Big Data and Learning Analytics in Higher Education

Current Theory and Practice
1. Auflage 2017
ISBN: 978-3-319-06519-9
Verlag: Springer International Publishing

Buch, Englisch, 272 Seiten, HC runder Rücken kaschiert, Format (B × H): 160 mm x 241 mm, Gewicht: 606 g

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.

Zielgruppe

Research

Autoren/Hrsg.

Kei Daniel, Ben

Fachgebiete

• Sozialwissenschaften Pädagogik Lehrerausbildung, Unterricht & Didaktik E-Learning, Bildungstechnologie
• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein E-Learning
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken

Inhaltsverzeichnis

Theory and Practice.- Global challenges in higher education.- Technological trends in higher education.- Data Science.- Big data in higher education.- Learning analytics.- Big Data Platforms and Systems.- Analytical platforms.- Systems.- Databases.- Tools.- Visualization.- Dashboards.- Measurement and Methodologies.- Measures, indicators, metrics.- Data mining techniques.- Data capture.- Data tracking.- Metadata.- Methodologies.- Institutional Best Practices.- Case studies/best practices.- Polyicy implication on learning, teaching, and research.- Challenges and opportunities.- Future Trends.- Lessons learned.- Future perspectives in big data.- Conclusions.

Über Autor(innen)

Dr Ben Daniel is a Senior Lecturer in Higher Education, and heads the Educational Technology Group at the University of Otago—New Zealand. In 2007 he completed his Ph.D. jointly in Computer Science and Educational Technology at the University of Saskatchewan in Canada. 

Previously, Dr Daniel was a Lecturer and a Senior Health Research and Innovation Analyst with the Office of Associate Vice President Research-Health (University of Saskatchewan)/Vice President Research and Innovation (Saskatoon Health Region)—Saskatoon, Canada. For over a decade Dr Daniel taught undergraduate, postgraduate students, academic staff, and Senior Corporate Executives on Research Methodologies; Program Evaluation and Logic Modelling; Quality Improvement, Statistics and Biostatistics as well as Advanced Learning Technologies. 

An active researcher, Dr Daniel has published over 50 peer-reviewed publications (2 edited books, 2 authored book, 13 book chapters, 10 peer-reviewed journal articles, 26 peer-reviewed conference papers, 10 peer-reviewed workshops and posters, and over 10 technical reports).  His current research is focused generally on exploring the value of Big Data and learning analytics in influencing learning, teaching and research in the context of higher education. He is also investigating theories and praxis of teaching research methodologies in Higher Education and the corporate sector.