Modelling User Linguistic Communicative Competences for Individual and Collaborative Learning

Abstract

In this article, an innovative framework for use in Intelligent Computer-Assisted Language Learning (henceforth, ICALL) systems (as developed by the ATLAS research group) is presented in terms of the different models that compose it. It is argued that such a general framework allows the design and development of ICALL systems in a technologically, pedagogically and linguistically robust fashion, thereby avoiding the use of ad hoc knowledge models, which prove difficult to move from one system to another. Such a framework has been designed to overcome three problems present in most second language learning systems: the oversimplification and reduction of the vastness and complexity of the learning domain to a few formal linguistic aspects (studied in closed and decontextualised activities), the lack of underlying pedagogic principles, and the complexity of automatic language parsing and speech recognition. The framework attempts to capture and model the relevant pedagogic, linguistic and technological elements for the effective development of second language (henceforth, L2) competence. One of the goals were that any ICALL system developed around this framework would structure the complex network of communicative language competences (linguistic, pragmatic and sociolinguistic) and processes (reception, production and interaction) within the L2 learning process in a causal quantitative way, adapting such process to the progress made by a given student.