Big Data and Learning Analytics in Higher Education

Author: Ben Kei Daniel
Publisher: Springer
ISBN: 3319065203
Format: PDF, Mobi
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​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​.

Learning Analytics in Higher Education

Author: Lester
Publisher: John Wiley & Sons
ISBN: 1119478634
Format: PDF, Kindle
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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.

Learning Analytics in Higher Education

Author: Jaime Lester
Publisher: Routledge
ISBN: 1351400525
Format: PDF, Mobi
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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.

Data Mining and Learning Analytics

Author: Samira ElAtia
Publisher: John Wiley & Sons
ISBN: 1118998235
Format: PDF
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Addresses the impacts of data mining on education and reviews applications in educational research teaching, and learning This book discusses the insights, challenges, issues, expectations, and practical implementation of data mining (DM) within educational mandates. Initial series of chapters offer a general overview of DM, Learning Analytics (LA), and data collection models in the context of educational research, while also defining and discussing data mining’s four guiding principles— prediction, clustering, rule association, and outlier detection. The next series of chapters showcase the pedagogical applications of Educational Data Mining (EDM) and feature case studies drawn from Business, Humanities, Health Sciences, Linguistics, and Physical Sciences education that serve to highlight the successes and some of the limitations of data mining research applications in educational settings. The remaining chapters focus exclusively on EDM’s emerging role in helping to advance educational research—from identifying at-risk students and closing socioeconomic gaps in achievement to aiding in teacher evaluation and facilitating peer conferencing. This book features contributions from international experts in a variety of fields. Includes case studies where data mining techniques have been effectively applied to advance teaching and learning Addresses applications of data mining in educational research, including: social networking and education; policy and legislation in the classroom; and identification of at-risk students Explores Massive Open Online Courses (MOOCs) to study the effectiveness of online networks in promoting learning and understanding the communication patterns among users and students Features supplementary resources including a primer on foundational aspects of educational mining and learning analytics Data Mining and Learning Analytics: Applications in Educational Research is written for both scientists in EDM and educators interested in using and integrating DM and LA to improve education and advance educational research.

The Analytics Revolution in Higher Education

Author: Jonathan S. Gagliardi
Publisher: Stylus Publishing, LLC
ISBN: 1620365790
Format: PDF, ePub, Mobi
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Co-published with AIR. img src="https://www.presswarehouse.com/sites/stylus/images/airlogo1.jpg"/a Co-published with ACE. img src="https://www.presswarehouse.com/sites/stylus/images/ACElogo1.jpg"/a 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.

Hochschuldidaktik der Informatik HDI 2018

Author: Nadine Bergner
Publisher: Universitätsverlag Potsdam
ISBN: 3869564350
Format: PDF, Mobi
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Die 8. Fachtagung für Hochschuldidaktik der Informatik (HDI) fand im September 2018 zusammen mit der Deutschen E-Learning Fachtagung Informatik (DeLFI) unter dem gemeinsamen Motto „Digitalisierungswahnsinn? - Wege der Bildungstransformationen“ in Frankfurt statt. Dabei widmet sich die HDI allen Fragen der informatischen Bildung im Hochschulbereich. Schwerpunkte bildeten in diesem Jahr u. a.: - Analyse der Inhalte und anzustrebenden Kompetenzen in Informatikveranstaltungen - Programmieren lernen &Einstieg in Softwareentwicklung - Spezialthemen: Data Science, Theoretische Informatik und Wissenschaftliches Arbeiten Die Fachtagung widmet sich ausgewählten Fragestellungen dieser Themenkomplexe, die durch Vorträge ausgewiesener Experten und durch eingereichte Beiträge intensiv behandelt werden.

Learning Analytics Implications for Higher Education

Author: Wolfgang Greller
Publisher: BoD – Books on Demand
ISBN: 3743161788
Format: PDF, Kindle
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This Special Issue gathers recent experiences and research examples concerning the use of Learning Analytics in higher education contexts of online and blended learning. All featured articles span across technically enabled data collection and processing/analysis, on the one hand, and, pedagogically motivated decision making by learners, teachers and other stakeholders on the other.

Developing Effective Educational Experiences through Learning Analytics

Author: Anderson, Mark
Publisher: IGI Global
ISBN: 1466699841
Format: PDF
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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.

Lernen mit Big Data

Author: Viktor Mayer-Schönberger
Publisher: Redline Wirtschaft
ISBN: 3864143020
Format: PDF, Mobi
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Was heute noch undenkbar scheint, ist morgen schon Alltag – sprechende Übungsbücher, Schulaufgaben, die von den Schülern lernen. Schneller als gedacht, wird Big Data Einzug in Schulen und Klassenzimmer halten, so die These der beiden Experten und Erfolgsautoren Viktor Mayer-Schönberger und Kenneth Cukier. Und damit das Schulsystem und das Lernen von Grund auf verändern. Die beiden Autoren von Big Data erklären, welche Neuheiten uns erwarten. Und zeigen, dass es nicht nur positiv ist, den Fortschritt der Schüler und Studenten immer besser messen zu können. Vor lauter PISA und Rankings bleibt oft das Wesentliche auf der Strecke – eine gute Bildung. Die Gefahr ist, dass das Lernen von der Quantität der Daten dominiert wird, und nicht von der Qualität, von Kreativität oder von Ideen. Sie plädieren daher eindringlich dafür, unsere Bildungssysteme schnellstens zukunftsfähig zu machen.

Building a Smarter University

Author: Jason E. Lane
Publisher: SUNY Press
ISBN: 143845452X
Format: PDF, ePub
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Demonstrates how universities can use Big Data to enhance operations and management, improve the education pipeline, and educate the next generation of data scientists. The Big Data movement and the renewed focus on data analytics are transforming everything from healthcare delivery systems to the way cities deliver services to residents. Now is the time to examine how this Big Data could help build smarter universities. While much of the cutting-edge research that is being done with Big Data is happening at colleges and universities, higher education has yet to turn the digital mirror on itself to advance the academic enterprise. Institutions can use the huge amounts of data being generated to improve the student learning experience, enhance research initiatives, support effective community outreach, and develop campus infrastructure. This volume focuses on three primary themes related to creating a smarter university: refining the operations and management of higher education institutions, cultivating the education pipeline, and educating the next generation of data scientists. Through an analysis of these issues, the contributors address how universities can foster innovation and ingenuity in the academy. They also provide scholarly and practical insights in order to frame these topics for an international discussion.