Learning Analytics Explained 1st Edition by Niall Sclater – Ebook PDF Instant Download/Delivery: 113893173X ,9781138931732
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Product details:
ISBN 10: 113893173X
ISBN 13: 9781138931732
Author: Niall Sclater
Learning Analytics Explained 1st Edition Table of contents:
PART I: Background
1. The Evolution of a New Field
The Opportunities Presented by Big Data and Analytics
Data-Informed Decision Making
Pressures on Institutions
Influences
A Confusing Mix of Disciplines and Terminology
Focus of Activity
Developing the Community
Further Evolution of the Field
References
2. Expert Motivations
Understanding the Learning Process
Enhancing Learning
A Fascination with Data
Personalisation
Education and the Labour Market
Involvement in a New, Interdisciplinary Field
Institutional Motivations
Reference
PART II: Applications
3. Early Alert and Student Success
Models to Predict Student Success
Validity of the Models
Effectiveness of the Interventions
References
4. Course Recommendation
Approaches to Recommendation
Conclusion
References
5. Adaptive Learning
Definitions
Types of Adaptive Learning System
Benefits
Integrating Adaptive Learning Systems with other Data and Systems
Conclusion
References
6. Curriculum Design
The Importance of Theory
Informing Learning Design with Learning Analytics
Representing Learning Designs and Learning Analytics
Analytics Tools to Help Assess Effectiveness of the Curriculum
Faculty Skills in Interpreting the Analytics
Conclusion
References
7. Expert Thoughts on Applications
Adaptive Learning
Understanding the Learning Process
Linking Learning Analytics to Curriculum and Learning Design
PART III: Logistics
8. Data
Types of Data used for Learning Analytics
Data Sources
Incorporating Data from Outside the Institution
Preparing the Data for Use in Learning Analytics
Conclusion
References
9. Metrics and Predictive Modelling
Developing Metrics from the Data
Linear Regression
Logistic Regression
Naïve Bayes
Conclusion
References
10. Visualisation
Dashboards
Other Cohort Overview Visualisations
Representing Trends and Changes over Time
Conclusion
References
11. Intervention
Feedback
Triggers
Types of Intervention
Timing and Frequency
Wording
Adoption
Evaluating the Interventions
Conclusion
References
12. Student-Facing Analytics
The Quantified Self
Dashboards
Apps
Conclusion
References
13. Expert Thoughts on Logistics
Improving the Data Sources
Improving the Analytics
Enhancing Feedback
PART IV: Technologies
14. Architecture
Extraction and Transformation
Loading and Storing
Processing
Alerting
Displaying
Software Components
Conclusion
References
15. Standards
Benefits
Learning Technology Standards
Emerging Standards for Learning Analytics
Predictive Model Markup Languages
Student Data
Learning Activity Data
Conclusion
References
16. Products
LMS Engagement Reporting Tools
LMS-Centric Analytics Systems
SIS-Centric Analytics Systems
Business Intelligence Systems
Platform-Independent Solutions
Application-Specific Products
Niche Components
Learning Activity Provider Systems
Conclusion
References
17. Expert Thoughts on Technologies
Data Access
Standards, Open Architectures and Open-Source Systems
Tools
Reference
PART V: Deployment
18. Institutional Readiness
Leadership
Culture and Vision
Strategy and Investment
Structure and Governance
Technology and Data
Skills
Conclusion
References
19. Project Planning
Objectives
Stakeholders
Concerns of Stakeholders
Communication and Awareness Raising
Workstreams
Budget
Timescales
Risks
Conclusion
References
20. Ethics
Ethical Approaches
Obligation to Use Learning Analytics
Flawed or Inadequate Data
Invalid Predictions
Loss of Autonomy
Demotivation
Negative Impacts of Continual Monitoring
Manipulation of the Analytics by Students
Human versus Computer Mediation of the Results
Obligations Resulting from the Analytics
Prejudicial Categorisation and Treatment of Students
Reduction of the Individual to a Metric
Triage
Conclusion
References
21. Transparency and Consent
Transparency
Student Input to Analytics Processes
Informed Consent
Consent and the Law
Privacy Policies
The Logistics of Requesting Consent
Consent for Interventions
Opting Out
New Uses for the Data
Unknown Future Uses of the Data
Conclusion
References
22. Privacy and Data Protection
The Legal Context
Sensitive Data
Publicly Available Data
MOOC Data
Anonymisation
Restricting Access to Student Data
External Access
Data Ownership
Student Access to their Analytics
Data Stewardship
References
23. Expert Thoughts on Deployment
Organisational Culture
Data Literacy
Leadership
Funding
Ethics and Legal Issues
The Need for Systemic Deployment
PART VI: Future Directions
24. Emerging Techniques
Discourse Analytics
Social Network Analysis
Sentiment and Emotion Analytics
Conclusion
References
25. Expert Visions
Exploring New Data Sources
Analytics as Normal Practice
Personalisation
Linking Research to Practice
Reference
Index
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