TY - BOOK AU - Daniel, Ben Kei TI - Big Data and Learning Analytics in Higher Education Current Theory and Practice SN - 9783319065199 PY - 2017/// CY - PB - Springer KW - LB - Theory and practice of education KW - Big data KW - Analytics KW - Trends KW - Higher education KW - Research KW - Embedded Digital Ecosystems (EDE) KW - Data Paradigm KW - Ethical Considerations KW - Justice KW - Care KW - Ethics KW - Curricular KW - Evaluation KW - Moodle KW - GraphFES KW - Ecosystem KW - Skills KW - Clinical Anatomy e-Cases KW - e-Cases N1 - current theory and practice; Chapter 1: Overview of Big Data and Analytics in Higher Education; Chapter 2: Thoughts on Recent Trends and Future Research Perspectives in Big Data and Analytics in Higher Education--; Chapter 3: Big Data in Higher Education: The Big Picture--; Chapter 4: Preparing the Next Generation of Education Researchers for Big Data in Higher Education--; Chapter 5: Managing the Embedded Digital Ecosystems (EDE) Using Big Data Paradigm--; Chapter 6: The Contemporary Research University and the Contest for Deliberative Space--; Part II: LEARNING ANALYTICS--; Chapter 7: Ethical Considerations in Adopting a University- and System-Wide Approach to Data and Learning Analytics--; Chapter 8: Big Data, Higher Education and Learning Analytics: Beyond Justice, Towards an Ethics of Care--; Chapter 9: Curricular and Learning Analytics: A Big Data Perspective--; Chapter 10: Implementing a Learning Analytics Intervention and Evaluation Framework: What Works?--; Chapter 11: GraphFES: A Web Service and Application for Moodle Message Board Social Graph Extraction--; Chapter 12: Toward an Open Learning Analytics Ecosystem--; Chapter 13: Predicting Four-Year Student Success from Two-Year Student Data--; Chapter 14: Assessing Science Inquiry Skills in an Immersive, Conversation-Based Scenario--; Chapter 15: Learning Analytics of Clinical Anatomy e-Cases.-- N2 - This book focuses on the uses of big data in the context of higher education. The book describes a wide range of administrative and operational data gathering processes aimed at assessing institutional performance and progress in order to predict future performance, and identifies potential issues related to academic programming, research, teaching and learning​. Big data refers to data which is fundamentally too big and complex and moves too fast for the processing capacity of conventional database systems. The value of big data is the ability to identify useful data and turn it into useable information by identifying patterns and deviations from patterns​ UR - https://books.google.es/books?id=hpHqDAAAQBAJ&lpg=PP1&dq=Big%20Data%20and%20Learning%20Analytics%20in%20Higher%20Education%20Current%20Theory%20and%20Practice&hl=es&pg=PP1#v=onepage&q=Big%20Data%20and%20Learning%20Analytics%20in%20Higher%20Education%20Current%20Theory%20and%20Practice&f=false ER -