This book provides a comprehensive introduction to the theory and practice of diagnostic
classification models (DCMs), which are useful for statistically driven diagnostic decision …

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 …

We describe a method for extracting Boolean implications (if-then relationships) in very large
amounts of gene expression microarray data. A meta-analysis of data from thousands of …

An intelligent tutoring system for learning basic statistics, called Stat-Knowlab, is presented
and analyzed. The algorithms implemented in the system are based on the competence …

Latent class analysis is an analytic technique often used in educational and psychological
research to identify meaningful groups of individuals within a larger heterogeneous …

Two theories of current interest and of mathematical and computational substance
concerning knowledge assessment in education are discussed. These are the theory of …

In knowledge space theory (KST), knowledge structure is an effective feature to evaluate
individuals' knowledge and guide future learning. How to construct knowledge structures is …

The methodologies for the construction of a knowledge structure mainly refer to the query to
experts, the skill maps, and the data-driven approaches. This last method is of growing …

One of the most crucial issues in knowledge space theory is the construction of the so-called
knowledge structures. In the present paper, a new data-driven procedure for large data sets …

The conjunctive model of skill map reflects a way to solve the items in a knowledge domain.
Currently, a skill map has been transformed into a formal context to construct a knowledge …