Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource George, Alwin T.; Gupta, Varuna; Mehndiratta, Vandana Title A name given to the resource Artificial Intelligence and Machine Learning in Educational Apps Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Cutting-Edge Mobile Applications for Higher Education;pp.39-90 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3693-8287-5.ch002" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3693-8287-5.ch002</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105031914524?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105031914524?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant George A.T., Christ University, Bangalore, India; Gupta V., Christ University, Bangalore, India; Mehndiratta V., Christ University, Bangalore, India Description An account of the resource The integration of Artificial Intelligence (AI) and Machine Learning (ML) in educational applications is transforming higher education by enhancing personalized learning, intelligent tutoring, and predictive analytics. This chapter explores AI-driven functionalities, including adaptive learning, NLP, and automated assessments, while addressing challenges such as data privacy, algorithmic bias, and accessibility. Through case studies, it highlights AIs transformative potential in shaping future education, offering insights for educators, researchers, and developers interested in AI-driven learning innovations. 2026 by IGI Global Scientific Publishing. All rights reserved. Publisher An entity responsible for making the resource available IGI Global Relation A related resource ISBN: 979-836938289-9; 979-836938287-5; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online