Emerging trends in learning analytics : leveraging the power of education data /
Emerging trends in learning analytics : leveraging the power of education data /
edited by Myint Swe Khine.
- 1 online resource.
- Contemporary approaches to research in learning innovations 12 Educational Research E-Books Online, Collection 2019, ISBN: 9789004390836 .
- Contemporary Approaches to Research in Learning Innovations 012. Educational Research E-Books Online, Collection 2019, ISBN: 9789004390836. .
Includes bibliographical references.
Front Matter -- Copyright page -- List of Figures and Tables -- Notes on Contributors -- Introduction -- Big Data Analytics in Education for Dynamic Personalised Learning Design / Trends in Learning Analytics -- Post-Traditional Learning Analytics / The Use of Analytics for Educational Purposes / A Snapshot of Research on Learning Analytics / The Benefits of Learning Analytics in Open and Distance Education / Pedagogical Applications of Learning Analytics -- The New Smarts in Teaching and Learning / Following the Learners’ Traces / Analytical Indicators for Profiling and Improving Engagement and Success of Vulnerable Participants / Triangulating Student Engagement with “Built and Bought” Learning Analytics / Learning Analytics and Educational Research -- Implementation of a Learning Analytics System in a Productive Higher Education Environment / Discourse Analysis Visualization Based on Community of Inquiry Framework / Learning Support Systems Based on Cohesive Learning Analytics / The Learning Analytics and Flipped PBL for Tool-Design Learning / Learning Analytics Cockpit for MOOC Platforms / Myint Swe Khine -- Alexander Amigud -- Min Liu , Zilong Pan , Xin Pan , Dongwook An , Wenting Zou , Chenglu Li and Yi Shi -- Selcan Kilis and Yasemin Gulbahar -- Billy Tak-Ming Wong -- Jon Mason , Stefan Popenici , Leigh Blackall and Peter Shaw -- Arif Altun and Mehmet Kokoç -- Mirella Atherton -- John Fritz and Robert Carpenter -- Clara Schumacher , Daniel Klasen and Dirk Ifenthaler -- Masanori Yamada , Yoshiko Goda , Kosuke Kaneko , Junko Handa and Yumi Ishige -- Fumiya Okubo , Masanori Yamada , Misato Oi , Atsushi Shimada , Yuta Taniguchi and Shin’ichi Konomi -- Il-Hyun Jo -- Karin Maier , Philipp Leitner and Martin Ebner.
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.
9789004399273
10.1163/9789004399273 DOI
2019005549
Education--Research--Statistical methods.
Education--Data processing.
Learning--Evaluation.
Educational evaluation.
LB1028.43 / .E448 2019
370.72
Includes bibliographical references.
Front Matter -- Copyright page -- List of Figures and Tables -- Notes on Contributors -- Introduction -- Big Data Analytics in Education for Dynamic Personalised Learning Design / Trends in Learning Analytics -- Post-Traditional Learning Analytics / The Use of Analytics for Educational Purposes / A Snapshot of Research on Learning Analytics / The Benefits of Learning Analytics in Open and Distance Education / Pedagogical Applications of Learning Analytics -- The New Smarts in Teaching and Learning / Following the Learners’ Traces / Analytical Indicators for Profiling and Improving Engagement and Success of Vulnerable Participants / Triangulating Student Engagement with “Built and Bought” Learning Analytics / Learning Analytics and Educational Research -- Implementation of a Learning Analytics System in a Productive Higher Education Environment / Discourse Analysis Visualization Based on Community of Inquiry Framework / Learning Support Systems Based on Cohesive Learning Analytics / The Learning Analytics and Flipped PBL for Tool-Design Learning / Learning Analytics Cockpit for MOOC Platforms / Myint Swe Khine -- Alexander Amigud -- Min Liu , Zilong Pan , Xin Pan , Dongwook An , Wenting Zou , Chenglu Li and Yi Shi -- Selcan Kilis and Yasemin Gulbahar -- Billy Tak-Ming Wong -- Jon Mason , Stefan Popenici , Leigh Blackall and Peter Shaw -- Arif Altun and Mehmet Kokoç -- Mirella Atherton -- John Fritz and Robert Carpenter -- Clara Schumacher , Daniel Klasen and Dirk Ifenthaler -- Masanori Yamada , Yoshiko Goda , Kosuke Kaneko , Junko Handa and Yumi Ishige -- Fumiya Okubo , Masanori Yamada , Misato Oi , Atsushi Shimada , Yuta Taniguchi and Shin’ichi Konomi -- Il-Hyun Jo -- Karin Maier , Philipp Leitner and Martin Ebner.
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.
9789004399273
10.1163/9789004399273 DOI
2019005549
Education--Research--Statistical methods.
Education--Data processing.
Learning--Evaluation.
Educational evaluation.
LB1028.43 / .E448 2019
370.72