Adoption Of Data Analytics In Higher Education Learning And Teaching
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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.
Adoption Of Data Analytics In Higher Education Learning And Teching
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Author : Dirk Ifenthaler
language : en
Publisher:
Release Date : 2020
Adoption Of Data Analytics In Higher Education Learning And Teching written by Dirk Ifenthaler and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Educational technology 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 Analytics In Higher Education
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Author : Jaime Lester
language : en
Publisher: John Wiley & Sons
Release Date : 2017-12-21
Learning Analytics In Higher Education written by Jaime Lester and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-21 with Education categories.
Learning analytics (or educational big data) tools are increasingly being deployed on campuses to improve student performance, retention and completion, especially when those metrics are tied to funding. Providing personalized, real-time, actionable feedback through mining and analysis of large data sets, learning analytics can illuminate trends and predict future outcomes. While promising, there is limited and mixed empirical evidence related to its efficacy to improve student retention and completion. Further, learning analytics tools are used by a variety of people on campus, and as such, its use in practice may not align with institutional intent. This monograph delves into the research, literature, and issues associated with learning analytics implementation, adoption, and use by individuals within higher education institutions. With it, readers will gain a greater understanding of the potential and challenges related to implementing, adopting, and integrating these systems on their campuses and within their classrooms and advising sessions. This is the fifth issue of the 43rd volume of the Jossey-Bass series ASHE Higher Education Report. Each monograph is the definitive analysis of a tough higher education issue, based on thorough research of pertinent literature and institutional experiences. Topics are identified by a national survey. Noted practitioners and scholars are then commissioned to write the reports, with experts providing critical reviews of each manuscript before publication.
Big Data And Learning Analytics In Higher Education
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Author : Ben Kei Daniel
language : en
Publisher: Springer
Release Date : 2018-04-21
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 2018-04-21 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.
Developing Effective Educational Experiences Through Learning Analytics
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Author : Anderson, Mark
language : en
Publisher: IGI Global
Release Date : 2016-04-07
Developing Effective Educational Experiences Through Learning Analytics written by Anderson, Mark and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-07 with Education categories.
The quality of students’ learning experiences is a critical concern for all higher education institutions. With the assistance of modern technological advances, educational establishments have the capability to better understand the strengths and weaknesses of their learning programs. Developing Effective Educational Experiences through Learning Analytics is a pivotal reference source that focuses on the adoption of data mining and analysis techniques in academic institutions, examining how this collected information is utilized to improve the outcome of student learning. Highlighting the relevance of data analytics to current educational practices, this book is ideally designed for researchers, practitioners, and professionals actively involved in higher education settings.
Online Learning Analytics
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Author : Jay Liebowitz
language : en
Publisher: CRC Press
Release Date : 2021-12-14
Online Learning Analytics written by Jay Liebowitz and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-14 with Education categories.
"In our increasingly digitally enabled education world, analytics used ethically, strategically, and with care holds the potential to help more and more diverse students be more successful on higher education journeys than ever before. Jay Liebowitz and a cadre of the fields best ‘good trouble’ makers in this space help shine a light on the possibilities, potential challenges, and the power of learning together in this work." —Mark David Milliron, Ph.D., Senior Vice President and Executive Dean of the Teachers College, Western Governors University Due to the COVID-19 pandemic and its aftereffects, we have begun to enter the "new normal" of education. Instead of online learning being an "added feature" of K–12 schools and universities worldwide, it will be incorporated as an essential feature in education. There are many questions and concerns from parents, students, teachers, professors, administrators, staff, accrediting bodies, and others regarding the quality of virtual learning and its impact on student learning outcomes. Online Learning Analytics is conceived on trying to answer the questions of those who may be skeptical about online learning. Through better understanding and applying learning analytics, we can assess how successful learning and student/faculty engagement, as examples, can contribute towards producing the educational outcomes needed to advance student learning for future generations. Learning analytics has proven to be successful in many areas, such as the impact of using learning analytics in asynchronous online discussions in higher education. To prepare for a future where online learning plays a major role, this book examines: Data insights for improving curriculum design, teaching practice, and learning Scaling up learning analytics in an evidence-informed way The role of trust in online learning. Online learning faces very real philosophical and operational challenges. This book addresses areas of concern about the future of education and learning. It also energizes the field of learning analytics by presenting research on a range of topics that is broad and recognizes the humanness and depth of educating and learning.
Learning Analytics In Higher Education
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Author : John Zilvinskis
language : en
Publisher: John Wiley & Sons
Release Date : 2017-10-16
Learning Analytics In Higher Education written by John Zilvinskis and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-16 with Education categories.
The goal of this volume is to introduce the reader to a basic understanding of learning analytics and the types of projects and initiatives that several leading practitioners have adopted and adapted, providing substantive examples of implementation, and expert learnings on some of the more nuanced issues related to this topic"--Page 5.
The Analytics Revolution In Higher Education
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Author : Jonathan S. Gagliardi
language : en
Publisher: Taylor & Francis
Release Date : 2023-07-03
The Analytics Revolution In Higher Education written by Jonathan S. Gagliardi and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-03 with Education categories.
Co-published with and In this era of “Big Data,” institutions of higher education are challenged to make the most of the information they have to improve student learning outcomes, close equity gaps, keep costs down, and address the economic needs of the communities they serve at the local, regional, and national levels. This book helps readers understand and respond to this “analytics revolution,” examining the evolving dynamics of the institutional research (IR) function, and the many audiences that institutional researchers need to serve.Internally, there is a growing need among senior leaders, administrators, faculty, advisors, and staff for decision analytics that help craft better resource strategies and bring greater efficiencies and return-on-investment for students and families. Externally, state legislators, the federal government, and philanthropies demand more forecasting and more evidence than ever before. These demands require new and creative responses, as they are added to previous demands, rather than replacing them, nor do they come with additional resources to produce the analysis to make data into actionable improvements. Thus the IR function must become that of teacher, ensuring that data and analyses are accurate, timely, accessible, and compelling, whether produced by an IR office or some other source. Despite formidable challenges, IR functions have begun to leverage big data and unlock the power of predictive tools and techniques, contributing to improved student outcomes.
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.
Data Analytics For Beginners
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Author : Florino Alfeche
language : en
Publisher:
Release Date : 2017-10-08
Data Analytics For Beginners written by Florino Alfeche and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-08 with categories.
Data Analytics For Beginners: The Ultimate Guide To Learn and Master Data Analysis, How to Integrate Analytics into Your Business.Working with big data using data mining and analytics is rapidly becoming common in the commercial sector. Tools and techniques once confined to research laboratories are being adopted by forward-looking industries, most notably those serving end users through online systems. Higher education institutions are applying learning analytics to improve the services they provide and to improve visible and measurable targets such as grades and retention. K-12 schools and school districts are starting to adopt such institution-level analyses for detecting areas for improvement, setting policies, and measuring results. Now, with advances in adaptive learning systems, possibilities exist to harness the power of feedback loops at the level of individual teachers and students. Measuring and making visible students' learning and assessment activities open up the possibility for students to develop skills in monitoring their own learning and to see directly how their effort improves their success. Teachers gain views into students' performance that help them adapt their teaching or initiate interventions in the form of tutoring, tailored assignments, and the like. Adaptive learning systems enable educators to quickly see the effectiveness of their adaptations and interventions, providing feedback for continuous improvement. Researchers and developers can more rapidly compare versions A and B of designs, products, and approaches to teaching and learning, enabling the state of the art and the state of the practice to keep pace with the rapid pace of adoption of online and blended learning environments. Open source tools for adaptive learning systems, commercial offerings, and increased understanding of what data reveal are leading to fundamental shifts in teaching and learning systems. As content moves online and mobile devices for interacting with content enable teaching to be always on, educational data mining and learning analytics will enable learning to be always assessed. Educators at all levels will benefit from understanding the possibilities of the developments described in the use of big data herein.