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Technology is currently playing a vital role in revolutionizing education systems and progressing academia into the digital age. Technological methods including data mining and machine learning are assisting with the discovery of new techniques for improving learning environments in regions across the world. As the educational landscape continues to rapidly transform, researchers and administrators need to stay up to date on the latest advancements in order to elevate the quality of teaching in their specific institutions. Machine Learning Approaches for Improvising Modern Learning Systems provides emerging research exploring the theoretical and practical aspects of technological enhancements in educational environments and the popularization of contemporary learning methods in developing countries. Featuring coverage on a broad range of topics such as game-based learning, intelligent tutoring systems, and course modelling, this book is ideally designed for researchers, scholars, administrators, policymakers, students, practitioners, and educators seeking current research on the digital transformation of educational institutions.
This is a digital product.
Additional ISBNs
1799850099, 1799850102, 9781799850090, 9781799850106
Machine Learning Approaches for Improvising Modern Learning Systems and published by Information Science Reference. The Digital and eTextbook ISBNs for Machine Learning Approaches for Improvising Modern Learning Systems are 9781799850113, 1799850110 and the print ISBNs are 9781799850090, 1799850099. Additional ISBNs for this eTextbook include 1799850099, 1799850102, 9781799850090, 9781799850106.
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