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Learning Analytics Explained.

Author: Niall Sclater
Publisher: Florence : Taylor and Francis, 2017.
Edition/Format:   eBook : Document : EnglishView all editions and formats
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Sclater, Niall.
Learning Analytics Explained.
Florence : Taylor and Francis, ©2017
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Niall Sclater
ISBN: 9781317394563 1317394569
OCLC Number: 973834493
Notes: LMS Engagement Reporting Tools.
Description: 1 online resource (291 pages)
Contents: Covers; Half Title; Title Page; Copyright Page; Dedication; Table of Contents; Preface; Acknowledgements; List of Abbreviations; Introduction; Part I: Background; Part II: Applications; Part III: Logistics; Part IV: Technologies; Part V: Deployment; Part VI: Future Directions; Expert Voices; 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. Integrating Adaptive Learning Systems with other Data and SystemsConclusion; 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 AnalyticsData 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; 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 AnalyticsThe 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.

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Learning Analytics Explained is a must-read for senior managers, learning technologists, and all academics interested in how learning is impacted by the volume of information and the new kinds of Read more...

 
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