Skip to main content

Knowledge Spaces

Applications in Education

  • Book
  • © 2013

Overview

  • The combinatoric and stochastic search engine described in the book monitors a unique knowledge assessment mechanism that produces the exact list of concepts that the student is ready to learn

  • This technology is meant to replace psychometric techniques and models that are the basis for current standardized testing

  • The technology is the basis of the ALEKS system, which has been used successfully by millions of students in the US and abroad in both K12 and higher education

This is a preview of subscription content, log in via an institution to check access.

Access this book

eBook USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (14 chapters)

  1. Learning in a Knowledge Space

  2. Recent Theoretical Progress

Keywords

About this book

The book describes up-to-date applications and relevant theoretical results. These applications come from various places, but the most important one, numerically speaking, is the internet based educational system ALEKS. The ALEKS system is bilingual English-Spanish and covers all of mathematics, from third grade to the end of high school, and chemistry. It is also widely used in higher education because US students are often poorly prepared when they reach the university level. The chapter by Taagepera and Arasasingham deals with the application of knowledge spaces, independent of ALEKS, to the teaching of college chemistry. The four chapters by Albert and his collaborators strive to give cognitive interpretations to the combinatoric structures obtained and used by the ALEKS system. The contribution by Eppstein is technical and develops means of searching the knowledge structure efficiently.

Reviews

From the reviews:

“The editors of this book have compiled a set of papers that provide insight into knowledge space theory and related practical deployment issues. … anyone involved in a learning discipline will find this book to be a helpful guide to the terms, issues, and theory development of knowledge spaces. I recommend it for researchers and practitioners willing to improve their understanding of current knowledge space theory and the possibilities for its deployment.” (F. J. Ruzic, Computing Reviews, November, 2013)

Editors and Affiliations

  • School of Social Sciences, Dept. Cognitive Sciences, University of California, Irvine, Irvine, USA

    Jean-Claude Falmagne

  • , Department of Psychology, University of Graz, Graz, Austria

    Dietrich Albert

  • ALEKS Corporation, Irvine, USA

    Christopher Doble

  • Donald Bren School of Information &, Computer Sciences, University of California, Irvine, Irvine, USA

    David Eppstein

  • , Department of Psychology, University of Memphis, Memphis, USA

    Xiangen Hu

About the editors

Dietrich Albert is an emeritus professor of Cognitive Psychology at the University of Graz and a senior scientist in Knowledge Management at the Graz University of Technology (Austria, Europe). His R&D interests cover several areas, including learning, memory, decision making, anxiety, knowledge and competences.
Chris Doble is the Math Content Development Manager at ALEKS Corporation.  Along with his focus on using technology in the teaching and learning of mathematics, he maintains academic interests and publishes in measurement theory and psychophysics.
Jean-Claude Falmagne is an emeritus professor of Cognitive Sciences at the University of California, Irvine. His research interests focus on the application of mathematics to educational technology, psychophysics, choice theory, and philosophy of sciences, in particular measurement theory.
David Eppstein is a professor of Computer Sciences at the University of California, Irvine. His research focuses on the design and analysis of algorithms, and especially graph algorithms and computational geometry.
Xiangen Hu is a professor in the Department of Psychology at The University of Memphis. His research interests include General Processing Tree (GPT) models, categorical data analysis, knowledge representation, computerized tutoring, and advanced distributed learning.


Bibliographic Information

Publish with us