Data Analytics In E Learning Approaches And Applications

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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 : 51,5 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.

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 : Unknown
Page : 0 pages
File Size : 48,8 Mb
Release : 2022
Category : Electronic
ISBN : 3030966453

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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.

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 : 48,5 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.

Data Analytics Applications in Education

Jan Vanthienen,Kristof De Witte
Data Analytics Applications in Education Book PDF

Author : Jan Vanthienen,Kristof De Witte
Publisher : CRC Press
Page : 265 pages
File Size : 50,9 Mb
Release : 2017-09-29
Category : Business & Economics
ISBN : 9781498769280

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Data Analytics Applications in Education by Jan Vanthienen,Kristof De Witte Pdf

The abundance of data and the rise of new quantitative and statistical techniques have created a promising area: data analytics. This combination of a culture of data-driven decision making and techniques to include domain knowledge allows organizations to exploit big data analytics in their evaluation and decision processes. Also, in education and learning, big data analytics is being used to enhance the learning process, to evaluate efficiency, to improve feedback, and to enrich the learning experience. As every step a student takes in the online world can be traced, analyzed, and used, there are plenty of opportunities to improve the learning process of students. First, data analytics techniques can be used to enhance the student’ s learning process by providing real-time feedback, or by enriching the learning experience. Second, data analytics can be used to support the instructor or teacher. Using data analytics, the instructor can better trace, and take targeted actions to improve, the learning process of the student. Third, there are possibilities in using data analytics to measure the performance of instructors. Finally, for policy makers, it is often unclear how schools use their available resources to "produce" outcomes. By combining structured and unstructured data from various sources, data analytics might provide a solution for governments that aim to monitor the performance of schools more closely. Data analytics in education should not be the domain of a single discipline. Economists should discuss the possibilities, issues, and normative questions with a multidisciplinary team of pedagogists, philosophers, computer scientists, and sociologists. By bringing together various disciplines, a more comprehensive answer can be formulated to the challenges ahead. This book starts this discussion by highlighting some economic perspectives on the use of data analytics in education. The book begins a rich, multidisciplinary discussion that may make data analytics in education seem as natural as a teacher in front of a classroom.

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 : 44,6 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.

Machine Learning Paradigms

Maria Virvou,Efthimios Alepis,George A. Tsihrintzis,Lakhmi C. Jain
Machine Learning Paradigms Book PDF

Author : Maria Virvou,Efthimios Alepis,George A. Tsihrintzis,Lakhmi C. Jain
Publisher : Springer
Page : 223 pages
File Size : 41,9 Mb
Release : 2019-03-16
Category : Technology & Engineering
ISBN : 9783030137434

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Machine Learning Paradigms by Maria Virvou,Efthimios Alepis,George A. Tsihrintzis,Lakhmi C. Jain Pdf

This book presents recent machine learning paradigms and advances in learning analytics, an emerging research discipline concerned with the collection, advanced processing, and extraction of useful information from both educators’ and learners’ data with the goal of improving education and learning systems. In this context, internationally respected researchers present various aspects of learning analytics and selected application areas, including: • Using learning analytics to measure student engagement, to quantify the learning experience and to facilitate self-regulation; • Using learning analytics to predict student performance; • Using learning analytics to create learning materials and educational courses; and • Using learning analytics as a tool to support learners and educators in synchronous and asynchronous eLearning. The book offers a valuable asset for professors, researchers, scientists, engineers and students of all disciplines. Extensive bibliographies at the end of each chapter guide readers to probe further into their application areas of interest.

Emerging Trends in Learning Analytics

Anonim
Emerging Trends in Learning Analytics Book PDF

Author : Anonim
Publisher : BRILL
Page : 297 pages
File Size : 44,8 Mb
Release : 2019-05-07
Category : Education
ISBN : 9789004399273

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Emerging Trends in Learning Analytics by Anonim Pdf

This book documents recent attempts to conduct systematic, prodigious and multidisciplinary research in learning analytics and present their findings and identify areas for further research and development. The book also unveils the distinguished and exemplary works by educators and researchers in the field highlighting the current trends, privacy and ethical issues, creative and unique approaches, innovative methods, frameworks, and theoretical and practical aspects of learning analytics.

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 : 52,8 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.

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 : 55,7 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: Fundaments, Applications, and Trends

Alejandro Peña-Ayala
Learning Analytics Fundaments Applications and Trends Book PDF

Author : Alejandro Peña-Ayala
Publisher : Springer
Page : 303 pages
File Size : 41,9 Mb
Release : 2017-02-17
Category : Technology & Engineering
ISBN : 9783319529776

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Learning Analytics: Fundaments, Applications, and Trends by Alejandro Peña-Ayala Pdf

This book provides a conceptual and empirical perspective on learning analytics, its goal being to disseminate the core concepts, research, and outcomes of this emergent field. Divided into nine chapters, it offers reviews oriented on selected topics, recent advances, and innovative applications. It presents the broad learning analytics landscape and in-depth studies on higher education, adaptive assessment, teaching and learning. In addition, it discusses valuable approaches to coping with personalization and huge data, as well as conceptual topics and specialized applications that have shaped the current state of the art. By identifying fundamentals, highlighting applications, and pointing out current trends, the book offers an essential overview of learning analytics to enhance learning achievement in diverse educational settings. As such, it represents a valuable resource for researchers, practitioners, and students interested in updating their knowledge and finding inspirations for their future work.

Software Data Engineering for Network eLearning Environments

Santi Caballé,Jordi Conesa
Software Data Engineering for Network eLearning Environments Book PDF

Author : Santi Caballé,Jordi Conesa
Publisher : Springer
Page : 228 pages
File Size : 45,5 Mb
Release : 2018-02-09
Category : Technology & Engineering
ISBN : 9783319683188

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Software Data Engineering for Network eLearning Environments by Santi Caballé,Jordi Conesa Pdf

This book presents original research on analytics and context awareness with regard to providing sophisticated learning services for all stakeholders in the eLearning context. It offers essential information on the definition, modeling, development and deployment of services for these stakeholders. Data analysis has long-since been a cornerstone of eLearning, supplying learners, teachers, researchers, managers and policymakers with valuable information on learning activities and design. With the rapid development of Internet technologies and sophisticated online learning environments, increasing volumes and varieties of data are being generated, and data analysis has moved on to more complex analysis techniques, such as educational data mining and learning analytics. Now powered by cloud technologies, online learning environments are capable of gathering and storing massive amounts of data in various formats, of tracking user-system and user-user interactions, and of delivering rich contextual information.

Computational Learning Approaches to Data Analytics in Biomedical Applications

Khalid Al-Jabery,Tayo Obafemi-Ajayi,Gayla Olbricht,Donald Wunsch
Computational Learning Approaches to Data Analytics in Biomedical Applications Book PDF

Author : Khalid Al-Jabery,Tayo Obafemi-Ajayi,Gayla Olbricht,Donald Wunsch
Publisher : Academic Press
Page : 312 pages
File Size : 42,7 Mb
Release : 2019-11-20
Category : Technology & Engineering
ISBN : 9780128144831

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Computational Learning Approaches to Data Analytics in Biomedical Applications by Khalid Al-Jabery,Tayo Obafemi-Ajayi,Gayla Olbricht,Donald Wunsch Pdf

Computational Learning Approaches to Data Analytics in Biomedical Applications provides a unified framework for biomedical data analysis using varied machine learning and statistical techniques. It presents insights on biomedical data processing, innovative clustering algorithms and techniques, and connections between statistical analysis and clustering. The book introduces and discusses the major problems relating to data analytics, provides a review of influential and state-of-the-art learning algorithms for biomedical applications, reviews cluster validity indices and how to select the appropriate index, and includes an overview of statistical methods that can be applied to increase confidence in the clustering framework and analysis of the results obtained. Includes an overview of data analytics in biomedical applications and current challenges Updates on the latest research in supervised learning algorithms and applications, clustering algorithms and cluster validation indices Provides complete coverage of computational and statistical analysis tools for biomedical data analysis Presents hands-on training on the use of Python libraries, MATLAB® tools, WEKA, SAP-HANA and R/Bioconductor

Methods for Analyzing and Leveraging Online Learning Data

Hai-Jew, Shalin
Methods for Analyzing and Leveraging Online Learning Data Book PDF

Author : Hai-Jew, Shalin
Publisher : IGI Global
Page : 436 pages
File Size : 51,9 Mb
Release : 2018-10-05
Category : Education
ISBN : 9781522575290

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Methods for Analyzing and Leveraging Online Learning Data by Hai-Jew, Shalin Pdf

While online learning continues to be a rapidly expanding field of research, analyzing data allows educational institutions to fine tune their curriculum and teaching methods. Properly utilizing the data, however, becomes difficult when taking into account how socio-technical systems are used, the administration of those systems, default settings, how data is described and captured, and other factors. Methods for Analyzing and Leveraging Online Learning Data is a pivotal reference source that provides vital research on the application of data in online education for improving a system’s capabilities and optimizing it for teaching and learning. This publication explores data handling, cleaning, analysis, management, and representation, as well as the methods of effectively and ethically applying data research. Tying together education and information science with special attention paid to informal learning, online assessment, and social media, this book is ideally designed for educational administrators, system developers, curriculum designers, data analysts, researchers, instructors, and graduate-level students seeking current research on capturing, analyzing, storing, and sharing data-analytic insights regarding online learning environments.

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 : 51,7 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.

Online Learning Analytics

Jay Liebowitz
Online Learning Analytics Book PDF

Author : Jay Liebowitz
Publisher : CRC Press
Page : 248 pages
File Size : 51,7 Mb
Release : 2021-12-13
Category : Education
ISBN : 9781000539004

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Online Learning Analytics by Jay Liebowitz Pdf

"In our increasingly digitally enabled education world, analytics used ethically, strategically, and with care holds the potential to help more and more diverse students be more successful on higher education journeys than ever before. Jay Liebowitz and a cadre of the fields best ‘good trouble’ makers in this space help shine a light on the possibilities, potential challenges, and the power of learning together in this work." —Mark David Milliron, Ph.D., Senior Vice President and Executive Dean of the Teachers College, Western Governors University Due to the COVID-19 pandemic and its aftereffects, we have begun to enter the "new normal" of education. Instead of online learning being an "added feature" of K–12 schools and universities worldwide, it will be incorporated as an essential feature in education. There are many questions and concerns from parents, students, teachers, professors, administrators, staff, accrediting bodies, and others regarding the quality of virtual learning and its impact on student learning outcomes. Online Learning Analytics is conceived on trying to answer the questions of those who may be skeptical about online learning. Through better understanding and applying learning analytics, we can assess how successful learning and student/faculty engagement, as examples, can contribute towards producing the educational outcomes needed to advance student learning for future generations. Learning analytics has proven to be successful in many areas, such as the impact of using learning analytics in asynchronous online discussions in higher education. To prepare for a future where online learning plays a major role, this book examines: Data insights for improving curriculum design, teaching practice, and learning Scaling up learning analytics in an evidence-informed way The role of trust in online learning. Online learning faces very real philosophical and operational challenges. This book addresses areas of concern about the future of education and learning. It also energizes the field of learning analytics by presenting research on a range of topics that is broad and recognizes the humanness and depth of educating and learning.