next areas of deployment of AI in higher education, considering the novel, innovative services that will disrupt the entire market in the next few years. Our strategic proposition for the deployment of AI in higher education highlighted six pillars, namely: large language models and research. AI is content creation. AI, or personalized learning. AI, skills-building assistants. AI is education out of the box. AI. We presented opportunities to harness AI to enhance teaching, learning, and research under each pillar, along with a detailed list of potential application areas and services. Universities are exploring innovative ways to use AI-driven solutions to improve research, teaching, and learning experiences, and we also developed indicative scenarios for the use of AI in higher education based on the six pillars. One of our bold contributions in this chapter is the structured framework for understanding the evolution and use of AI in higher education, utilising a matrix to map the intersection of market penetration and product development. Finally, we discuss future directions and strategies for higher education in 2030 in light of advances in AI technology.en_US
dc.publisherEmerald Publishing Limiteden_US
dc.subjectDigital Transformationen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectDigital Learningen_US
dc.subjectArtificial Intelligenceen_US
dc.titleWhat's next in higher education: The AI revolution 2030en_US
dc.source.volumeEmerald Studies in Active and Transformative Learning in Higher Education. Emerald Publishing.;
refterms.dateFOA2024-05-13T06:21:47Z
dc.contributor.researcherExternal Collaborationen_US
dc.contributor.labNAen_US
dc.subject.KSAEducationen_US
dc.contributor.ugstudent0en_US
dc.contributor.alumnae0en_US
dc.source.indexScopusen_US
dc.contributor.departmentComputer Scienceen_US
dc.contributor.pgstudent0en_US
dc.contributor.firstauthorLytras, Miltiadis


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