Educational Data Mining And Learning Analytics
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Data Mining And Learning Analytics
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Author : Samira ElAtia
language : en
Publisher: John Wiley & Sons
Release Date : 2016-09-06
Data Mining And Learning Analytics written by Samira ElAtia 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 2016-09-06 with Computers categories.
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.
Responsible Analytics And Data Mining In Education
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Author : Badrul H. Khan
language : en
Publisher: Routledge
Release Date : 2018-12-07
Responsible Analytics And Data Mining In Education written by Badrul H. Khan and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-07 with Computers categories.
Winner of two Outstanding Book Awards from the Association of Educational Communications and Technology (Culture, Learning, & Technology and Systems Thinking & Change divisions)! Rapid advancements in our ability to collect, process, and analyze massive amounts of data along with the widespread use of online and blended learning platforms have enabled educators at all levels to gain new insights into how people learn. Responsible Analytics and Data Mining in Education addresses the thoughtful and purposeful navigation, evaluation, and implementation of these emerging forms of educational data analysis. Chapter authors from around the world explore how data analytics can be used to improve course and program quality; how the data and its interpretations may inadvertently impact students, faculty, and institutions; the quality and reliability of data, as well as the accuracy of data-based decisions; ethical implications surrounding the collection, distribution, and use of student-generated data; and more. This volume unpacks and explores this complex issue through a systematic framework whose dimensions address the issues that must be considered before implementation of a new initiative or program.
Advancing The Power Of Learning Analytics And Big Data In Education
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Author : Azevedo, Ana
language : en
Publisher: IGI Global
Release Date : 2021-03-19
Advancing The Power Of Learning Analytics And Big Data In Education written by Azevedo, Ana and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-19 with Education categories.
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.
Educational Data Mining And Learning Analytics
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Author : Tai Tan Mai
language : en
Publisher: Springer
Release Date : 2023-11-11
Educational Data Mining And Learning Analytics written by Tai Tan Mai and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-11 with Education categories.
This book is the result of a collaboration between a human editor and an artificial intelligence algorithm to create a machine-generated literature overview of research articles analyzing Educational Data Mining and Learning Analytics. It’s a new publication format in which state-of-the-art computer algorithms are applied to select the most relevant articles published in Springer Nature journals and create machine-generated literature reviews by arranging the selected articles in a topical order and creating short summaries of these articles. The popularity of Educational Data Mining has grown among educators seeking more effective ways to monitor and incentivize student progress and engagement during the COVID-19 pandemic. This has led to increased interest within research communities. The book provides a comprehensive overview of state-of-the-art research in Education Data Mining and its applications. Each chapter includes case studies to support theoretical concepts. The book is of great interest for a wide range of audiences, including computer scientists and educational philosophers.
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 Analytics Goes To School
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Author : Andrew Krumm
language : en
Publisher: Routledge
Release Date : 2018-01-12
Learning Analytics Goes To School written by Andrew Krumm and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-12 with Education categories.
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.
Data Mining And Learning Analytics
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Author : Samira ElAtia
language : en
Publisher: John Wiley & Sons
Release Date : 2016-09-26
Data Mining And Learning Analytics written by Samira ElAtia 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 2016-09-26 with Computers categories.
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.
Handbook Of Educational Data Mining
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Author : Cristobal Romero
language : en
Publisher: CRC Press
Release Date : 2010-10-25
Handbook Of Educational Data Mining written by Cristobal Romero and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-10-25 with Business & Economics categories.
This handbook provides a thorough overview of the current state of knowledge in this area. The first part of the book includes nine surveys and tutorials on the principal data mining techniques that have been applied in education. The second part presents a set of 25 case studies that give a rich overview of the problems that EDM has addressed. With contributions by well-known researchers from a variety of fields, the book reflects the multidisciplinary nature of the EDM community. It helps education experts understand what types of questions EDM can address and helps data miners understand what types of questions are important to educational design and educational decision making.
Learning Analytics
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Author : Johann Ari Larusson
language : en
Publisher: Springer
Release Date : 2014-07-04
Learning Analytics written by Johann Ari Larusson and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-04 with Education categories.
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.
Utilizing Educational Data Mining Techniques For Improved Learning Emerging Research And Opportunities
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Author : Bhatt, Chintan
language : en
Publisher: IGI Global
Release Date : 2019-08-02
Utilizing Educational Data Mining Techniques For Improved Learning Emerging Research And Opportunities written by Bhatt, Chintan and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-02 with Education categories.
Modern education has increased its reach through ICT tools and techniques. To manage educational data with the help of modern artificial intelligence, data and web mining techniques on dedicated cloud or grid platforms for educational institutes can be used. By utilizing data science techniques to manage educational data, the safekeeping, delivery, and use of knowledge can be increased for better quality education. Utilizing Educational Data Mining Techniques for Improved Learning: Emerging Research and Opportunities is a critical scholarly resource that explores data mining and management techniques that promote the improvement and optimization of educational data systems. The book intends to provide new models, platforms, tools, and protocols in data science for educational data analysis and introduces innovative hybrid system models dedicated to data science. Including topics such as automatic assessment, educational analytics, and machine learning, this book is essential for IT specialists, data analysts, computer engineers, education professionals, administrators, policymakers, researchers, academicians, and technology experts.