The term 'learning analytics' is defined as the measurement, collection, analysis, and reporting of information about learners and their contexts for the purposes of understanding and optimizing learning. In recent years learning analytics has emerged as a promising area of research that trails the digital footprint of the learners and extracts useful knowledge from educational databases to understand students’ progress and success. With the availability of an increased amount of data, potential benefits of learning analytics can be far-reaching to all stakeholders in education including students, teachers, leaders, and policymakers. Educators firmly believe that, if properly harnessed, learning analytics will be an indispensable tool to enhance the teaching-learning process, narrow the achievement gap, and improve the quality of education.
Many investigations have been carried out and disseminated in the literature and studies related to learning analytics are growing exponentially. This book documents recent attempts to conduct systematic, prodigious and multidisciplinary research in learning analytics and present their findings and identify areas for further research and development. The book also unveils the distinguished and exemplary works by educators and researchers in the field highlighting the current trends, privacy and ethical issues, creative and unique approaches, innovative methods, frameworks, and theoretical and practical aspects of learning analytics.
Contributors are: Arif Altun, Alexander Amigud, Dongwook An, Mirella Atherton, Robert Carpenter, Martin Ebner, John Fritz, Yoshiko Goda, Yasemin Gulbahar, Junko Handa, Dirk Ifenthaler, Yumi Ishige, Il-Hyun Jo, Kosuke Kaneko, Selcan Kilis, Daniel Klasen, Mehmet Kokoç, Shin'ichi Konomi, Philipp Leitner, ChengLu Li, Min Liu, Karin Maier, Misato Oi, Fumiya Okubo, Xin Pan, Zilong Pan, Clara Schumacher, Yi Shi, Atsushi Shimada, Yuta Taniguchi, Masanori Yamada, and Wenting Zou.
Chapter 10 Implementation of a Learning Analytics System in a Productive Higher Education Environment
Chapter 11 Discourse Analysis Visualization Based on Community of Inquiry Framework
Chapter 12 Learning Support Systems Based on Cohesive Learning Analytics
Chapter 13 The Learning Analytics and Flipped PBL for Tool-Design Learning
Chapter 14 Learning Analytics Cockpit for MOOC Platforms
Myint Swe Khine, Ed.D. (2001), Curtin University of Technology, is Professor at Emirates College for Advanced Education, United Arab Emirates. He has published widely in international refereed academic journals and edited several books, including International Trends in Educational Assessment: Emerging Issues and Practices (Brill | Sense, 2019).
List of Figures and Tables Notes on Contributors
PART 1: Introduction
1 Big Data Analytics in Education for Dynamic Personalised Learning Design Myint Swe Khine
PART 2: Trends in Learning Analytics
2 Post-Traditional Learning Analytics: How Data and Information Technology Transform Learning Environment Alexander Amigud 3 The Use of Analytics for Educational Purposes: A Review of Literature from 2015 to Present Min Liu, Zilong Pan, Xin Pan, Dongwook An, Wenting Zou, Chenglu Li and Yi Shi 4 A Snapshot of Research on Learning Analytics: A Systematic Review Selcan Kilis and Yasemin Gulbahar 5 The Benefits of Learning Analytics in Open and Distance Education: A Review of the Evidence Billy Tak-Ming Wong
PART 3: Pedagogical Applications of Learning Analytics
6 The New Smarts in Teaching and Learning Jon Mason, Stefan Popenici, Leigh Blackall and Peter Shaw 7 Following the Learners’ Traces: Profiling Learners and Visualizing the Learning Process for Building Better Learning Experiences Arif Altun and Mehmet Kokoç 8 Analytical Indicators for Profiling and Improving Engagement and Success of Vulnerable Participants Mirella Atherton 9 Triangulating Student Engagement with “Built & Bought” Learning Analytics John Fritz and Robert Carpenter
PART 4: Learning Analytics and Educational Research
10 Implementation of a Learning Analytics System in a Productive Higher Education Environment Clara Schumacher, Daniel Klasen and Dirk Ifenthaler 11 Discourse Analysis Visualization Based on Community of Inquiry Framework Masanori Yamada, Yoshiko Goda, Kosuke Kaneko, Junko Handa and Yumi Ishige 12 Learning Support Systems Based on Cohesive Learning Analytics Fumiya Okubo, Masanori Yamada, Misato Oi, Atsushi Shimada, Yuta Taniguchi and Shin’ichi Konomi 13 The Learning Analytics and Flipped PBL for Tool-Design Learning Il-Hyun Jo 14 Learning Analytics Cockpit for MOOC Platforms Karin Maier, Philipp Leitner and Martin Ebner
All interested in the field of learning analytics and anyone concerned with improvement of teaching and learning with the use of education data.