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Author: Samira ElAtia Publisher: John Wiley & Sons ISBN: 1118998219 Category : Computers Languages : en Pages : 351
Book Description
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.
Author: Samira ElAtia Publisher: John Wiley & Sons ISBN: 1118998219 Category : Computers Languages : en Pages : 351
Book Description
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.
Author: Maren Scheffel Publisher: Springer Nature ISBN: 3030297365 Category : Education Languages : en Pages : 798
Book Description
This book constitutes the proceedings of the 14th European Conference on Technology Enhanced Learning, EC-TEL 2019, held in Delft, The Netherlands, in September 2019. The 41 research papers and 50 demo and poster papers presented in this volume were carefully reviewed and selected from 149 submissions. The contributions reflect the debate around the role of and challenges for cutting-edge 21st century meaningful technologies and advances such as artificial intelligence and robots, augmented reality and ubiquitous computing technologies and at the same time connecting them to different pedagogical approaches, types of learning settings, and application domains that can benefit from such technologies.
Author: Dirk Ifenthaler Publisher: Springer ISBN: 331964792X Category : Education Languages : en Pages : 341
Book Description
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 for supporting 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.
Author: Maiga Chang Publisher: Springer ISBN: 366244447X Category : Education Languages : en Pages : 224
Book Description
This book addresses main issues concerned with the future learning, learning and academic analytics, virtual world and smart user interface, and mobile learning. This book gathers the newest research results of smart learning environments from the aspects of learning, pedagogies, and technologies in learning. It examines the advances in technology development and changes in the field of education that has been affecting and reshaping the learning environment. Then, it proposes that under the changed technological situations, smart learning systems, no matter what platforms (i.e., personal computers, smart phones, and tablets) they are running at, should be aware of the preferences and needs that their users (i.e., the learners and teachers) have, be capable of providing their users with the most appropriate services, helps to enhance the users' learning experiences, and to make the learning efficient.
Author: Jason Lodge Publisher: Routledge ISBN: 1351113011 Category : Education Languages : en Pages : 352
Book Description
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.
Author: Caroline Haythornthwaite Publisher: SAGE ISBN: 1473955009 Category : Education Languages : en Pages : 607
Book Description
The new edition of The SAGE Handbook of E-Learning Research retains the original effort of the first edition by focusing on research while capturing the leading edge of e-learning development and practice. Chapters focus on areas of development in e-learning technology, theory, practice, pedagogy and method of analysis. Covering the full extent of e-learning can be a challenge as developments and new features appear daily. The editors of this book meet this challenge by including contributions from leading researchers in areas that have gained a sufficient critical mass to provide reliable results and practices. The 25 chapters are organised into six key areas: 1. THEORY 2. LITERACY & LEARNING 3. METHODS & PERSPECTIVES 4. PEDAGOGY & PRACTICE 5. BEYOND THE CLASSROOM 6. FUTURES
Author: Roope Jaakonmäki Publisher: Springer Nature ISBN: 3030433773 Category : Business & Economics Languages : en Pages : 99
Book Description
This book offers an introduction and hands-on examples that demonstrate how Learning Analytics (LA) can be used to enhance digital learning, teaching and training at various levels. While the majority of existing literature on the subject focuses on its application at large corporations, this book develops and showcases approaches that bring LA closer to smaller organizations, and to educational institutions that lack sufficient resources to implement a full-fledged LA infrastructure. In closing, the book introduces a set of software tools for data analytics and visualization, and explains how they can be employed in several LA scenarios.
Author: Olusola O. Adesope Publisher: Springer ISBN: 3319896806 Category : Education Languages : en Pages : 268
Book Description
This 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.
Author: George Siemens Publisher: ISBN: 9781450310574 Category : Languages : en Pages :
Book Description
1st International Conference on Learning Analytics and Knowledge Feb 27, 2011-Mar 01, 2011 Banff, Canada. You can view more information about this proceeding and all of ACM�s other published conference proceedings from the ACM Digital Library: http://www.acm.org/dl.
Author: Roger Azevedo Publisher: Springer Science & Business Media ISBN: 1441955461 Category : Education Languages : en Pages : 746
Book Description
Education in today's technologically advanced environments makes complex cognitive demands on students pre-learning, during, and post-learning. Not surprisingly, these analytical learning processes--metacognitive processes--have become an important focus of study as new learning technologies are assessed for effectiveness in this area.Rich in theoretical models and empirical data, the International Handbook of Metacognition and Learning Technologies synthesizes current research on this critical topic. This interdisciplinary reference delves deeply into component processes of self-regulated learning (SRL), examining theories and models of metacognition, empirical issues in the study of SRL, and the expanding role of educational technologies in helping students learn. Innovations in multimedia, hypermedia, microworlds, and other platforms are detailed across the domains, so that readers in diverse fields can evaluate the theories, data collection methods, and conclusions. And for the frontline instructor, contributors offer proven strategies for using technologies to benefit students at all levels. For each technology covered, the Handbook: Explains how the technology fosters students' metacognitive or self-regulated learning.Identifies features designed to study or support metacognitve/SRL behaviors.Reviews how its specific theory or model addresses learners' metacognitive/SRL processes.Provides detailed findings on its effectiveness toward learning.Discusses its implications for the design of metacognitive tools.Examines any theoretical, instructional, or other challenges.These leading-edge perspectives make the International Handbook of Metacognition and Learning Technologies a resource of great interest to professionals and researchers in science and math education, classroom teachers, human resource researchers, and industrial and other instructors.
Author: Samira ElAtia
Author: Samira ElAtia
Author: Maren Scheffel
Author: Dirk Ifenthaler
Author: Maiga Chang
Author: Jason Lodge
Author: Caroline Haythornthwaite
Author: Roope Jaakonmäki
Author: Olusola O. Adesope
Author: George Siemens
Author: Roger Azevedo