This second part of an overview of fuzzy set-based methods for approximate reasoning is
devoted to deductive approaches dealing with knowledge bases made of a collection of …

Student modelling-the task of building dynamic models of student ability-is fraught with
uncertainty, caused by such factors as multiple sources of student errors, careless errors and …

The student record (SR) is a major source of input for any decision making done by an
Intelligent Tutoring System (ITS) and is a basis of the individualization in such systems …

A formal, computational, semantically clean representation of natural language is presented.
This representation captures the fact that logical inferences in natural language crucially …

Several fuzzy logic programming systems that deal with fuzzy sets as data in programs have
been developed, but they lack the fundamentals of a theorem prover, whence the …

This paper examines two currently popular models of interactive learning. While both
emphasize the importance of acquiring metacognitive intelligence, each represents a …

This paper presents an approach to local student modeling in mathematics intelligent tutors.
A knowledge representation is developed that stores separately the semantic and structural …

Student modeling—the task of building dynamic models of student ability—is fraught with
uncertainty, caused by such factors as multiple sources of student errors, careless errors and …

This writing lays the foundation for a model of natural human reasoning with imprecise
linguistic information. Key to the model is a collection of abstraction mechanisms based on …

Computational Linguistics Research Group “TALL”, “GOOD”, “HIGH” — COMPARED TO WHAT?
Steffen Staab & Udo Hahn Page 1 LIF Computational Linguistics Research Group …