Online Learning Analytics (Data Analytics Applications)

✍ Scribed by Jay Liebowitz (editor)

• Publisher: Auerbach Publications
• Year: 2021
• Tongue: English
• Leaves: 270
• Edition: 1
• Category: Library

✦ Synopsis

"In our increasingly digitally enabled education world, analytics used ethically, strategically, and with care hold 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 one’s 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.

✦ Table of Contents

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