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Learning Analytics in R with SNA, LSA, and MPIA

BuchGebunden
275 Seiten
Englisch
Springererschienen am11.04.20161st ed. 2016
This book introduces Meaningful Purposive Interaction Analysis (MPIA) theory, which combines social network analysis (SNA) with latent semantic analysis (LSA) to help create and analyse a meaningful learning landscape from the digital traces left by a learning community in the co-construction of knowledge.mehr
Verfügbare Formate
BuchGebunden
EUR106,99
BuchKartoniert, Paperback
EUR106,99
E-BookPDF1 - PDF WatermarkE-Book
EUR96,29

Produkt

KlappentextThis book introduces Meaningful Purposive Interaction Analysis (MPIA) theory, which combines social network analysis (SNA) with latent semantic analysis (LSA) to help create and analyse a meaningful learning landscape from the digital traces left by a learning community in the co-construction of knowledge.
Zusammenfassung
Written in a tutorial-style

Includes reproducible examples and demos

Provides aesthetic visual analytics

Extends the analysis instruments significantly beyond doc-term mapping

Provides a technological framework and methodology for study and research
Details
ISBN/GTIN978-3-319-28789-8
ProduktartBuch
EinbandartGebunden
Verlag
Erscheinungsjahr2016
Erscheinungsdatum11.04.2016
Auflage1st ed. 2016
Seiten275 Seiten
SpracheEnglisch
Gewicht549 g
IllustrationenXV, 275 p. 106 illus., 59 illus. in color.
Artikel-Nr.36510818

Inhalt/Kritik

Inhaltsverzeichnis
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.mehr

Schlagworte

Autor

Dr Fridolin Wild is a Senior Research Fellow, leading the Performance Augmentation Lab (PAL) of Oxford Brookes University. With the research and development of the lab, Fridolin seeks to close the dissociative gap between abstract knowledge and its practical application, researching radically new forms of linking directly from knowing something 'in principle' to applying that knowledge 'in practice' and speeding its refinement and integration into polished performance. Fridolin is leading numerous EU, European Space Agency, and nationally funded research projects, including WEKIT, TCBL, ARPASS, Tellme, TELmap, cRunch, Stellar, Role, LTfLL, iCamp, and Prolearn. Fridolin is the voted treasurer of the European Association of Technology Enhanced Learning (EATEL) and leads its Special Interest Group on Wearable-Enhanced Learning (SIG WELL). He chairs the working group on Augmented Reality Learning Experience Models (ARLEM) of the IEEE Standards Association as well as the Natural Language Processing task view of the Comprehensive R Archive Network (CRAN).Fridolin also holds the post as Research Fellow of the Open University of the UK. Before, Fridolin worked as a researcher at the Vienna University of Economics and Business in Austria from 2004 to 2009. He studied at the University of Regensburg, Germany, with extra-murals at the Ludwig Maximilian University of Munich and the University of Hildesheim.