Big Data And Learning Analytics In Higher Education
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Big Data And Learning Analytics In Higher Education
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Author : Ben Kei Daniel
language : en
Publisher: Springer
Release Date : 2016-08-27
Big Data And Learning Analytics In Higher Education written by Ben Kei Daniel and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-27 with Education categories.
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.
Big Data On Campus
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Author : Karen L. Webber
language : en
Publisher: Johns Hopkins University Press
Release Date : 2020-11-03
Big Data On Campus written by Karen L. Webber and has been published by Johns Hopkins University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-03 with Education categories.
How data-informed decision making can make colleges and universities more effective institutions. The continuing importance of data analytics is not lost on higher education leaders, who face a multitude of challenges, including increasing operating costs, dwindling state support, limits to tuition increases, and increased competition from the for-profit sector. To navigate these challenges, savvy leaders must leverage data to make sound decisions. In Big Data on Campus, leading data analytics experts and higher ed leaders show the role that analytics can play in the better administration of colleges and universities. Aimed at senior administrative leaders, practitioners of institutional research, technology professionals, and graduate students in higher education, the book opens with a conceptual discussion of the roles that data analytics can play in higher education administration. Subsequent chapters address recent developments in technology, the rapid accumulation of data assets, organizational maturity in building analytical capabilities, and methodological advancements in developing predictive and prescriptive analytics. Each chapter includes a literature review of the research and application of analytics developments in their respective functional areas, a discussion of industry trends, examples of the application of data analytics in their decision process, and other related issues that readers may wish to consider in their own organizational environment to find opportunities for building robust data analytics capabilities. Using a series of focused discussions and case studies, Big Data on Campus helps readers understand how analytics can support major organizational functions in higher education, including admission decisions, retention and enrollment management, student life and engagement, academic and career advising, student learning and assessment, and academic program planning. The final section of the book addresses major issues and human factors involved in using analytics to support decision making; the ethical, cultural, and managerial implications of its use; the role of university leaders in promoting analytics in decision making; and the need for a strong campus community to embrace the analytics revolution. Contributors: Rana Glasgal, J. Michael Gower, Tom Gutman, Brian P. Hinote, Braden J. Hosch, Aditya Johri, Christine M. Keller, Carrie Klein, Jaime Lester, Carrie Hancock Marcinkevage, Gail B. Marsh, Susan M. Menditto, Jillian N. Morn, Valentina Nestor, Cathy O'Bryan, Huzefa Rangwala, Timothy Renick, Charles Tegen, Rachit Thariani, Chris Tompkins, Lindsay K. Wayt, Karen L. Webber, Henry Y. Zheng, Ying Zhou
Learning Analytics In Higher Education
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Author : Jaime Lester
language : en
Publisher: Routledge
Release Date : 2018-08-06
Learning Analytics In Higher Education written by Jaime Lester and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-06 with Education categories.
Learning Analytics in Higher Education provides a foundational understanding of how learning analytics is defined, what barriers and opportunities exist, and how it can be used to improve practice, including strategic planning, course development, teaching pedagogy, and student assessment. Well-known contributors provide empirical, theoretical, and practical perspectives on the current use and future potential of learning analytics for student learning and data-driven decision-making, ways to effectively evaluate and research learning analytics, integration of learning analytics into practice, organizational barriers and opportunities for harnessing Big Data to create and support use of these tools, and ethical considerations related to privacy and consent. Designed to give readers a practical and theoretical foundation in learning analytics and how data can support student success in higher education, this book is a valuable resource for scholars and administrators.
Smart Sensors At The Iot Frontier
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Author : Hiroto Yasuura
language : en
Publisher: Springer
Release Date : 2017-05-29
Smart Sensors At The Iot Frontier written by Hiroto Yasuura and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-29 with Technology & Engineering categories.
This book describes technology used for effective sensing of our physical world and intelligent processing techniques for sensed information, which are essential to the success of Internet of Things (IoT). The authors provide a multidisciplinary view of sensor technology from materials, process, circuits, to big data domains and they showcase smart sensor systems in real applications including smart home, transportation, medical, environmental, agricultural, etc. Unlike earlier books on sensors, this book provides a “global” view on smart sensors covering abstraction levels from device, circuit, systems, and algorithms.
Big Data In Education
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Author : Ben Williamson
language : en
Publisher: SAGE
Release Date : 2017-07-24
Big Data In Education written by Ben Williamson and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-24 with Education categories.
Big data has the power to transform education and educational research. Governments, researchers and commercial companies are only beginning to understand the potential that big data offers in informing policy ideas, contributing to the development of new educational tools and innovative ways of conducting research. This cutting-edge overview explores the current state-of-play, looking at big data and the related topic of computer code to examine the implications for education and schooling for today and the near future. Key topics include: · The role of learning analytics and educational data science in schools · A critical appreciation of code, algorithms and infrastructures · The rise of ‘cognitive classrooms’, and the practical application of computational algorithms to learning environments · Important digital research methods issues for researchers This is essential reading for anyone studying or working in today′s education environment!
Applied Degree Education And The Future Of Work
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Author : Christina Hong
language : en
Publisher: Springer Nature
Release Date : 2020-05-16
Applied Degree Education And The Future Of Work written by Christina Hong and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-16 with Education categories.
This edited volume sets the stage for discussion on Education 4.0, with a focus on applied degree education and the future of work. Education 4.0 refers to the shifts in the education sector in response to Industry 4.0 where digital transformation is impacting the ways in which the world of work and our everyday lives are becoming increasingly automated. In the applied degree sector, significant change and transformation is occurring as leaders, educators and partners evolve smart campus environments to include blended learning, artificial intelligence, data analytics, BYOD devices, process automation and engage in curriculum renewal for and with industries and professions. This volume aims to profile and enhance the contribution of applied educational practice and research particularly in the applied degree sector and includes contributions that show case real world outcomes with students and industry as partners. This edited volume includes a wide range of topics, such as rethinking the role of education and educators; curriculum and the future of work; industrial partnership, collaboration and work integrated learning; vocational and professional practices; students, industry and professions as partners; employability skills and qualities for the 21st century world of work; innovative pedagogy and instructional design; adaptive learning technologies; and data analytics, assessment and feedback. The contributors come from different parts of the world in higher education, including, Canada, China, Finland, Germany, Hong Kong, Italy, Macau, Singapore and the United Kingdom.
Adoption Of Data Analytics In Higher Education Learning And Teaching
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Author : Dirk Ifenthaler
language : en
Publisher: Springer Nature
Release Date : 2020-08-10
Adoption Of Data Analytics In Higher Education Learning And Teaching written by Dirk Ifenthaler and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-10 with Education categories.
The book aims to advance global knowledge and practice in applying data science to transform higher education learning and teaching to improve personalization, access and effectiveness of education for all. Currently, higher education institutions and involved stakeholders can derive multiple benefits from educational data mining and learning analytics by using different data analytics strategies to produce summative, real-time, and predictive or prescriptive insights and recommendations. Educational data mining refers to the process of extracting useful information out of a large collection of complex educational datasets while learning analytics emphasizes insights and responses to real-time learning processes based on educational information from digital learning environments, administrative systems, and social platforms. This volume provides insight into the emerging paradigms, frameworks, methods and processes of managing change to better facilitate organizational transformation toward implementation of educational data mining and learning analytics. It features current research exploring the (a) theoretical foundation and empirical evidence of the adoption of learning analytics, (b) technological infrastructure and staff capabilities required, as well as (c) case studies that describe current practices and experiences in the use of data analytics in higher education.
Learning With Big Data
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Author : Viktor Mayer-Schönberger
language : en
Publisher: HarperCollins
Release Date : 2014-03-04
Learning With Big Data written by Viktor Mayer-Schönberger and has been published by HarperCollins this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03-04 with Education categories.
Homework assignments that learn from students. Courses tailored to fit individual pupils. Textbooks that talk back. This is tomorrow’s education landscape, thanks to the power of big data. These advances go beyond online courses. As the New York Times-bestselling authors of Big Data explain, the truly fascinating changes are actually occurring in how we measure students’ progress and how we can use that data to improve education for everyone, in real time, both on- and offline. Learning with Big Data offers an eye-opening, insight-packed tour through these new trends, for educators, administrators, and readers interested in the latest developments in business and technology.
Learning Analytics Fundaments Applications And Trends
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Author : Alejandro Peña-Ayala
language : en
Publisher: Springer
Release Date : 2017-02-17
Learning Analytics Fundaments Applications And Trends written by Alejandro Peña-Ayala and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-17 with Technology & Engineering categories.
This book provides a conceptual and empirical perspective on learning analytics, its goal being to disseminate the core concepts, research, and outcomes of this emergent field. Divided into nine chapters, it offers reviews oriented on selected topics, recent advances, and innovative applications. It presents the broad learning analytics landscape and in-depth studies on higher education, adaptive assessment, teaching and learning. In addition, it discusses valuable approaches to coping with personalization and huge data, as well as conceptual topics and specialized applications that have shaped the current state of the art. By identifying fundamentals, highlighting applications, and pointing out current trends, the book offers an essential overview of learning analytics to enhance learning achievement in diverse educational settings. As such, it represents a valuable resource for researchers, practitioners, and students interested in updating their knowledge and finding inspirations for their future work.