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.

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.