This book demonstrates teachers' and learners' experiences with big data in education; education and cloud computing; and new technologies for teacher support. It also discusses the advantages of using these frontier technologies in teaching and learning and predicts the future challenges. As such, it enables readers to better understand how technologies can improve learning and teaching experiences. It is intended for graduates and scholars in educational technology disciplines and anyone interested in the applications of frontier technologies in education.

Demonstrates the application of big data in education Enhances teaching with educational technology Supports learning through cloud computing

Autorentext
Johnathan Michael Spector is a professor at the Study Technology Department, School of Information, University of North Texas and former chairman of the Association of American Education and Communication Technology.Vivekanandan Kumar is a professor at the School of Computing and Information Systems at Athabasca University, Canada. He holds the Natural Sciences and Engineering Research Council of Canada's Discovery Grant on Anthropomorphic Pedagogical Agents, funded by the Government of Canada.Alfred Essa is vice president of Analytics and R&D at McGraw-Hill Education, where he leads the company-wide learning science research and data science practices. Previously he was director of Analytics Research & Strategy at Desire2Learn Inc, where he was responsible for research and business strategy for the analytics portfolio.Yueh-Min Huang is a chair professor of the Multimedia Network Lab at the Department of Engineering Science, National Cheng Kung University. His research interests include multimedia communications, e-learning, wireless networking and artificial intelligence.Rob Koper is a distinguished professor at the Open University of the Netherlands with a specific focus on the innovation of online education. He studies the social and cognitive aspects of human learning, the effective use of ICTs for human learning and the improvement of educational institutions to facilitate teaching and learning.Richard A. W. Tortorella received his MSc degree from Athabasca University, Canada in 2013 and is currently a PhD candidate at the University of Eastern Finland. His research interests include context-aware learning systems, m-Learning and artificial intelligence.Ting-Wen Chang is an associate research fellow and the director of the International Cooperation Center at Beijing Normal University's Smart Learning Institute. His research focuses on smart learning as is involved in numerous international cooperation projects.Yanyan Li is a professor at Beijing Normal University's Smart Learning Institute. Her research interests include computer-supported collaborative learning, learning analytics, and STEAM education.Zhizhen Zhang is a lecturer at the School of Educational Technology, Faculty of Education at Beijing NormalUniversity. His research interests include teacher professional learning, technology-enhanced science education and education software development.

Inhalt
Chapter 1 Learning Any Time, Anywhere: Big Educational Data from Smart Devices.- Chapter 2 Framing Learning Analytics and Educational Data Mining for Teaching: Critical Inferencing, Domain Knowledge, & Pedagogy.- Chapter 3 Learning Traces, Competence Assessment, and Causal Inference for English Composition.- Chapter 4 QUESGEN: A Framework for Automatic Question Generation Using Semantic Web and Lexical Databases.- Chapter 5 A big data reference architecture for teaching social media mining.- Chapter 6 Big Data in Education: Supporting Learners in Their Role as Reflective Practitioners.- Chapter 7 Towards Big Data in Education: the case at the Open University of the Netherlands.- Chapter 8 Learning Analytics in Practice: Providing e-Learning Researchers and Practitioners with Activity Data.- Chapter 9 Using Apache Spark for Modeling Education Data at Scale.- Chapter 10 Towards a Cloud-Based Big Data Infrastructure for Higher Education Institutions.- Chapter 11 Cloud Services in Collaborative Learning: Applications and Implications.- Chapter 12 Cloud Computing Environment in Big Data for Education.- Chapter 13 Head in the Clouds: Some of the Possible Issues with Cloud-Computing in Education.