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      1. Data och IT
      2. Systemvetenskap och AI

      Data Analytics and Adaptive Learning

      Research Perspectives

      AvPatsy D. Moskal,Charles D. Dziuban

      Inbunden, Engelska, 2023

      2 385 kr

      Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

      Beskrivning

      Data Analytics and Adaptive Learning offers new insights into the use of emerging data analysis and adaptive techniques in multiple learning settings. In recent years, both analytics and adaptive learning have helped educators become more responsive to learners in virtual, blended, and personalized environments. This set of rich, illuminating, international studies spans quantitative, qualitative, and mixed-methods research in higher education, K–12, and adult/continuing education contexts. By exploring the issues of definition and pedagogical practice that permeate teaching and learning and concluding with recommendations for the future research and practice necessary to support educators at all levels, this book will prepare researchers, developers, and graduate students of instructional technology to produce evidence for the benefits and challenges of data-driven learning.

      Produktinformation

      • Utgivningsdatum:2023-08-25
      • Mått:152 x 229 x 27 mm
      • Vikt:720 g
      • Format:Inbunden
      • Språk:Engelska
      • Antal sidor:334
      • Förlag:Taylor & Francis Ltd
      • ISBN:9781032150390

      Utforska kategorier

      • Systemvetenskap och AI inom Data och IT
      • Databaser inom Data och IT
      • Material och digital teknik i undervisningen inom Psykologi och pedagogik

      Mer om författaren

      Patsy D. Moskal is Director of the Digital Learning Impact Evaluation in the Research Initiative for Teaching Effectiveness at the University of Central Florida, USA.Charles D. Dziuban is Director of the Research Initiative for Teaching Effectiveness at the University of Central Florida, USA.Anthony G. Picciano is Professor of Education Leadership at Hunter College and Professor in the PhD program in Urban Education at the City University of New York Graduate Center, USA.

      Recensioner i media

      "This book is an essential guide to the promise and practice of data analytics and adaptive learning in higher education. These pioneers and practitioners share valuable insights all institutions can use to enhance learning and student success."—Diana G. Oblinger, Ph.D., President Emeritus, EDUCAUSE"Impacts on learning we called overdetermined can now be parsed but need an informed judgment rising to the complexities involved. Data Analytics and Adaptive Learning, a collection of the very best thinking about both, provides just that, rendering the (potentially) all-seeing and hyper-focused approaches of DA and AL fruitful, humane, transformative."—George Otte, former University Director of Academic Technology, The City University of New York"At last: a book by education experts about the use of digital Information and Communication Technologies (ICTs) not only for lowering the friction in data, but for processing information to help teachers and students. This can be the beginning of a more radical change in education."—Anders Norberg, Coordinator of the ERASMUS+ALBATTS Blueprint project for development of innovative education for the emerging European battery and electromobility value chain (ERASMUS is a European Union Initiative for Education Mobility and Development)"Digital learning is the new normal in higher education. The group of experts assembled in this book share important ideas and trends related to learning analytics and adaptive learning that will surely influence all of our digital learning environments in the future."—Charles R. Graham, Professor, Department of Instructional Psychology and Technology, Brigham Young University "The concept of personalized and adaptive learning has long been touted but seldom enacted in education at scale. Data Analytics and Adaptive Learning brings together a compelling set of experts that provide novel and research informed insights into contemporary education spaces."—Professor Shane Dawson, Executive Dean Education Futures, University of South Australia"Moskal, Dziuban, and Picciano challenge the reader to keep the student at the center and imagine how data analytics and adaptive learning can be mutually reinforcing in closing the gap between students from different demographics."—Susan Rundell Singer, Vice President for Academic Affairs and Provost, Rollins College, former Division Director for Undergraduate Education at the National Science Foundation"We are currently living in a digital age where higher education institutions have an abundance of accessible data. This book contains a series of chapters that provide insight and strategies for using data analytics and adaptive learning to support student success and satisfaction."—Dr. Norman Vaughan, Professor of Education, Mount Royal University, Calgary, Alberta, Canada"An important book that comes at a critical moment in higher education. We are swimming in an ocean of data and this book from some of the country’s top researchers and practitioners will help us make sense of it and put it in the service of student success." —Thomas Cavanagh, Ph.D. Vice Provost for Digital Learning, University of Central Florida"Data Analytics and Adaptive Learning is an excellent addition to the canon of literature in this field. The book offers several valuable perspectives and innovative ways of approaching both new and old problems to improve organizational outcomes."—Jeffrey S. Russell, P.E., Ph.D., Dist.M.ASCE, NAC, F.NSPE, Vice Provost for Lifelong Learning, Dean for Div. of Continuing Studies, University of Wisconsin-Madison"Data is used to customize experiences from buying an item to booking travel. What about learning—a uniquely human endeavor? This book contextualizes the complex answers to that question shedding light on areas with promise: learning analytics, adaptive learning and the use of big data."—Dale Whittaker, Senior Program Officer in Post-Secondary Success, Bill and Melinda Gates Foundation"Data Analytics and Adaptive Learning presents a timely and wide-ranging consideration of the progress of adaptive learning and analytics in levelling the educational playing field, while providing necessary cautions regarding the drawing of too many conclusions in what is still a nascent area."—Frank Claffey, Chief Product Officer, Realizeit Learning"Data Analytics and Adaptive Learning provides insights and best practices from leaders in digital learning who outline considerations for strategies, change management, and effective decision making related to data. As higher education expands its work in digital learning and utilizing data for decisions, this book is a must read!"—Dr. Connie Johnson, Chancellor, Colorado Technical University"Data analytics and adaptive learning compromise two of the most relevant educational challenges. This book provides excellent research approaches and analysis to answer practical questions related to digital education involving teachers and learners"—Josep M Duart & Elsa Rodriguez, Editor-in-Chief & Editorial Manager of the International Journal of Educational technology in Higher Education, the Universitat Oberta de Catalunya (UOC)"Data, analytics, and machine learning are impacting all jobs and industries. For education, the opportunities are immense, but so are the challenges. This book provides an essential view into the possibilities and pitfalls. If you want to use data to impact learners positively, this book is a must-read."—Colm Howlin, PhD, Chief Data Scientist, ReliaQuest"Data Analytics and Adaptive Learning helps the educational community broaden its understanding of these two technology-based opportunities to enhance education, looking at very different complementary contributions. Congratulations to the authors."—Alvaro Galvis, professor at University of Los Andes, Bogotá"The menus, dashboards, and pathways to effective data analytics and adaptive learning can be found in this massively timely and hugely impactful juggernaut."—Curtis J. Bonk, Professor of Instructional Systems Technology and adjunct in the School of Informatics, Indiana University Bloomington"Adaptive learning and learning analytics – should we use both or choose one? Do they imply organizational transformation? What works and what does not? In my opinion, the book is valuable reading for those seeking the answers to their questions."—Maria Zajac, Associate Professor (emeritus) at Pedagogical University Cracow and SGH Warsaw School of Economics, Certified Instructional Designer, Poland "Data analytics and adaptive learning platforms can direct support as needed to at-risk students, helping to create more equitable outcomes. This volume contains a timely collection of studies that examine the impact of these approaches."—John Kane, Director of the Center for Excellence in Learning and Teaching at SUNY Oswego."This book shines a spotlight on the potential for data analytics, adaptive learning and big data to transform higher education. The volume lights the way for those brave enough to embrace a new paradigm of teaching and learning that enacts a more equitable and person-centered experience for all learners."—Paige McDonald, Associate Professor and Vice Chair, Department of Clinical Research and Leadership, The George Washington School of Medicine and Health Sciences"Deftly weaving adaptive learning and analytic theory and practice together, the authors offer numerous examples of how these methods can help us address academic barriers to student success. Their work significantly strengthens the fabric of knowledge on how adaptive learning can benefit students (and faculty)." —Dale P. Johnson, Director of Digital Innovation, University Design Institute, Arizona State University"The authors of this book convince us that the concepts of data analytics and adaptive learning are tightly integrated, and the book provides insights on different aspects related to utilization of intelligent technologies and how to approach the learning cycle at different stages." —Eli Hustad, Professor in Information Systems, The University of Agder"Student success is a fundamental mission for all educational institutions. This book explores the current opportunities within analytics, adaptive Learning, and organizational transformation to generate wide-scale and equitable learning outcomes."—John Campbell, Associate Professor, Higher Education Administration, School of Education, West Virginia University"This book brings together top scholars making the connection between data analytics and adaptive learning, all while keeping pedagogical theory on the central stage. It’s a powerhouse driven in equal parts by excellence and innovation providing vision for educators on the quest for learner success across the spectrum."—Kimberly Arnold, Director of Learning Analytics Center of Excellence"Once again, a dream team of faculty, researchers, thought leaders and practitioners come up with this defining, must-read book for every institutional leader and teacher that is invested in the success of every student. This book based on years of research and practice gives the "how-to"."—Manoj Kulkarni, CEO at Realizeit Learning"The chapters in this book bring a desperately needed clarity and a depth of understanding to the topic of data and analytics, adaptive learning and learning more generally in higher education. You will leave this book smarter about these topics than you started and both you and higher education will be the beneficiary."—Glenda Morgan

      Innehållsförteckning

      • Section 1: Introduction 1. Data Analytics and Adaptive Learning: Increasing the Odds Section 2: Analytics 2. What We Want Versus What We Have: Transforming Teacher Performance Analytics to Personalize Professional Development 3. System-Wide Momentum 4. A Precise and Consistent Early Warning System for Identifying At-Risk Students 5. Predictive Analytics, Artificial Intelligence and the Impact of Delivering Personalized Supports to Students from Underserved Backgrounds 6. Predicting Student Success with Self-regulated Behaviors: A Seven-year Data Analytics Study on a Hong Kong University English Course 7. Back to Bloom: Why Theory Matters in Closing the Achievement Gap 8. The Metaphors We Learn By: Toward a Philosophy of Learning Analytics Section 3: Adaptive Learning 9. A Cross-Institutional Survey of the Instructor Use of Data Analytics in Adaptive Courses 10. Data Analytics in Adaptive Learning for Equitable Outcomes 11. Banking on Adaptive Questions to Nudge Student Responsibility for Learning in General Chemistry 12. 3-Year Experience with Adaptive Learning: Faculty and Student Perspectives 13. Analyzing Question Items with Limited Data 14. When Adaptivity and Universal Design for Learning are Not Enough: Bayesian Network Recommendations for Tutoring Section 4: Organizational Transformation 15. Sprint to 2027: Corporate Analytics in the Digital Age 16. Academic Digital Transformation: Focused on Data, Equity and Learning Science Section 5: Closing 17. Future Technological Trends and Research – Tony Picciano
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