Learning languages: Implications for student modelling in ICALL

Abstract

Many factors affect the learning of a foreign language. When designing computer assisted language learning software it is usually not sufficient to think only about creating an exercise in the language, but students should be modelled in order to allow the program to take account of individuals' beliefs and learning. However, student models are criticised for various reasons, the most common of which include: 1. Modelling the learner places a great burden on the system, as it has sole responsibility for the creation of an accurate student model. 2. Student models are inadequate because it is not possible to model all aspects of a student's knowledge and learning. This paper describes the student model of an intelligent computer assisted language learning (ICALL) system which strives to overcome problems of traditional student models by taking into account issues important in the field of second language acquisition, and research in collaborative approaches to learning.