Online Learning Analytics
- Length: 232 pages
- Edition: 1
- Language: English
- Publisher: Auerbach Publications
- Publication Date: 2021-12-14
- ISBN-10: 1032200979
- ISBN-13: 9781032200972
- Sales Rank: #0 (See Top 100 Books)
“In our increasingly digitally enabled education world, analytics used ethically, strategically, and with care holds the potential to help more and more diverse students be more successful on higher education journeys than ever before. Jay Liebowitz and a cadre of the fields best ‘good trouble’ makers in this space help shine a light on the possibilities, potential challenges, and the power of learning together in this work.”
—Mark David Milliron, Ph.D., Senior Vice President and Executive Dean of the Teachers College, Western Governors University
Due to the COVID-19 pandemic and its aftereffects, we have begun to enter the “new normal” of education. Instead of online learning being an “added feature” of K–12 schools and universities worldwide, it will be incorporated as an essential feature in education. There are many questions and concerns from parents, students, teachers, professors, administrators, staff, accrediting bodies, and others regarding the quality of virtual learning and its impact on student learning outcomes.
Online Learning Analytics is conceived on trying to answer the questions of those who may be skeptical about online learning. Through better understanding and applying learning analytics, we can assess how successful learning and student/faculty engagement, as examples, can contribute towards producing the educational outcomes needed to advance student learning for future generations. Learning analytics has proven to be successful in many areas, such as the impact of using learning analytics in asynchronous online discussions in higher education. To prepare for a future where online learning plays a major role, this book examines:
- Data insights for improving curriculum design, teaching practice, and learning
- Scaling up learning analytics in an evidence-informed way
- The role of trust in online learning.
Online learning faces very real philosophical and operational challenges. This book addresses areas of concern about the future of education and learning. It also energizes the field of learning analytics by presenting research on a range of topics that is broad and recognizes the humanness and depth of educating and learning.
Cover Half Title Title Page Copyright Page Dedication Table of Contents List of Figures List of Tables Foreword Preface Contributing Authors About the Editor Chapter 1 Leveraging Learning Analytics for Assessment and Feedback Abstract Introduction Current State of Educational Assessment Harnessing Data and Analytics for Assessment Benefits of Analytics-Enhanced Assessment Analytics-Enhanced Assessment Framework Conclusion References Chapter 2 Desperately Seeking the Impact of Learning Analytics in Education at Scale: Marrying Data Analysis with Teaching and Learning Abstract Introduction Critical Aspects of LA in a Human-Centered Perspective Focus on Teachers’ Needs and Goals Teachers’ Data Literacy Skills Data Conclusions References Chapter 3 Designing for Insights: An Evidenced-Centered Approach to Learning Analytics Abstract Introduction Current Issues in Learning Analytics Learning Theory and Learning Analytics Availability and Validity of Learner Data Contextual Gaps in Data Footprints Ethical Considerations Conclusion An Evidenced-Centered Design Approach to Yielding Valid and Reliable Learning Analytics ELAborate User-Centered Design in Discovery Learning Outcomes, Theory of Action, Theory of Change, and a Learning Model Learner Data Footprint Construct Validity and Meaningful Insights Ethics-Informed Learning Analytics Conclusion References Chapter 4 Implementing Learning Analytics at Scale in an Online World: Lessons Learned from the Open University UK Abstract Introduction Making Use of Learning Analytics Data The Rise of the Learning Analytics Community Case Study 1: The Analytics4Action Project Case Study 2: Learning Design to Understand Learning Analytics Discussion References Chapter 5 Realising the Potential of Learning Analytics: Reflections from a Pandemic Abstract Introduction Some Notes on the Nature of Conceptual Exploration Glimpses of Learning Analytics During the Pandemic Implications and (Un)Realised Potential of Learning Analytics Conceptual Operations Conclusions References Chapter 6: Using Learning Analytics and Instructional Design to Inform,Find, and Scale Quality Online Learning Abstract Introduction Selected Research and Practice About Online Learning Quality Learning Analytics in Higher Ed and at UMBC UMBC’s Pandemic PIVOT Theory and Practice Adoption Impact Faculty Students Lessons Learned Conclusion References Chapter 7 Democratizing Data at a Large R1 Institution: Supporting Data-Informed Decision Making for Advisers, Faculty, and Instructional Designers Abstract Introduction Dimensions of Learning Analytics Learning Analytics Project Dimensions Organizational Considerations: Creating Conditions for Success Security, Privacy, and Ethics Advancing Analytics Initiatives at Your Institution Iterating Toward Success Consortium, Research Partnerships, and Standards Penn State Projects Penn State Projects: Analytical Design Model Penn State Projects: Elevate Penn State Projects: Spectrum Conclusion References Chapter 8 The Benefits of the ‘New Normal’: Data Insights for Improving Curriculum Design, Teaching Practice, and Learning Abstract Introduction Testing the Benefits of the New Normal Variables and Proxies Digging Deeper: How to Separate Curriculum, Assessment, and Teacher Effects on Learning Conclusion References Chapter 9 Learning Information, Knowledge, and Data Analysis in Israel: A Case Study Abstract Introduction: The 21st-Century Skills Developing the Digital Information Discovery and Detection Programs Upgrading the Program: Data and Information COVID-19 Current Situation Summary References Chapter 10 Scaling Up Learning Analytics in an Evidence-Informed Way Abstract Introduction A Capability Model for Learning Analytics Capabilities for Learning Analytics Design Process Using the Learning Analytics Capability Model in Practice Evaluation of the Learning Analytics Capability Model Phases of Learning Analytics Implementation Measuring Impact on Learning Conclusion and Recommendations References Chapter 11 The Role of Trust in Online Learning Abstract Introduction Trust and Online Learning—Literature Review Research Method Characteristics of the Research Sample The Instrument and Data Analysis Research Results Demographic Characteristics of Respondents Technological Availability and Software Used Benefits of Learning Online Bottlenecks in Online Learning Factors Affecting Online Learning Discussion Conclusion References Chapter 12 Face Detection with Applications in Education Abstract Introduction Problem Statement Literature Review Face Detection Techniques Geometric Approach Machine Learning Approach Methodology Image Preprocessing Integral Image Removing Haar Features Experimentation Creating the Haar Cascading Classifier Tuning Parameters Experimentation Results Results Metrics Results Comparison Table Conclusions and Future Work Acknowledgments References Index
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