Machine Learning Approaches For Improvising Modern Learning Systems
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Machine Learning Approaches for Improvising Modern Learning Systems
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.
International Conference on Innovative Approaches to the Application of Digital Technologies in Education and Research
This book is based on the best papers accepted for presentation during the SLET-2022: International Conference on Innovative Approaches to the Application of Digital Technologies in Education and Research. The book includes research on digital pedagogy, e-learning technologies, end-to-end technologies in education, and educational transformation. The contributions in this volume highlight the significant advancements and innovative methodologies in digital education. The book provides a consolidated research exploration on contemporary themes in education such as digital teaching technologies, digital pedagogy and resources, gamification, and innovations in education with a special focus on educational technology for present and future educators. The authors of these papers have explored diverse topics, such as artificial intelligence in education, the integration of virtual and augmented reality, the development of online learning platforms, and the impact of digital tools on student engagement and learning outcomes. This collection aims to provide educators, researchers, and practitioners with insights into the latest trends and challenges in digital education. It also seeks to inspire further research and innovation in applying digital technologies to enhance teaching and learning experiences. As the landscape of education continues to evolve, the integration of digital technologies becomes increasingly critical. This book addresses a wide range of issues and opportunities, offering valuable perspectives on how digital tools can be leveraged to improve educational outcomes and accessibility. This book serves as a vital resource for comprehending the future of education and the transformative role digital technologies play in its development. By delving into the innovative approaches and cutting-edge research presented within, readers gain a deeper understanding of how digital advancements are redefining educational practices and enhancing learning experiences. The insights provided in this volume help educators develop more effective teaching strategies, incorporate new technologies into their curricula, and ultimately create more engaging and inclusive learning environments. Moreover, the book intends to foster new ideas, discussions, and collaborations that will continue to advance educational technology, thus bringing together a diverse array of research and perspectives to encourage a multidisciplinary approach to solving the complex challenges facing modern education.
Applications of Machine Learning and Artificial Intelligence in Education
Modes and models of learning and instruction have shown a significant shift from yesterday's conventional learning and teaching given this era’s current educational and social contexts. Learners are no longer learning and communicating with human-generated, computed, and mediated—or traditional—learning and instructional practices, paving the way for machine-facilitated communication, learning, and teaching tools. Learning and instruction, communication and information exchange, as well as gathering, coding, analyzing, and synthesizing data have proven to be in need of even more innovative technology-moderated tools. Applications of Machine Learning and Artificial Intelligence in Education focuses on the parameters of remote learning, machine learning, deep learning, and artificial intelligence under 21st-century learning and instructional contexts. Covering topics such as data coding and social networking technology, it is ideal for learners with an interest in the deep learning discipline, educators, educational technologists, instructional designers, and data evaluators, as well as special interest groups (SGIs) in the discipline.