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How Interval and Fuzzy Techniques Can Improve Teaching

Processing Educational Data: From Traditional Statistical Techniques to an Appropriate Combination of Probabilistic, Interval, and Fuzzy Approaches

  • Olga Kosheleva
  • Karen Villaverde

Part of the Studies in Computational Intelligence book series (SCI, volume 750)

Table of contents

  1. Front Matter
    Pages i-x
  2. How to Motivate Students

    1. Front Matter
      Pages 9-9
    2. Olga Kosheleva, Karen Villaverde
      Pages 11-14
    3. Olga Kosheleva, Karen Villaverde
      Pages 125-130
  3. In What Order to Present the Material

    1. Front Matter
      Pages 131-131
    2. Olga Kosheleva, Karen Villaverde
      Pages 133-134
    3. Olga Kosheleva, Karen Villaverde
      Pages 135-145
    4. Olga Kosheleva, Karen Villaverde
      Pages 147-151
    5. Olga Kosheleva, Karen Villaverde
      Pages 161-165
  4. How to Select an Appropriate Way of Teaching Each Topic

  5. How to Assess Students, Teachers, and Teaching Techniques

    1. Front Matter
      Pages 245-245
    2. Olga Kosheleva, Karen Villaverde
      Pages 249-251
    3. Olga Kosheleva, Karen Villaverde
      Pages 253-265
    4. Olga Kosheleva, Karen Villaverde
      Pages 267-277
    5. Olga Kosheleva, Karen Villaverde
      Pages 279-285
    6. Olga Kosheleva, Karen Villaverde
      Pages 287-293
    7. Olga Kosheleva, Karen Villaverde
      Pages 295-303
    8. Olga Kosheleva, Karen Villaverde
      Pages 305-318
    9. Olga Kosheleva, Karen Villaverde
      Pages 319-334
    10. Olga Kosheleva, Karen Villaverde
      Pages 335-344
    11. Olga Kosheleva, Karen Villaverde
      Pages 353-353
  6. Back Matter
    Pages 355-362

About this book

Introduction

This book explains how to teach better and presents the latest research on processing educational data and presents traditional statistical techniques as well as probabilistic, interval, and fuzzy approaches. Teaching is a very rewarding activity; it is also a very difficult one – because it is largely an art. There is a lot of advice on teaching available, but it is usually informal and is not easy to follow. To remedy this situation, it is reasonable to use techniques specifically designed to handle such imprecise knowledge: the fuzzy logic techniques.

Since there are a large number of statistical studies of different teaching techniques, the authors combined statistical and fuzzy approaches to process the educational data in order to provide insights into improving all the stages of the education process: from forming a curriculum to deciding in which order to present the material to grading the assignments and exams.

The authors do not claim to have solved all the problems of education. Instead they show, using numerous examples, that an innovative combination of different uncertainty techniques can improve teaching. The book offers teachers and instructors valuable advice and provides researchers in pedagogical and fuzzy areas with techniques to further advance teaching.

Keywords

Computational Intelligence Fuzzy Approaches Interval Approaches Probabilistic Approaches Processing Educational Data Traditional Statistical Techniques

Authors and affiliations

  • Olga Kosheleva
    • 1
  • Karen Villaverde
    • 2
  1. 1.Department of Teacher EducationUniversity of TexasEl PasoUSA
  2. 2.Department of MathematicsNew Mexico State UniversityLas CrucesUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-662-55993-2
  • Copyright Information Springer-Verlag GmbH Germany 2018
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-662-55991-8
  • Online ISBN 978-3-662-55993-2
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • Buy this book on publisher's site
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