Table of Contents
Table of Contents
Foreword
Preface
Section I. Digital Technology and Deep Learning: Multiple Theoretical Perspectives
Chapter 1. The Psychology of Deep Learning
(Michael K. Gardner, PhD, Department of Educational Psychology, University of Utah, Salt Lake City, UT, USA)
Chapter 2. Promoting and Assessing Deep Learning Using Technology
(J. Michael Spector, PhD and Kaushal K. Bhagat, Department of Learning Technologies, University of North Texas, Denton, TX, USA, and others)
Chapter 3. Fostering Self-Regulated Learning with Digital Technologies
(Nada Dabbagh, PhD and Anastasia Kitsantas, PhD, College of Education and Human Development, George Mason University, Fairfax, VA, USA)
Chapter 4. Online Discussion Structure and Instructor Roles for the Promotion of Deep Learning
(Byron Havard, PhD, Instructional Design and Technology, University of West Florida, Pensacola, FL, USA)
Section II. Strategies for Promoting Deep Learning with Digital Technology
Chapter 5. Multimedia Simulations That Foster Transfer: Findings from a Review of the Literature
(Jennifer G. Cromley and LuEttaMae Lawrence, Department of Educational Psychology, University of Illinois, Urbana-Champaign, IL, USA)
Chapter 6. Visualizations for Deep Learning: Using 3D Models to Promote Scientific Observation and Reasoning during Collaborative Stem Inquiry
(Kirsten R. Butcher, Ph.D., Michelle Hudson, and Madlyn Runburg, Department of Educational Psychology, University of Utah, Salt Lake City, Utah, UT, USA, and others)
Chapter 7. Strategies for Designing Advanced Learning Technologies to Foster Self-Regulated Learning
(Michelle Taub, PhD, Nicholas V. Mudrick, and Roger Azevedo, PhD, Department of Psychology, North Carolina State University, Raleigh, NC, USA)
Chapter 8. nBrowser: An Intelligent Web Browser for Studying Self-Regulated Learning in Teachers’ Use of Technology
(Eric G. Poitras, Tenzin Doleck, Lingyun Huang, Shan Li, and Susanne Lajoie, Department of Educational Psychology, University of Utah, Salt Lake City, UT, USA, and others)
Section III. Case Studies in Digital Technology and Deep Learning
Chapter 9. An Empirical Examination of Goals, Student Approaches to Learning, and Adaptive Outcomes
(Huy P. Phan, Ph.D and Bing H. Ngu, Ph.D, School of Education, University of New England, Armidale, Australia)
Chapter 10. Supporting Students’ Reflective Practice Using the OneNote Class Notebook and Scaffolding
(Silvia Hartung, Alexander Florian, and Bernhard Ertl, Department of Education, Universität der Bundeswehr München, Germany)
Chapter 11. Exploiting Innovative Technology-Enhanced Learning Environments for Teacher Professional Development
(Fotini Paraskeva, PhD, Department of Digital Systems, University of Piraeus, Piraeus, Greece)
Chapter 12. Innovative Technologies-Embedded Scientific Inquiry Practices: A Socially Situated Cognition Theory
(Muammer Çalýk, PhD and Jazlin Ebenezer, EdD, Department of Elementary Education, Karadeniz Technical University, Trabzon, Turkey, and others)
Chapter 13. Fostering Deep Learning in an Online Learning Environment
(Chih-hsuan Wang, PhD, Brian W. Lebeck, PhD, and David M. Shannon, PhD, Department of Educational Foundations, Leadership, and Technology, Auburn University, Auburn, AL, USA, and others)
Chapter 14. A Study on Deep Learning and Mental Reasoning in Digital Technology in Relation to Cognitive Load
(Kevin Greenberg and Robert Zheng, Department of Educational Psychology, University of Utah, Salt Lake City, Utah, USA)
Concluding Remarks
Index
Reviews
“This book covers a cutting edge topic in education with strong theoretical ties to work in cognition, metacognition, and emotion, with chapters written by leading researchers in the field. Researchers and practitioners interested in the impact of digital technologies in learning will find this volume to be informative, comprehensive, and thought-provoking.” – Anne E. Cook, Professor and Chair, Educational Psychology Department, Director for Student and Faculty Affairs, College of Education, University of Utah, USA
“This edited book provides excellent resources for researchers and academic professionals about the connections between deep learning (involving critical and creative thinking, reasoning performance, making inferences and knowledge transfer) and the use of digital technologies (such as virtual reality, artificial intelligence, 3D visualization, e-portfolios, and a network-based approach). Authors examine theories relevant to deep learning and provide research results regarding the cognitive and metacognitive learning strategies, self-regulated learning, reasoning performance, along with many other themes. This book offers the valuable support to graduate students and teachers aiming at their professional development, and a must for a library.” – Anna Ursyn, Professor of Digital Media Digital Media Area Head, School of Art and Design, College of Performing and Visual Arts, University of Northern Colorado, USA
““Deep learning” is the holy grail of teaching and learning, particularly for the solving of complicated and real-world challenges. The editor defines deep learning as “learners’ engagement in critical and creative thinking, making inferences and transferring knowledge” (Zheng, 2018, p. xiii). While defined in different ways, “deep learning” involves complex understandings of the target subject domain (and related areas) that are transferable and that enable real-life problem solving and innovating in various contexts.” <a href=”http://scalar.usc.edu/works/c2c-digital-magazine-fall-2018–winter-2019/book-review–achieving-deep-learning-through-digital-technology” target=”_blank”>READ MORE… – Reviewed by Shalin Hai-Jew, instructional designer at Kansas State University, USA. Published in <i>C2C Digital Magazine
The book can be used as a text for graduate and undergraduate courses in technology and learning, a reference for researchers, and a guide for individual academic professionals who are interested in applying deep learning and digital technology to teaching and learning.
