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by Srinivasa K. G. (Author), Muralidhar Kurni (Author)
This book A Beginner's Guide to Learning Analytics is designed to meet modern educational trends' needs. It is addressed to readers who have no prior knowledge of learning analytics and functions as an introductory text to learning analytics for those who want to do more with evaluation/assessment in their organizations. The book is useful to all who need to evaluate their learning and teaching strategies. It aims to bring greater efficiency and deeper engagement to individual students, learning communities, and educators.
Covered here are the key concepts linked to learning analytics for researchers and practitioners interested in learning analytics. This book helps those who want to apply analytics to learning and development programs and helps educational institutions to identify learners who require support and provide a more personalized learning experience. Like chapters show diverse uses of learning analytics to enhance student and faculty performance. It presents a coherent framework for the effective translation of learning analytics research for educational practice to its practical application in different educational domains. This book provides educators and researchers with the tools and frameworks to effectively make sense of and use data and analytics in their everyday practice. This book will be a valuable addition to researchers' bookshelves.
Back Jacket
This book A Beginner's Guide to Learning Analytics is designed to meet modern educational trends' needs. It is addressed to readers who have no prior knowledge of learning analytics and functions as an introductory text to learning analytics for those who want to do more with evaluation/assessment in their organizations. The book is useful to all who need to evaluate their learning and teaching strategies. It aims to bring greater efficiency and deeper engagement to individual students, learning communities, and educators.
Covered here are the key concepts linked to learning analytics for researchers and practitioners interested in learning analytics. This book helps those who want to apply analytics to learning and development programs and helps educational institutions to identify learners who require support and provide a more personalized learning experience. Like chapters show diverse uses of learning analytics to enhance student and faculty performance. It presents a coherent framework for the effective translation of learning analytics research for educational practice to its practical application in different educational domains. This book provides educators and researchers with the tools and frameworks to effectively make sense of and use data and analytics in their everyday practice. This book will be a valuable addition to researchers' bookshelves.
Author Biography
Dr. Srinivasa K G is currently working as a Professor in National Institute of Technical Teachers Training and Research, Chandigarh. He received his Ph.D. in Computer Science and Engineering from Bangalore University in 2007. He is the recipient of All India Council for Technical Education - Career Award for Young Teachers, Indian Society of Technical Education - ISGITS National Award for Best Research Work Done by Young Teachers, Institution of Engineers (India) - IEI Young Engineer Award in Computer Engineering, Rajarambapu Patil National Award for Promising Engineering Teacher Award from ISTE - 2012, IMS Singapore - Visiting Scientist Fellowship Award. He has published more than 150 research papers in International Conferences and Journals. He has visited many Universities abroad as a visiting researcher - He has visited University of Oklahoma, USA, Iowa State University, USA, Hong Kong University, Korean University, National University of Singapore, University of British Columbia, Canada are his few prominent visits. He has authored eight text books with prestigious publishers like TMH, Springer, Oxford, etc. He has edited many research monographs in the areas of Cyber Physical Systems, Energy Aware Computing and Artificial Intelligence with prestigious International publishers. He has been awarded BOYSCAST Fellowship by DST, for conducting collaborative. Research with Clouds Laboratory in University of Melbourne in the area of Cloud Computing. He is the principal Investigator for many funded projects from AICTE, UGC, DRDO, and DST. He is the senior member of IEEE and ACM. His research areas include Data Mining, Machine Learning and Cloud Computing. His recent research areas include Innovative Teaching Practices in Engineering Education, pedagogy; outcomes based education, and teaching philosophy.
Mr. Muralidhar Kurni is an Independent Consultant for Pedagogy Refinement, EduRefine, India. He is currently working as an Assistant Professor in the Department of Computer Science & Engineering at Anantha Lakshmi Institute of Technology & Sciences, Anantapuramu, Andhra Pradesh, India. Previously he worked as Head, Department of Computer Applications, Sri Sai College of Technology & Management, Kadapa, Andhra Pradesh, India. Mr. Muralidhar Kurni has received his M.Sc. in Computer Science from S. K. University and M.Tech. in Computer Science & Engineering from JNTUA, Ananthapuram, Andhra Pradesh, India. He has more than 19 years of teaching experience. He is an IUCEE & IGIP certified International Engineering Educator & researcher. He has several scholarly publications to his credit. He presented about 30 papers at various national and international conferences and journals. Four of his papers received the best paper awards. Two of them are the IEEE Conference Best Paper awards. He has been a reviewer for various International Conferences & Journals, including SCIE & Scopus indexed Journals. He served as a Guest Editor for the Special Issue on "Security, Privacy, and Trust in IoT" of IJWNBT Journal, IGI Global, Volume 8, Issue 2, July-December 2019. His research interests include Learning Analytics, Learning Strategies, Digital Pedagogy, Design Thinking, Pedagogy refinement & Engineering Education Research.- In stock, ready to ship
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