Learning Analytics Methods and Tutorials
Author: Mohammed Saqr
Publisher: Springer Nature
Published:
Total Pages: 748
ISBN-13: 3031544641
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Data Mining and Learning Analytics
Author: Samira ElAtia
Publisher: John Wiley & Sons
Published: 2016-09-20
Total Pages: 351
ISBN-13: 1118998219
DOWNLOAD EBOOKAddresses 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.
Innovative Learning Analytics for Evaluating Instruction
Author: Theodore W. Frick
Publisher: Routledge
Published: 2021-07-19
Total Pages: 136
ISBN-13: 1000454770
DOWNLOAD EBOOKInnovative Learning Analytics for Evaluating Instruction covers the application of a forward-thinking research methodology that uses big data to evaluate the effectiveness of online instruction. Analysis of Patterns in Time (APT) is a practical analytic approach that finds meaningful patterns in massive data sets, capturing temporal maps of students’ learning journeys by combining qualitative and quantitative methods. Offering conceptual and research overviews, design principles, historical examples, and more, this book demonstrates how APT can yield strong, easily generalizable empirical evidence through big data; help students succeed in their learning journeys; and document the extraordinary effectiveness of First Principles of Instruction. It is an ideal resource for faculty and professionals in instructional design, learning engineering, online learning, program evaluation, and research methods.
Contemporary Technologies in Education
Author: Olusola O. Adesope
Publisher: Springer
Published: 2018-11-08
Total Pages: 268
ISBN-13: 3319896806
DOWNLOAD EBOOKThis edited volume provides a critical discussion of theoretical, methodological, and practical developments of contemporary forms of educational technologies. Specifically, the book discusses the use of contemporary technologies such as the Flipped Classroom (FC), Massive Open Online Course (MOOC), Social Media, Serious Educational Games (SEG), Wikis, innovative learning software tools, and learning analytic approach for making sense of big data. While some of these contemporary educational technologies have been touted as panaceas, researchers and developers have been faced with enormous challenges in enhancing the use of these technologies to arouse student attention and improve persistent motivation, engagement, and learning. Hence, the book examines how contemporary technologies can engender student motivation and result in improved engagement and learning. Each chapter also discusses the road ahead and where appropriate, uses the current trend to predict future affordances of technologies.
Quantitative Ethnography
Author: David Williamson Shaffer
Publisher: Lulu.com
Published: 2017
Total Pages: 498
ISBN-13: 0578191687
DOWNLOAD EBOOKHow can we make sense of make sense of the deluge of information in the digital age? The new science of Quantitative Ethnography dissolves the boundaries between quantitative and qualitative research to give researchers tools for studying the human side of big data: to understand not just what data says, but what it tells us about the people who created it. Thoughtful, literate, and humane, Quantitative Ethnography integrates data-mining, discourse analysis, psychology, statistics, and ethnography into a brand-new science for understanding what people do and why they do it. Packed with anecdotes, stories, and clear explanations of complex ideas, Quantitative Ethnography is an engaging introduction to research methods for students, an introduction to data science for qualitative researchers, and an introduction to the humanities for statisticians--but also a compelling philosophical and intellectual journey for anyone who wants to understand learning, culture and behavior in the age of big data.
Data Science in Education Using R
Author: Ryan A. Estrellado
Publisher: Routledge
Published: 2020-10-26
Total Pages: 315
ISBN-13: 1000200906
DOWNLOAD EBOOKData Science in Education Using R is the go-to reference for learning data science in the education field. The book answers questions like: What does a data scientist in education do? How do I get started learning R, the popular open-source statistical programming language? And what does a data analysis project in education look like? If you’re just getting started with R in an education job, this is the book you’ll want with you. This book gets you started with R by teaching the building blocks of programming that you’ll use many times in your career. The book takes a "learn by doing" approach and offers eight analysis walkthroughs that show you a data analysis from start to finish, complete with code for you to practice with. The book finishes with how to get involved in the data science community and how to integrate data science in your education job. This book will be an essential resource for education professionals and researchers looking to increase their data analysis skills as part of their professional and academic development.
Technology Enhanced Learning for Inclusive and Equitable Quality Education
Author: Rafael Ferreira Mello
Publisher: Springer Nature
Published:
Total Pages: 296
ISBN-13: 3031723120
DOWNLOAD EBOOKLearning Analytics in Higher Education
Author: Jaime Lester
Publisher: John Wiley & Sons
Published: 2017-12-21
Total Pages: 155
ISBN-13: 1119478464
DOWNLOAD EBOOKLearning analytics (or educational big data) tools are increasingly being deployed on campuses to improve student performance, retention and completion, especially when those metrics are tied to funding. Providing personalized, real-time, actionable feedback through mining and analysis of large data sets, learning analytics can illuminate trends and predict future outcomes. While promising, there is limited and mixed empirical evidence related to its efficacy to improve student retention and completion. Further, learning analytics tools are used by a variety of people on campus, and as such, its use in practice may not align with institutional intent. This monograph delves into the research, literature, and issues associated with learning analytics implementation, adoption, and use by individuals within higher education institutions. With it, readers will gain a greater understanding of the potential and challenges related to implementing, adopting, and integrating these systems on their campuses and within their classrooms and advising sessions. This is the fifth issue of the 43rd volume of the Jossey-Bass series ASHE Higher Education Report. Each monograph is the definitive analysis of a tough higher education issue, based on thorough research of pertinent literature and institutional experiences. Topics are identified by a national survey. Noted practitioners and scholars are then commissioned to write the reports, with experts providing critical reviews of each manuscript before publication.
Emergent Practices of Learning Analytics in K-12 Classrooms
Author: Kavakl? Uluta?, Nurdan
Publisher: IGI Global
Published: 2023-12-29
Total Pages: 290
ISBN-13:
DOWNLOAD EBOOKIn the world of education, technology has revolutionized teaching and learning practices globally. However, the widespread adoption of technology, especially in response to Covid-19, has led to a deluge of data from students' digital footprints. The challenge lies in effectively using this data through learning analytics (LA) to optimize K-12 classroom practices. Emergent Practices of Learning Analytics in K-12 Classrooms, edited by Dr. Nurdan Kavakl? Uluta? and Dr. Devrim Höl offers a comprehensive solution to these challenges. This book gathers academic scholars to explore practical perspectives on applying learning analytics in K-12 classrooms, combining qualitative and quantitative methodologies. Addressing topics such as predictive analytics, ethical considerations, and future directions, it empowers educators to make data-driven decisions, creating engaging learning experiences for improved student outcomes. By embracing the insights and recommendations presented in this book, academic scholars can confidently navigate the realm of learning analytics and shape the future of K-12 education.
Recommender Systems for Learning
Author: Nikos Manouselis
Publisher: Springer
Published: 2012-08-28
Total Pages: 0
ISBN-13: 9781461443605
DOWNLOAD EBOOKTechnology enhanced learning (TEL) aims to design, develop and test sociotechnical innovations that will support and enhance learning practices of both individuals and organisations. It is therefore an application domain that generally covers technologies that support all forms of teaching and learning activities. Since information retrieval (in terms of searching for relevant learning resources to support teachers or learners) is a pivotal activity in TEL, the deployment of recommender systems has attracted increased interest. This brief attempts to provide an introduction to recommender systems for TEL settings, as well as to highlight their particularities compared to recommender systems for other application domains.
