Abstract
In Chapter 13 we described learning sequences, a powerful tool for the computer representation of learning spaces, and we showed how to use learning sequences as the basis for computer algorithms that efficiently perform the state generation necessary for knowledge assessment in a learning space.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Eppstein, D. (2013). Projection, Decomposition, and Adaption of Learning Spaces. In: Falmagne, JC., Albert, D., Doble, C., Eppstein, D., Hu, X. (eds) Knowledge Spaces. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35329-1_14
Download citation
DOI: https://doi.org/10.1007/978-3-642-35329-1_14
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35328-4
Online ISBN: 978-3-642-35329-1
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)