Big Data and Learning Analytics in Higher Education - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Big Data and Learning Analytics in Higher Education write by Ben Kei Daniel. This book was released on 2016-08-27. Big Data and Learning Analytics in Higher Education available in PDF, EPUB and Kindle. 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
Big Data on Campus - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Big Data on Campus write by Karen L. Webber. This book was released on 2020-11-03. Big Data on Campus available in PDF, EPUB and Kindle. Webber, Henry Y. Zheng, Ying Zhou
Adoption of Data Analytics in Higher Education Learning and Teaching
Adoption of Data Analytics in Higher Education Learning and Teaching - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Adoption of Data Analytics in Higher Education Learning and Teaching write by Dirk Ifenthaler. This book was released on 2020-08-10. Adoption of Data Analytics in Higher Education Learning and Teaching available in PDF, EPUB and Kindle. 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
Learning Analytics in Higher Education - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Learning Analytics in Higher Education write by Jaime Lester. This book was released on 2018-08-06. Learning Analytics in Higher Education available in PDF, EPUB and Kindle. 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.
Advancing the Power of Learning Analytics and Big Data in Education
Advancing the Power of Learning Analytics and Big Data in Education - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Advancing the Power of Learning Analytics and Big Data in Education write by Azevedo, Ana. This book was released on 2021-03-19. Advancing the Power of Learning Analytics and Big Data in Education available in PDF, EPUB and Kindle. The term learning analytics is used in the context of the use of analytics in e-learning environments. Learning analytics is used to improve quality. It uses data about students and their activities to provide better understanding and to improve student learning. The use of learning management systems, where the activity of the students can be easily accessed, potentiated the use of learning analytics to understand their route during the learning process, help students be aware of their progress, and detect situations where students can give up the course before its completion, which is a growing problem in e-learning environments. Advancing the Power of Learning Analytics and Big Data in Education provides insights concerning the use of learning analytics, the role and impact of analytics on education, and how learning analytics are designed, employed, and assessed. The chapters will discuss factors affecting learning analytics such as human factors, geographical factors, technological factors, and ethical and legal factors. This book is ideal for teachers, administrators, teacher educators, practitioners, stakeholders, researchers, academicians, and students interested in the use of big data and learning analytics for improved student success and educational environments.
