Learning Analytics in R with SNA, LSA, and MPIA
Springer | Computer Science | May 6 2016 | ISBN-10: 3319287893 | 275 pages | pdf | 9.45 mb
Authors: Wild, Fridolin
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
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.
The hybrid algorithm is implemented in the statistical programming language and environment R, introducing packages which capture – through matrix algebra – elements of learners’ work with more knowledgeable others and resourceful content artefacts. The book provides comprehensive package-by-package application examples, and code samples that guide the reader through the MPIA model to show how the MPIA landscape can be constructed and the learner’s journey mapped and analysed. This building block application will allow the reader to progress to using and building analytics to guide students and support decision-making in learning.
Number of Illustrations and Tables
47 b/w illustrations, 59 illustrations in colour
Topics
Data Mining and Knowledge Discovery
Computational Linguistics
Mathematics in the Humanities and Social Sciences
Educational Technology
Philosophy of Language
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