Markov Processes in Learning Spaces

Autor: Jean-Claude Falmagne
Rok vydání: 2015
Předmět:
DOI: 10.1016/b978-0-08-097086-8.43056-4
Popis: A learning space is a family of sets satisfying certain conditions. The sets are called knowledge states. In the most common application of these concepts, a knowledge state is a set of items of knowledge, such as all the concepts mastered by a student in some part of mathematics. Two applications of Markov processes to learning spaces are described. The most important one is the core component of an assessment system designed to uncover the knowledge state of the student by systematic questioning. A learning space can also be used as a teaching instrument. The student masters the items one by one, progressively increasing the size of his or her knowledge state. The second Markov process is a stochastic mechanism tracking the gradual learning of an item.
Databáze: OpenAIRE