Inhaltsangabe
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.
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