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Emerging Trends in Learning Analytics : Leveraging the Power of Education Data

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Title: Emerging Trends in Learning Analytics : Leveraging the Power of Education Data
Description: 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.
Authors: Myint Swe Khine
Resource Type: eBook.
Subjects: Education--Data processing, Education--Research--Statistical methods, Learning--Evaluation, Educational evaluation
Categories: EDUCATION / Research
Database: eBook Collection (EBSCOhost)
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  Data: 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.
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        Scheme: ddc
        Type: prePub
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      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Education--Data processing
        Type: general
      – SubjectFull: Education--Research--Statistical methods
        Type: general
      – SubjectFull: Learning--Evaluation
        Type: general
      – SubjectFull: Educational evaluation
        Type: general
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      – TitleFull: Emerging Trends in Learning Analytics : Leveraging the Power of Education Data
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            – D: 01
              M: 01
              Type: published
              Y: 2019
            – D: 06
              M: 06
              Type: profile
              Y: 2019
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              Value: 9789004399273
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