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Learning Analytics Fundaments Applications And Trends


Learning Analytics Fundaments Applications And Trends
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Learning Analytics Fundaments Applications And Trends


Learning Analytics Fundaments Applications And Trends
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Author : Alejandro Peña-Ayala
language : en
Publisher: Springer
Release Date : 2017-02-17

Learning Analytics Fundaments Applications And Trends written by Alejandro Peña-Ayala and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-17 with Technology & Engineering categories.


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.



Data Mining And Learning Analytics


Data Mining And Learning Analytics
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Author : Samira ElAtia
language : en
Publisher: John Wiley & Sons
Release Date : 2016-09-20

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 2016-09-20 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.



Learning Analytics


Learning Analytics
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Author : Gwo-Jen Hwang
language : en
Publisher: Routledge
Release Date : 2018-12-18

Learning Analytics written by Gwo-Jen Hwang and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-18 with Education categories.


Learning analytics is one of the most important research issues in the field of educational technology. By analyzing logs and records in educational databases and systems, it can provide useful information to teachers, learners, and decision makers – information which they can use to improve teaching strategies, learning performances, and educational policies. However, it is a great challenge for most researchers to efficiently analyze educational data in a meaningful way. This book presents various learning analytics approaches and applications, including the process of determining the coding scheme, analyzing the collected data, and interpreting the findings. This book was originally published as a special issue of Interactive Learning Environments.



Perspectives On Learning Analytics For Maximizing Student Outcomes


Perspectives On Learning Analytics For Maximizing Student Outcomes
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Author : Durak, Gürhan
language : en
Publisher: IGI Global
Release Date : 2023-10-24

Perspectives On Learning Analytics For Maximizing Student Outcomes written by Durak, Gürhan and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-24 with Education categories.


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.



Visualizations And Dashboards For Learning Analytics


Visualizations And Dashboards For Learning Analytics
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Author : Muhittin Sahin
language : en
Publisher: Springer Nature
Release Date : 2021-12-16

Visualizations And Dashboards For Learning Analytics written by Muhittin Sahin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-16 with Education categories.


This edited volume fills the gaps in existing literature on visualization and dashboard design for learning analytics. To do so, it presents critical tips to stakeholders and acts as guide to efficient implementation. The book covers the following topics: visualization and dashboard design for learning analytics, visualization and dashboard preferences of stakeholders, learners’ patterns on the dashboard, usability of visualization techniques and the dashboard, dashboard and intervention design, learning and instructional design for learning analytics, privacy and security issues about the dashboard, and future directions of visualization and dashboard design. This book will be of interest to researchers with interest in learning analytics and data analytics, teachers and students in higher education institutions and instructional designers, as it includes contributions from a wide variety of educational and psychological researchers, engineers, instructional designers, learning scientists, and computer scientists interested in learning analytics.



Learning Analytics In The Classroom


Learning Analytics In The Classroom
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Author : Jason Lodge
language : en
Publisher: Routledge
Release Date : 2018-10-03

Learning Analytics In The Classroom written by Jason Lodge and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-03 with Education categories.


Learning Analytics in the Classroom presents a coherent framework for the effective translation of learning analytics research for educational practice to its practical application in different education domains. Highlighting the real potential of learning analytics as a way to better understand and enhance student learning and with each chapter including specific discussion about what the research means in the classroom, this book provides educators and researchers alike with the tools and frameworks to effectively make sense of and use data and analytics in their everyday practice. This volume is split into five sections, all of which relate to the key themes in understanding learning analytics through the lens of the classroom: broad theoretical perspectives understanding learning through analytics the relationship between learning design and learning analytics analytics in the classroom and the impact it can and will have on education implementing analytics and the challenges involved. Bridging the gap between research, theory and practice, Learning Analytics in the Classroom is both a practical tool and an instructive guide for educators, and a valuable addition to researchers' bookshelves. A team of world-leading researchers and expert editors have compiled a state-of-the-art compendium on this fascinating subject and this will be a critical resource for the evolution of this field into the future.



Utilizing Learning Analytics To Support Study Success


Utilizing Learning Analytics To Support Study Success
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Author : Dirk Ifenthaler
language : en
Publisher: Springer
Release Date : 2019-01-17

Utilizing Learning Analytics To Support Study Success written by Dirk Ifenthaler and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-17 with Education categories.


Students often enter higher education academically unprepared and with unrealistic perceptions and expectations of university life, which are critical factors that influence students’ decisions to leave their institutions prior to degree completion. Advances in educational technology and the current availability of vast amounts of educational data make it possible to represent how students interact with higher education resources, as well as provide insights into students’ learning behavior and processes. This volume offers new research in such learning analytics and demonstrates how they support students at institutions of higher education by offering personalized and adaptive support of their learning journey. It focuses on four major areas of discussion: · Theoretical perspectives linking learning analytics and study success. · Technological innovations forsupporting student learning. · Issues and challenges for implementing learning analytics at higher education institutions. · Case studies showcasing successfully implemented learning analytics strategies at higher education institutions. Utilizing Learning Analytics to Support Study Success ably exemplifies how educational data and innovative digital technologies contribute to successful learning and teaching scenarios and provides critical insight to researchers, graduate students, teachers, and administrators in the general areas of education, educational psychology, academic and organizational development, and instructional technology.



Manage Your Own Learning Analytics


Manage Your Own Learning Analytics
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Author : Elspeth McKay
language : en
Publisher: Springer Nature
Release Date : 2021-12-04

Manage Your Own Learning Analytics written by Elspeth McKay and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-04 with Technology & Engineering categories.


This book sheds light on the practice of learning analytics, illuminating how others approach their data analysis. At the beginning of the book, a ‘prescriptive learning analytics planning model’ gives straightforward instructions for people to follow. This book is organized into ten chapters, falling into four topical sections: Managing Learning Analytics (overview, instructional systems design (ISD), instructional design, and planning data analysis); Cognitive Performance Measurement Practices (classical test theory (CTT), Rasch measurement theory (RMT), Item response theory(IRT), Rasch Modeling Tools (research design, setting methodology); and Case Studies (corporate training settings, healthcare industry, and educational courseware design). This book is an important reference for: educational research community and instructional systems designers; corporate training developers; postgraduate course developers; and doctoral students.



Educational Data Mining


Educational Data Mining
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Author : Alejandro Peña-Ayala
language : en
Publisher: Springer
Release Date : 2013-11-08

Educational Data Mining written by Alejandro Peña-Ayala and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-08 with Technology & Engineering categories.


This book is devoted to the Educational Data Mining arena. It highlights works that show relevant proposals, developments, and achievements that shape trends and inspire future research. After a rigorous revision process sixteen manuscripts were accepted and organized into four parts as follows: · Profile: The first part embraces three chapters oriented to: 1) describe the nature of educational data mining (EDM); 2) describe how to pre-process raw data to facilitate data mining (DM); 3) explain how EDM supports government policies to enhance education. · Student modeling: The second part contains five chapters concerned with: 4) explore the factors having an impact on the student's academic success; 5) detect student's personality and behaviors in an educational game; 6) predict students performance to adjust content and strategies; 7) identify students who will most benefit from tutor support; 8) hypothesize the student answer correctness based on eye metrics and mouse click. · Assessment: The third part has four chapters related to: 9) analyze the coherence of student research proposals; 10) automatically generate tests based on competences; 11) recognize students activities and visualize these activities for being presented to teachers; 12) find the most dependent test items in students response data. · Trends: The fourth part encompasses four chapters about how to: 13) mine text for assessing students productions and supporting teachers; 14) scan student comments by statistical and text mining techniques; 15) sketch a social network analysis (SNA) to discover student behavior profiles and depict models about their collaboration; 16) evaluate the structure of interactions between the students in social networks. This volume will be a source of interest to researchers, practitioners, professors, and postgraduate students aimed at updating their knowledge and find targets for future work in the field of educational data mining.



Educational Data Science Essentials Approaches And Tendencies


Educational Data Science Essentials Approaches And Tendencies
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Author : Alejandro Peña-Ayala
language : en
Publisher: Springer Nature
Release Date : 2023-04-29

Educational Data Science Essentials Approaches And Tendencies written by Alejandro Peña-Ayala and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-29 with Computers categories.


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 aboutlearning 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! Chapter “Sync Ratio and Cluster Heat Map for Visualizing Student Engagement” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.