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Table of Contents
Preface
1.Introduction
2.Learning Theory and Algorithmic Quality Characteristics
3.Representing and Analysing Purposiveness with SNA
4.Representing and Analysing Meaning with LSA
5.Meaningful, Purposive Interaction Analysis
6.Visual Analytics Using Vector Maps as Projection Surfaces
7.Calibrating for Specific Domains
8.Implementation: The MPIA Package
9.MPIA in Action: Example Learning Analytics
10.Evaluation
11.Conclusion and Outlook
Annex A: Classes and Methods of the MPIA Package.
1.Introduction
2.Learning Theory and Algorithmic Quality Characteristics
3.Representing and Analysing Purposiveness with SNA
4.Representing and Analysing Meaning with LSA
5.Meaningful, Purposive Interaction Analysis
6.Visual Analytics Using Vector Maps as Projection Surfaces
7.Calibrating for Specific Domains
8.Implementation: The MPIA Package
9.MPIA in Action: Example Learning Analytics
10.Evaluation
11.Conclusion and Outlook
Annex A: Classes and Methods of the MPIA Package.