Machine Learning Approaches for Improvising Modern Learning Systems (Advances in Educational Technologies and Instructional Design)

ISBN 10: 1799850099 / ISBN 13: 9781799850090

Verlag: Information Science Reference, 2021

Beschreibung

In. Bestandsnummer des Verkäufers ria9781799850090_new

Bibliografische Details

Titel: Machine Learning Approaches for Improvising ...

Verlag: Information Science Reference

Erscheinungsdatum: 2021

Einband: Hardcover

Zustand: New

Über diesen Titel

Inhaltsangabe:

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.

Über die Autorin bzw. den Autor:

Zameer Gulzar is an Assistant Professor in the Department of Computer Application, BSAR Crescent Institute of Science and Technology, Chennai. The editor’s areas of interest are e-learning, ontology, recommender systems, multimedia. Semantic Web, etc.