Modelado del estudiante para el STI ELE-TUTOR: diseño de un componente adaptativo para apoyar la competencia lingüística del español como lengua extranjera

Abstract

Intelligent Tutorial Systems (ITS) for language teaching are computational applications that are capable to process natural language input provided by a language student, in order to give feedback strategies according to their linguistic competence. However, in order to achieve this adaptability, it is important to develop a student module, which stores and processes information about each one of the students that interact with the system. The present work is a design of a student module for an intelligent tutorial system (ITS) to teach Spanish as a foreign language considering the B2 level of the Common European Framework which takes as variables the student's level of proficiency, their learning style and the type of language error made by them during the interaction with the ITS. Due to the fact that the proficiency level variable changes as the student works on the exercises, the student module also contains a diagnosis and update system for the data that uses a Bayesian belief network. The output of the student module is a vector with specific values for each variable, which is delivered to a tutor module that will decide which feedback strategies should be used.