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Learning Analytics Explained
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Learning Analytics Explained

Learning Analytics Explained

ByNiall Sclater
Edition 1st Edition
First Published 2017
eBook Published 17 February 2017
Pub. location New York
Imprint Routledge
DOIhttps://doi.org/10.4324/9781315679563
Pages 290 pages
eBook ISBN 9781317394563
SubjectsComputer Science, Education
KeywordsLearning Analytics, Rio Salado College, Learning Record Store, Learning Analytics Initiatives, Adaptive Learning Systems
Get Citation

Get Citation

Sclater, N. (2017). Learning Analytics Explained. New York: Routledge, https://doi.org/10.4324/9781315679563
ABOUT THIS BOOK

Learning Analytics Explained draws extensively from case studies and interviews with experts in order to discuss emerging applications of the new field of learning analytics. Educational institutions increasingly collect data on students and their learning experiences, a practice that helps enhance courses, identify learners who require support, and provide a more personalized learning experience. There is, however, a corresponding need for guidance on how to carry out institutional projects, intervene effectively with students, and assess legal and ethical issues. This book provides that guidance while also covering the evolving technical architectures, standards, and products within the field.

TABLE OF CONTENTS
chapter |5 pages
Introduction
View abstract
part I|27 pages
Background
chapter 1|13 pages
The Evolution of a New Field
View abstract
chapter 2|13 pages
Expert Motivations
View abstract
part II|44 pages
Applications
chapter 3|10 pages
Early Alert and Student Success
View abstract
chapter 4|7 pages
Course Recommendation
View abstract
chapter 5|10 pages
Adaptive Learning
View abstract
chapter 6|13 pages
Curriculum Design
View abstract
chapter 7|3 pages
Expert Thoughts on Applications
View abstract
part III|62 pages
Logistics
chapter 8|10 pages
Data
View abstract
chapter 9|11 pages
Metrics and Predictive Modelling
View abstract
chapter 10|14 pages
Visualisation
View abstract
chapter 11|12 pages
Intervention
View abstract
chapter 12|11 pages
Student-Facing Analytics
View abstract
chapter 13|3 pages
Expert Thoughts on Logistics
View abstract
part IV|35 pages
Technologies
chapter 14|10 pages
Architecture
View abstract
chapter 15|10 pages
Standards
View abstract
chapter 16|10 pages
Products
View abstract
chapter 17|4 pages
Expert Thoughts on Technologies
View abstract
part V|76 pages
Deployment
chapter 18|14 pages
Institutional Readiness
View abstract
chapter 19|14 pages
Project Planning
View abstract
chapter 20|14 pages
Ethics
View abstract
chapter 21|12 pages
Transparency and Consent
View abstract
chapter 22|14 pages
Privacy and Data Protection
View abstract
chapter 23|7 pages
Expert Thoughts on Deployment
View abstract
part VI|25 pages
Future Directions
chapter 24|17 pages
Emerging Techniques
View abstract
chapter 25|7 pages
Expert Visions
View abstract

Learning Analytics Explained draws extensively from case studies and interviews with experts in order to discuss emerging applications of the new field of learning analytics. Educational institutions increasingly collect data on students and their learning experiences, a practice that helps enhance courses, identify learners who require support, and provide a more personalized learning experience. There is, however, a corresponding need for guidance on how to carry out institutional projects, intervene effectively with students, and assess legal and ethical issues. This book provides that guidance while also covering the evolving technical architectures, standards, and products within the field.

TABLE OF CONTENTS
chapter |5 pages
Introduction
View abstract
part I|27 pages
Background
chapter 1|13 pages
The Evolution of a New Field
View abstract
chapter 2|13 pages
Expert Motivations
View abstract
part II|44 pages
Applications
chapter 3|10 pages
Early Alert and Student Success
View abstract
chapter 4|7 pages
Course Recommendation
View abstract
chapter 5|10 pages
Adaptive Learning
View abstract
chapter 6|13 pages
Curriculum Design
View abstract
chapter 7|3 pages
Expert Thoughts on Applications
View abstract
part III|62 pages
Logistics
chapter 8|10 pages
Data
View abstract
chapter 9|11 pages
Metrics and Predictive Modelling
View abstract
chapter 10|14 pages
Visualisation
View abstract
chapter 11|12 pages
Intervention
View abstract
chapter 12|11 pages
Student-Facing Analytics
View abstract
chapter 13|3 pages
Expert Thoughts on Logistics
View abstract
part IV|35 pages
Technologies
chapter 14|10 pages
Architecture
View abstract
chapter 15|10 pages
Standards
View abstract
chapter 16|10 pages
Products
View abstract
chapter 17|4 pages
Expert Thoughts on Technologies
View abstract
part V|76 pages
Deployment
chapter 18|14 pages
Institutional Readiness
View abstract
chapter 19|14 pages
Project Planning
View abstract
chapter 20|14 pages
Ethics
View abstract
chapter 21|12 pages
Transparency and Consent
View abstract
chapter 22|14 pages
Privacy and Data Protection
View abstract
chapter 23|7 pages
Expert Thoughts on Deployment
View abstract
part VI|25 pages
Future Directions
chapter 24|17 pages
Emerging Techniques
View abstract
chapter 25|7 pages
Expert Visions
View abstract
CONTENTS
ABOUT THIS BOOK

Learning Analytics Explained draws extensively from case studies and interviews with experts in order to discuss emerging applications of the new field of learning analytics. Educational institutions increasingly collect data on students and their learning experiences, a practice that helps enhance courses, identify learners who require support, and provide a more personalized learning experience. There is, however, a corresponding need for guidance on how to carry out institutional projects, intervene effectively with students, and assess legal and ethical issues. This book provides that guidance while also covering the evolving technical architectures, standards, and products within the field.

TABLE OF CONTENTS
chapter |5 pages
Introduction
View abstract
part I|27 pages
Background
chapter 1|13 pages
The Evolution of a New Field
View abstract
chapter 2|13 pages
Expert Motivations
View abstract
part II|44 pages
Applications
chapter 3|10 pages
Early Alert and Student Success
View abstract
chapter 4|7 pages
Course Recommendation
View abstract
chapter 5|10 pages
Adaptive Learning
View abstract
chapter 6|13 pages
Curriculum Design
View abstract
chapter 7|3 pages
Expert Thoughts on Applications
View abstract
part III|62 pages
Logistics
chapter 8|10 pages
Data
View abstract
chapter 9|11 pages
Metrics and Predictive Modelling
View abstract
chapter 10|14 pages
Visualisation
View abstract
chapter 11|12 pages
Intervention
View abstract
chapter 12|11 pages
Student-Facing Analytics
View abstract
chapter 13|3 pages
Expert Thoughts on Logistics
View abstract
part IV|35 pages
Technologies
chapter 14|10 pages
Architecture
View abstract
chapter 15|10 pages
Standards
View abstract
chapter 16|10 pages
Products
View abstract
chapter 17|4 pages
Expert Thoughts on Technologies
View abstract
part V|76 pages
Deployment
chapter 18|14 pages
Institutional Readiness
View abstract
chapter 19|14 pages
Project Planning
View abstract
chapter 20|14 pages
Ethics
View abstract
chapter 21|12 pages
Transparency and Consent
View abstract
chapter 22|14 pages
Privacy and Data Protection
View abstract
chapter 23|7 pages
Expert Thoughts on Deployment
View abstract
part VI|25 pages
Future Directions
chapter 24|17 pages
Emerging Techniques
View abstract
chapter 25|7 pages
Expert Visions
View abstract

Learning Analytics Explained draws extensively from case studies and interviews with experts in order to discuss emerging applications of the new field of learning analytics. Educational institutions increasingly collect data on students and their learning experiences, a practice that helps enhance courses, identify learners who require support, and provide a more personalized learning experience. There is, however, a corresponding need for guidance on how to carry out institutional projects, intervene effectively with students, and assess legal and ethical issues. This book provides that guidance while also covering the evolving technical architectures, standards, and products within the field.

TABLE OF CONTENTS
chapter |5 pages
Introduction
View abstract
part I|27 pages
Background
chapter 1|13 pages
The Evolution of a New Field
View abstract
chapter 2|13 pages
Expert Motivations
View abstract
part II|44 pages
Applications
chapter 3|10 pages
Early Alert and Student Success
View abstract
chapter 4|7 pages
Course Recommendation
View abstract
chapter 5|10 pages
Adaptive Learning
View abstract
chapter 6|13 pages
Curriculum Design
View abstract
chapter 7|3 pages
Expert Thoughts on Applications
View abstract
part III|62 pages
Logistics
chapter 8|10 pages
Data
View abstract
chapter 9|11 pages
Metrics and Predictive Modelling
View abstract
chapter 10|14 pages
Visualisation
View abstract
chapter 11|12 pages
Intervention
View abstract
chapter 12|11 pages
Student-Facing Analytics
View abstract
chapter 13|3 pages
Expert Thoughts on Logistics
View abstract
part IV|35 pages
Technologies
chapter 14|10 pages
Architecture
View abstract
chapter 15|10 pages
Standards
View abstract
chapter 16|10 pages
Products
View abstract
chapter 17|4 pages
Expert Thoughts on Technologies
View abstract
part V|76 pages
Deployment
chapter 18|14 pages
Institutional Readiness
View abstract
chapter 19|14 pages
Project Planning
View abstract
chapter 20|14 pages
Ethics
View abstract
chapter 21|12 pages
Transparency and Consent
View abstract
chapter 22|14 pages
Privacy and Data Protection
View abstract
chapter 23|7 pages
Expert Thoughts on Deployment
View abstract
part VI|25 pages
Future Directions
chapter 24|17 pages
Emerging Techniques
View abstract
chapter 25|7 pages
Expert Visions
View abstract
ABOUT THIS BOOK
ABOUT THIS BOOK

Learning Analytics Explained draws extensively from case studies and interviews with experts in order to discuss emerging applications of the new field of learning analytics. Educational institutions increasingly collect data on students and their learning experiences, a practice that helps enhance courses, identify learners who require support, and provide a more personalized learning experience. There is, however, a corresponding need for guidance on how to carry out institutional projects, intervene effectively with students, and assess legal and ethical issues. This book provides that guidance while also covering the evolving technical architectures, standards, and products within the field.

TABLE OF CONTENTS
chapter |5 pages
Introduction
View abstract
part I|27 pages
Background
chapter 1|13 pages
The Evolution of a New Field
View abstract
chapter 2|13 pages
Expert Motivations
View abstract
part II|44 pages
Applications
chapter 3|10 pages
Early Alert and Student Success
View abstract
chapter 4|7 pages
Course Recommendation
View abstract
chapter 5|10 pages
Adaptive Learning
View abstract
chapter 6|13 pages
Curriculum Design
View abstract
chapter 7|3 pages
Expert Thoughts on Applications
View abstract
part III|62 pages
Logistics
chapter 8|10 pages
Data
View abstract
chapter 9|11 pages
Metrics and Predictive Modelling
View abstract
chapter 10|14 pages
Visualisation
View abstract
chapter 11|12 pages
Intervention
View abstract
chapter 12|11 pages
Student-Facing Analytics
View abstract
chapter 13|3 pages
Expert Thoughts on Logistics
View abstract
part IV|35 pages
Technologies
chapter 14|10 pages
Architecture
View abstract
chapter 15|10 pages
Standards
View abstract
chapter 16|10 pages
Products
View abstract
chapter 17|4 pages
Expert Thoughts on Technologies
View abstract
part V|76 pages
Deployment
chapter 18|14 pages
Institutional Readiness
View abstract
chapter 19|14 pages
Project Planning
View abstract
chapter 20|14 pages
Ethics
View abstract
chapter 21|12 pages
Transparency and Consent
View abstract
chapter 22|14 pages
Privacy and Data Protection
View abstract
chapter 23|7 pages
Expert Thoughts on Deployment
View abstract
part VI|25 pages
Future Directions
chapter 24|17 pages
Emerging Techniques
View abstract
chapter 25|7 pages
Expert Visions
View abstract

Learning Analytics Explained draws extensively from case studies and interviews with experts in order to discuss emerging applications of the new field of learning analytics. Educational institutions increasingly collect data on students and their learning experiences, a practice that helps enhance courses, identify learners who require support, and provide a more personalized learning experience. There is, however, a corresponding need for guidance on how to carry out institutional projects, intervene effectively with students, and assess legal and ethical issues. This book provides that guidance while also covering the evolving technical architectures, standards, and products within the field.

TABLE OF CONTENTS
chapter |5 pages
Introduction
View abstract
part I|27 pages
Background
chapter 1|13 pages
The Evolution of a New Field
View abstract
chapter 2|13 pages
Expert Motivations
View abstract
part II|44 pages
Applications
chapter 3|10 pages
Early Alert and Student Success
View abstract
chapter 4|7 pages
Course Recommendation
View abstract
chapter 5|10 pages
Adaptive Learning
View abstract
chapter 6|13 pages
Curriculum Design
View abstract
chapter 7|3 pages
Expert Thoughts on Applications
View abstract
part III|62 pages
Logistics
chapter 8|10 pages
Data
View abstract
chapter 9|11 pages
Metrics and Predictive Modelling
View abstract
chapter 10|14 pages
Visualisation
View abstract
chapter 11|12 pages
Intervention
View abstract
chapter 12|11 pages
Student-Facing Analytics
View abstract
chapter 13|3 pages
Expert Thoughts on Logistics
View abstract
part IV|35 pages
Technologies
chapter 14|10 pages
Architecture
View abstract
chapter 15|10 pages
Standards
View abstract
chapter 16|10 pages
Products
View abstract
chapter 17|4 pages
Expert Thoughts on Technologies
View abstract
part V|76 pages
Deployment
chapter 18|14 pages
Institutional Readiness
View abstract
chapter 19|14 pages
Project Planning
View abstract
chapter 20|14 pages
Ethics
View abstract
chapter 21|12 pages
Transparency and Consent
View abstract
chapter 22|14 pages
Privacy and Data Protection
View abstract
chapter 23|7 pages
Expert Thoughts on Deployment
View abstract
part VI|25 pages
Future Directions
chapter 24|17 pages
Emerging Techniques
View abstract
chapter 25|7 pages
Expert Visions
View abstract
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