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Knowledge Spaces

Edited by Jean-Claude Falmagne (), Dietrich Albert (), Christopher Doble (), David Eppstein () and Xiangen Hu ()

in Springer Books from Springer

Date: 2013
Edition: 2013
ISBN: 978-3-642-35329-1
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Chapters in this book:

Ch 1 Overview
Jean-Claude Falmagne and Christopher Doble
Ch 2 Assessing Mathematical Knowledge in a Learning Space
Eric Cosyn, Christopher Doble, Jean-Claude Falmagne, Arnaud Lenoble, Nicolas Thiéry and Hasan Uzun
Ch 3 ALEKS-based Placement at the University of Illinois
Alison Ahlgren Reddy and Marc Harper
Ch 4 The Impact of a Mathematical Intelligent Tutoring System on Students’ Performance on Standardized High-Stake Tests
Jeremiah Sullins, Rob Meister, Scotty D. Craig, William M. Wilson, Anna Bargagliotti and Xiangen Hu
Ch 5 A Potential Technological Solution for Reducing the Achievement Gap Between White And Black Students
Xiangen Hu, Yonghong Jade Xu, Charles Hall, Kristin Walker and Theresa Okwumabua
Ch 6 A Commercial Implementation of Knowledge Space Theory In College General Chemistry
Christopher J. Grayce
Ch 7 Using Knowledge Space Theory to Assess Student Understanding of Chemistry
Mare Taagepera and Ramesh D. Arasasingham
Ch 8 Learning Spaces: A Mathematical Compendium
Jean-Paul Doignon, Jean-Claude Falmagne and Eric Cosyn
Ch 9 Recent Developments in Performance-based Knowledge Space Theory
Ali Ünlü, Martin Schrepp, Jürgen Heller, Cord Hockemeyer, Gudrun Wesiak and Dietrich Albert
Ch 10 Heuristics for Generating and Validating Surmise Relations across, between and within Sets/Tests
Dietrich Albert, Gudrun Wesiak and Ali Ünlü
Ch 11 Skills, Competencies and Knowledge Structures
Jürgen Heller, Ali Ünlü and Dietrich Albert
Ch 12 Recent Developments in Competence-based Knowledge Space Theory
Jürgen Heller, Thomas Augustin, Cord Hockemeyer, Luca Stefanutti and Dietrich Albert
Ch 13 Learning Sequences: An Efficient Data Structure for Learning Spaces
David Eppstein
Ch 14 Projection, Decomposition, and Adaption of Learning Spaces
David Eppstein

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DOI: 10.1007/978-3-642-35329-1

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