Frontiers of Cyberlearning Emerging Technologies for Teaching and Learning /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Spector, J. Michael (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Kumar, Vivekanandan (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Essa, Alfred (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Huang, Yueh-Min (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Koper, Rob (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Tortorella, Richard A. W. (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Chang, Ting-Wen (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Li, Yanyan (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Zhang, Zhizhen (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2018.
• Έκδοση: 1st ed. 2018.
• Σειρά: Lecture Notes in Educational Technology,
• Θέματα: Educational technology.; Education-Data processing.; Educational Technology.; Technology and Digital Education.; Computers and 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....

Πίνακας περιεχομένων:

• 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.