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Author: Paul Prinsloo
Publisher: Springer Nature
ISBN: 9811907862
Category : Education
Languages : en
Pages : 131
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Book Description
This book explores and further expands on the rich history of theoretical and empirical research in open and distributed learning, and addresses the impact of the “data revolution” and the emergence of learning analytics on this increasingly diverse form of educational delivery. Following an introductory chapter that maps the book’s conceptual rationale, the book discusses the potential, challenges and practices of learning analytics in various open and distributed contexts. A concluding chapter briefly summarises the chapters before providing a tentative future research agenda for learning analytics in open and distributed environments.
Author: Paul Prinsloo
Publisher: Springer Nature
ISBN: 9811907862
Category : Education
Languages : en
Pages : 131
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Book Description
This book explores and further expands on the rich history of theoretical and empirical research in open and distributed learning, and addresses the impact of the “data revolution” and the emergence of learning analytics on this increasingly diverse form of educational delivery. Following an introductory chapter that maps the book’s conceptual rationale, the book discusses the potential, challenges and practices of learning analytics in various open and distributed contexts. A concluding chapter briefly summarises the chapters before providing a tentative future research agenda for learning analytics in open and distributed environments.
Author: Durak, Gürhan
Publisher: IGI Global
ISBN: 1668495287
Category : Education
Languages : en
Pages : 479
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Book Description
Maximizing student outcomes in education presents a significant challenge, as traditional assessment methods often fall short in providing actionable insights for improvement. Perspectives on Learning Analytics for Maximizing Student Outcomes addresses this challenge by offering a comprehensive solution. Edited by esteemed scholars Gürhan Durak and Serkan Çankaya, this book provides innovative knowledge and practical experiences on emerging technologies and processes in learning analytics. It covers topics such as data collection, visualization, predictive analytics, and ethical considerations, serving as a guide for academic scholars, technology enthusiasts, and educational institutions. This book empowers professionals and researchers to leverage learning analytics effectively, enabling data-informed decision-making, improved teaching practices, and tailored educational programs. By presenting best practices and future directions, it equips readers with the necessary tools to optimize learning environments and drive student success. With a focus on the transformative potential of learning analytics, this book propels education toward a more efficient and effective system that prioritizes student outcomes.
Author: Feng-Qi Lai
Publisher: Springer
ISBN: 3319389564
Category : Education
Languages : en
Pages : 244
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Book Description
This book explores trends in learning and knowledge analytics in open education, as explored in proceedings papers from AECT-LKAOE 2015 International Research Symposium. The chapters investigate various issues surrounding open education in all disciplines, such as learning design in open-ended learning environments, MOOCs (Massive Open Online Courses), learning analytics studies and applications, and technology and new media. The chapter authors provide guidance for how to design and develop most effective, efficient, and appealing instruction as well as suggesting learning strategies relevant to the open education era.
Author: Samira ElAtia
Publisher: John Wiley & Sons
ISBN: 1118998219
Category : Computers
Languages : en
Pages : 351
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Book Description
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.
Author: Johann Ari Larusson
Publisher: Springer
ISBN: 1461433053
Category : Education
Languages : en
Pages : 203
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Book Description
In education today, technology alone doesn't always lead to immediate success for students or institutions. In order to gauge the efficacy of educational technology, we need ways to measure the efficacy of educational practices in their own right. Through a better understanding of how learning takes place, we may work toward establishing best practices for students, educators, and institutions. These goals can be accomplished with learning analytics. Learning Analytics: From Research to Practice updates this emerging field with the latest in theories, findings, strategies, and tools from across education and technological disciplines. Guiding readers through preparation, design, and examples of implementation, this pioneering reference clarifies LA methods as not mere data collection but sophisticated, systems-based analysis with practical applicability inside the classroom and in the larger world. Case studies illustrate applications of LA throughout academic settings (e.g., intervention, advisement, technology design), and their resulting impact on pedagogy and learning. The goal is to bring greater efficiency and deeper engagement to individual students, learning communities, and educators, as chapters show diverse uses of learning analytics to: Enhance student and faculty performance. Improve student understanding of course material. Assess and attend to the needs of struggling learners. Improve accuracy in grading. Allow instructors to assess and develop their own strengths. Encourage more efficient use of resources at the institutional level. Researchers and practitioners in educational technology, IT, and the learning sciences will hail the information in Learning Analytics: From Research to Practice as a springboard to new levels of student, instructor, and institutional success.
Author: Andrew Krumm
Publisher: Routledge
ISBN: 1317307860
Category : Education
Languages : en
Pages : 275
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Book Description
Learning Analytics Goes to School presents a framework for engaging in education research and improving education practice through the use of newly available data sources and analytical approaches. The application of data-intensive research techniques to understanding and improving learning environments has been growing at a rapid pace. In this book, three leading researchers convey lessons from their own experiences—and the current state of the art in educational data mining and learning analytics more generally—by providing an explicit set of tools and processes for engaging in collaborative data-intensive improvement.
Author: Santi Caballé
Publisher: Academic Press
ISBN: 0128231270
Category : Computers
Languages : en
Pages : 427
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Book Description
Intelligent Systems and Learning Data Analytics in Online Education provides novel artificial intelligence (AI) and analytics-based methods to improve online teaching and learning. This book addresses key problems such as attrition and lack of engagement in MOOCs and online learning in general. This book explores the state of the art of artificial intelligence, software tools and innovative learning strategies to provide better understanding and solutions to the various challenges of current e-learning in general and MOOC education. In particular, Intelligent Systems and Learning Data Analytics in Online Education shares stimulating theoretical and practical research from leading international experts. This publication provides useful references for educational institutions, industry, academic researchers, professionals, developers, and practitioners to evaluate and apply. - Presents the application of innovative AI techniques to collaborative learning activities - Offers strategies to provide automatic and effective tutoring to students' activities - Offers methods to collect, analyze and correctly visualize learning data in educational environments
Author: Azevedo, Ana
Publisher: IGI Global
ISBN: 1799871045
Category : Education
Languages : en
Pages : 296
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Book Description
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.
Author: Niall Sclater
Publisher: Taylor & Francis
ISBN: 1317394569
Category : Education
Languages : en
Pages : 291
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Book Description
Learning Analytics Explained draws extensively from case studies and interviews with experts in order to discuss emerging applications of the new field of learning analytics. Educational institutions increasingly collect data on students and their learning experiences, a practice that helps enhance courses, identify learners who require support, and provide a more personalized learning experience. There is, however, a corresponding need for guidance on how to carry out institutional projects, intervene effectively with students, and assess legal and ethical issues. This book provides that guidance while also covering the evolving technical architectures, standards, and products within the field.
Author: Srinivasa K G
Publisher: Springer Nature
ISBN: 3030702588
Category : Education
Languages : en
Pages : 326
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Book Description
This book A Beginner’s Guide to Learning Analytics is designed to meet modern educational trends’ needs. It is addressed to readers who have no prior knowledge of learning analytics and functions as an introductory text to learning analytics for those who want to do more with evaluation/assessment in their organizations. The book is useful to all who need to evaluate their learning and teaching strategies. It aims to bring greater efficiency and deeper engagement to individual students, learning communities, and educators. Covered here are the key concepts linked to learning analytics for researchers and practitioners interested in learning analytics. This book helps those who want to apply analytics to learning and development programs and helps educational institutions to identify learners who require support and provide a more personalized learning experience. Like chapters show diverse uses of learning analytics to enhance student and faculty performance. It presents a coherent framework for the effective translation of learning analytics research for educational practice to its practical application in different educational domains. This book provides educators and researchers with the tools and frameworks to effectively make sense of and use data and analytics in their everyday practice. This book will be a valuable addition to researchers’ bookshelves.
