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Learning Analytics in R with SNA, LSA, and MPIA

  • Fridolin Wild

Table of contents

  1. Front Matter
    Pages i-xv
  2. Fridolin Wild
    Pages 1-21
  3. Fridolin Wild
    Pages 71-106
  4. Fridolin Wild
    Pages 107-131
  5. Fridolin Wild
    Pages 149-163
  6. Fridolin Wild
    Pages 165-181
  7. Fridolin Wild
    Pages 183-222
  8. Fridolin Wild
    Pages 223-245
  9. Fridolin Wild
    Pages 247-264
  10. Back Matter
    Pages 265-275

About this book

Introduction

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.

Keywords

Latent Semantic Analysis Learning Learning Analytics Linear Algebra Social Network Analysis

Authors and affiliations

  • Fridolin Wild
    • 1
  1. 1.Performance Augmentation Lab, DepartmentOxford Brookes UniversityOxfordUnited Kingdom

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-28791-1
  • Copyright Information Springer International Publishing Switzerland 2016
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-28789-8
  • Online ISBN 978-3-319-28791-1
  • Buy this book on publisher's site
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