Online Learning Analytics Data Analytics Applications 1st Edition by Jay Liebowitz ISBN 9781032200972 1032200979

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