Computer-Assisted Learning for Engaging Varying Aptitudes

Computer-assisted learning has completely modernized the way that students learn both in the average classroom as well as in language learning contexts. Through its ability to provide interactive and engaging learning resources, computer-assisted learning is a useful tool for engaging all learners. It is essential that educators stay current with the emerging learning technologies so that they can create more dynamic and engaging classrooms and pique the interest of even the most apathetic students. Computer-Assisted Learning for Engaging Varying Aptitudes: From Theory to Practice is an essential reference source that provides insights on the practical applications of technology-based learning and its measurement and explains the applicability of this method in various classrooms. Covering topics in facial recognition technology, big data technology, and learning challenges, this premier reference source is a dynamic resource for faculty and administrators of both K-12 and higher education, pre-service teachers, IT consultants, educational software developers, government officials, superintendents, researchers, and academicians.

Prof. R. Dhaya has 16 years experience in teaching and research in the field of Computer Science and Engineering. She published more than 80 research papers in peer reviewed international Journals. She was the recipient of IEI Young women Engineer award. Her areas of interests are wireless sensor networks, embedded systems, Machine Learning, Communication Systems.

Prof. Kanthavel has 22 years' experience in teaching and research in the field of information and Communication Engineering. He has the credit of more than 100 research articles in peer reviewed international Journals. His areas of interests are computer networking, Machine Learning and AI, Cooperative communication, computing and mobile networks.