Overview
- Interdisciplinary representation of the theory of Knowledge Spaces.
- Application oriented introduction based on real and simulated data.
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About this book
Knowledge spaces offer a rigorous mathematical foundation for various practical systems of knowledge assessment. An example is offered by the ALEKS system (Assessment and LEarning in Knowledge Spaces), a software for the assessment of mathematical knowledge. From a mathematical standpoint, knowledge spaces generalize partially ordered sets. They are investigated both from a combinatorial and a stochastic viewpoint. The results are applied to real and simulated data. The book gives a systematic presentation of research and extends the results to new situations. It is of interest to mathematically oriented readers in education, computer science and combinatorics at research and graduate levels. The text contains numerous examples and exercises and an extensive bibliography.
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Keywords
Table of contents (13 chapters)
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Front Matter
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Back Matter
Authors and Affiliations
Bibliographic Information
Book Title: Knowledge Spaces
Authors: Jean-Paul Doignon, Jean-Claude Falmagne
DOI: https://doi.org/10.1007/978-3-642-58625-5
Publisher: Springer Berlin, Heidelberg
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eBook Packages: Springer Book Archive
Copyright Information: Springer-Verlag Berlin Heidelberg 1999
Softcover ISBN: 978-3-540-64501-6Published: 20 October 1998
eBook ISBN: 978-3-642-58625-5Published: 06 December 2012
Edition Number: 1
Number of Pages: XVI, 334
Number of Illustrations: 4 b/w illustrations
Topics: Discrete Mathematics, Artificial Intelligence, Combinatorics