Responsible Analytics And Data Mining In Education

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Responsible Analytics and Data Mining in Education

Badrul H. Khan,Joseph Rene Corbeil,Maria Elena Corbeil
Responsible Analytics and Data Mining in Education Book PDF

Author : Badrul H. Khan,Joseph Rene Corbeil,Maria Elena Corbeil
Publisher : Routledge
Page : 292 pages
File Size : 51,5 Mb
Release : 2018-12-07
Category : Computers
ISBN : 9781351394673

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Responsible Analytics and Data Mining in Education by Badrul H. Khan,Joseph Rene Corbeil,Maria Elena Corbeil Pdf

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.

Data Mining and Learning Analytics

Samira ElAtia,Donald Ipperciel,Osmar R. Zaïane
Data Mining and Learning Analytics Book PDF

Author : Samira ElAtia,Donald Ipperciel,Osmar R. Zaïane
Publisher : John Wiley & Sons
Page : 320 pages
File Size : 45,7 Mb
Release : 2016-09-26
Category : Computers
ISBN : 9781118998236

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Data Mining and Learning Analytics by Samira ElAtia,Donald Ipperciel,Osmar R. Zaïane Pdf

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.

Adoption of Data Analytics in Higher Education Learning and Teaching

Dirk Ifenthaler,David Gibson
Adoption of Data Analytics in Higher Education Learning and Teaching Book PDF

Author : Dirk Ifenthaler,David Gibson
Publisher : Springer Nature
Page : 464 pages
File Size : 53,9 Mb
Release : 2020-08-10
Category : Education
ISBN : 9783030473921

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Adoption of Data Analytics in Higher Education Learning and Teaching by Dirk Ifenthaler,David Gibson Pdf

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

Andrew Krumm,Barbara Means,Marie Bienkowski
Learning Analytics Goes to School Book PDF

Author : Andrew Krumm,Barbara Means,Marie Bienkowski
Publisher : Routledge
Page : 275 pages
File Size : 50,7 Mb
Release : 2018-01-12
Category : Education
ISBN : 9781317307860

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Learning Analytics Goes to School by Andrew Krumm,Barbara Means,Marie Bienkowski Pdf

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.

Utilizing Educational Data Mining Techniques for Improved Learning: Emerging Research and Opportunities

Bhatt, Chintan,Sajja, Priti Srinivas,Liyanage, Sidath
Utilizing Educational Data Mining Techniques for Improved Learning Emerging Research and Opportunities Book PDF

Author : Bhatt, Chintan,Sajja, Priti Srinivas,Liyanage, Sidath
Publisher : IGI Global
Page : 166 pages
File Size : 52,9 Mb
Release : 2019-08-02
Category : Education
ISBN : 9781799800125

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Utilizing Educational Data Mining Techniques for Improved Learning: Emerging Research and Opportunities by Bhatt, Chintan,Sajja, Priti Srinivas,Liyanage, Sidath Pdf

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.

Learning Analytics

Johann Ari Larusson,Brandon White
Learning Analytics Book PDF

Author : Johann Ari Larusson,Brandon White
Publisher : Springer
Page : 195 pages
File Size : 51,8 Mb
Release : 2014-07-04
Category : Education
ISBN : 9781461433057

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Learning Analytics by Johann Ari Larusson,Brandon White Pdf

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.

Data Mining and Learning Analytics

Samira ElAtia,Donald Ipperciel,Osmar Zaïane
Data Mining and Learning Analytics Book PDF

Author : Samira ElAtia,Donald Ipperciel,Osmar Zaïane
Publisher : Unknown
Page : 320 pages
File Size : 53,5 Mb
Release : 2016
Category : Computer-assisted instruction
ISBN : OCLC:1105779445

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Data Mining and Learning Analytics by Samira ElAtia,Donald Ipperciel,Osmar Zaïane Pdf

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.

Educational Improvement Through Data Mining and Analytics

Marcella Pietro
Educational Improvement Through Data Mining and Analytics Book PDF

Author : Marcella Pietro
Publisher : Nova Science Publishers
Page : 0 pages
File Size : 51,9 Mb
Release : 2014
Category : Education
ISBN : 1633213587

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Educational Improvement Through Data Mining and Analytics by Marcella Pietro Pdf

This book describes data analytics and data mining in the commercial world and how similar techniques (learner analytics and educational data mining) are starting to be applied in education. The book examines the challenges being encountered and the potential of such efforts for improving student outcomes and the productivity of K12 education systems. The goal is to help education policymakers and administrators understand how data mining and analytics work and how they can be applied within online learning systems to support education-related decision making.

Educational Data Science

Alejandro Peña-Ayala
Educational Data Science Book PDF

Author : Alejandro Peña-Ayala
Publisher : Springer Nature
Page : 299 pages
File Size : 49,7 Mb
Release : 2023
Category : Artificial intelligence
ISBN : 9789819900268

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Educational Data Science by Alejandro Peña-Ayala Pdf

This book describes theoretical elements, practical approaches, and specialized tools that systematically organize, characterize, and analyze big data gathered from educational affairs and settings. Moreover, the book shows several inference criteria to leverage and produce descriptive, explanatory, and predictive closures to study and understand education phenomena at in classroom and online environments. This is why diverse researchers and scholars contribute with valuable chapters to ground with well-sounded theoretical and methodological constructs in the novel field of Educational Data Science (EDS), which examines academic big data repositories, as well as to introduces systematic reviews, reveals valuable insights, and promotes its application to extend its practice. EDS as a transdisciplinary field relies on statistics, probability, machine learning, data mining, and analytics, in addition to biological, psychological, and neurological knowledge about learning science. With this in mind, the book is devoted to those that are in charge of educational management, educators, pedagogues, academics, computer technologists, researchers, and postgraduate students, who pursue to acquire a conceptual, formal, and practical landscape of how to deploy EDS to build proactive, real- time, and reactive applications that personalize education, enhance teaching, and improve learning!

Trust, Organizations and the Digital Economy

Joanna Paliszkiewicz,Kuanchin Chen
Trust Organizations and the Digital Economy Book PDF

Author : Joanna Paliszkiewicz,Kuanchin Chen
Publisher : Routledge
Page : 210 pages
File Size : 51,5 Mb
Release : 2021-09-28
Category : Business & Economics
ISBN : 9781000455441

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Trust, Organizations and the Digital Economy by Joanna Paliszkiewicz,Kuanchin Chen Pdf

Trust is a pervasive catalyst of human and business relationships that has inspired interest in researchers and practitioners alike. It has been shown to enhance engagement, communication, organizational performance, and online activities. Despite its role to cultivate cooperation, knowledge-sharing, and innovation, trust through digital means or even trust in digital media has presented new opportunities and challenges in society. Examples include a wider and faster dissemination of trust-influencing messages, and richer options of digital cues that engage, disrupt, or even transform how trust is formulated. Despite that, trust helps people to live through risky and uncertain situations, and the many capabilities enabled on the digital platforms have made the formation and sustaining of trust very different compared to traditional means. Trust in today’s digital environment plays an important role and is intertwined with concepts including reliability, quality, and privacy. This book aims to bring together the theory and practice of trust in the new digital era and will present theoretical and practical foundations. Trust is not given; we must work to build it, but it is a very fragile and intangible asset once built. It is easy to destroy and challenging to rebuild. Researchers, academics, and students in the fields of management, responsibility, and business ethics will gain knowledge on trust and related concepts, learn about the theoretical underpinnings of trust and how it sustains itself through digital dissemination, and explore empirically validated practice regarding trust and its related concepts.

Learning Analytics in Education

David Niemi,Roy D. Pea,Bror Saxberg,Richard E. Clark
Learning Analytics in Education Book PDF

Author : David Niemi,Roy D. Pea,Bror Saxberg,Richard E. Clark
Publisher : IAP
Page : 128 pages
File Size : 45,5 Mb
Release : 2018-08-01
Category : Education
ISBN : 9781641133715

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Learning Analytics in Education by David Niemi,Roy D. Pea,Bror Saxberg,Richard E. Clark Pdf

This book provides a comprehensive introduction by an extraordinary range of experts to the recent and rapidly developing field of learning analytics. Some of the finest current thinkers about ways to interpret and benefit from the increasing amount of evidence from learners’ experiences have taken time to explain their methods, describe examples, and point out new underpinnings for the field. Together, they show how this new field has the potential to dramatically increase learner success through deeper understanding of the academic, social-emotional, motivational, identity and meta-cognitive context each learner uniquely brings. Learning analytics is much more than “analyzing learning data”—it is about deeply understanding what learning activities work well, for whom, and when. Learning Analytics in Education provides an essential framework, as well as guidance and examples, for a wide range of professionals interested in the future of learning. If you are already involved in learning analytics, or otherwise trying to use an increasing density of evidence to understand learners’ progress, these leading thinkers in the field may give you new insights. If you are engaged in teaching at any level, or training future teachers/faculty for this new, increasingly technology-enhanced learning world, and want some sense of the potential opportunities (and pitfalls) of what technology can bring to your teaching and students, these forward-thinking leaders can spark your imagination. If you are involved in research around uses of technology, improving learning measurements, better ways to use evidence to improve learning, or in more deeply understanding human learning itself, you will find additional ideas and insights from some of the best thinkers in the field here. If you are involved in making administrative or policy decisions about learning, you will find new ideas (and dilemmas) coming your way from inevitable changes in how we design and deliver instruction, how we measure the outcomes, and how we provide feedback to students, teachers, developers, administrators, and policy-makers. For all these players, the trick will be to get the most out of all the new developments to efficiently and effectively improve learning performance, without getting distracted by “shiny” technologies that are disconnected from how human learning and development actually work.

A-Z of Digital Research Methods

Catherine Dawson
A Z of Digital Research Methods Book PDF

Author : Catherine Dawson
Publisher : Routledge
Page : 378 pages
File Size : 52,5 Mb
Release : 2019-07-10
Category : Science
ISBN : 9781351044653

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A-Z of Digital Research Methods by Catherine Dawson Pdf

This accessible, alphabetical guide provides concise insights into a variety of digital research methods, incorporating introductory knowledge with practical application and further research implications. A-Z of Digital Research Methods provides a pathway through the often-confusing digital research landscape, while also addressing theoretical, ethical and legal issues that may accompany each methodology. Dawson outlines 60 chapters on a wide range of qualitative and quantitative digital research methods, including textual, numerical, geographical and audio-visual methods. This book includes reflection questions, useful resources and key texts to encourage readers to fully engage with the methods and build a competent understanding of the benefits, disadvantages and appropriate usages of each method. A-Z of Digital Research Methods is the perfect introduction for any student or researcher interested in digital research methods for social and computer sciences.

A Beginner’s Guide to Learning Analytics

Srinivasa K G,Muralidhar Kurni
A Beginner s Guide to Learning Analytics Book PDF

Author : Srinivasa K G,Muralidhar Kurni
Publisher : Springer Nature
Page : 326 pages
File Size : 48,6 Mb
Release : 2021-04-19
Category : Education
ISBN : 9783030702588

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A Beginner’s Guide to Learning Analytics by Srinivasa K G,Muralidhar Kurni Pdf

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.

Data Cultures in Higher Education

Juliana E. Raffaghelli,Albert Sangrà
Data Cultures in Higher Education Book PDF

Author : Juliana E. Raffaghelli,Albert Sangrà
Publisher : Springer Nature
Page : 389 pages
File Size : 49,8 Mb
Release : 2023-03-07
Category : Education
ISBN : 9783031241932

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Data Cultures in Higher Education by Juliana E. Raffaghelli,Albert Sangrà Pdf

This collection focuses on the role of higher education institutions concerning datafication as a complex phenomenon. It explores how the universities can develop data literac(ies) shaping tomorrow skills and “formae mentis” to face the most deleterious effects of datafication, but also to engage in creative and constructive ways with data. Notably, the book spots data practices within the two most relevant sides of academics’ professional practice, namely, research and teaching. Hence, the collection seeks to reflect on faculty’s professional learning about data infrastructures and practices. The book draws on a range of studies covering the higher education response to the several facets of data in society, from data surveillance and the algorithmic control of human behaviour to empowerment through the use of open data. The research reported ranges from literature overviews to multi-case and in-depth case studies illustrating institutional and educational responses to different problems connected to data. The ultimate intention is to provide conceptual bases and practical examples relating to universities’ faculty development policies to overcome data practices and discourses' fragmentation and contradictions: in a nutshell, to build “fair data cultures” in higher education.

Data Analytics in e-Learning: Approaches and Applications

Marian Cristian Mihăescu
Data Analytics in e Learning Approaches and Applications Book PDF

Author : Marian Cristian Mihăescu
Publisher : Springer Nature
Page : 167 pages
File Size : 45,5 Mb
Release : 2022-03-22
Category : Computers
ISBN : 9783030966447

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Data Analytics in e-Learning: Approaches and Applications by Marian Cristian Mihăescu Pdf

This book focuses on research and development aspects of building data analytics workflows that address various challenges of e-learning applications. This book represents a guideline for building a data analysis workflow from scratch. Each chapter presents a step of the entire workflow, starting from an available dataset and continuing with building interpretable models, enhancing models, and tackling aspects of evaluating engagement and usability. The related work shows that many papers have focused on machine learning usage and advancement within e-learning systems. However, limited discussions have been found on presenting a detailed complete roadmap from the raw dataset up to the engagement and usability issues. Practical examples and guidelines are provided for designing and implementing new algorithms that address specific problems or functionalities. This roadmap represents a potential resource for various advances of researchers and practitioners in educational data mining and learning analytics.