Intelligent tutoring systems for language learning

Abstract

Intelligent tutoring systems (ITS) are able to provide a personalized approach to learning by assuming the role of a real teacher/expert who adapts and steers the learning process according to the specific needs of each learner. This is done by taking into account a number of learner features and deciding on the best action to follow at any point in the learning process. Within the field of computer assisted language learning (CALL), the “computer-as-a-tutor” modality has been widely accepted for some time now, although it has long been overshadowed by the “computer-as-a-tool” modality. This was mainly due to the observable lack of interactivity of language learning systems and the inability of technology to show “intelligence”. However, the development of artificial intelligence in general, and natural language processing, user modeling and ITSs in particular, gave impetus for the development of the field referred to as intelligent CALL (ICALL). The paper at hand outlines and briefly discusses the issues surrounding the development and use of ITSs for language learning, taking also into account the broader context of (I)CALL, and gives an overview of such systems already in use.