GOALS: generator of adaptive learning scenarios

Abstract

The problem of generating personalised learning activities for learners is a difficult task. The difficulty is compounded if the learning activity is mediated or presented through a serious game. In this paper, we present a system, called generator of adaptive learning scenarios (GOALS) that is capable of generating learning scenarios taking into account the learners' interaction traces, pedagogical objectives and the specificities of serious games. The generator we propose aims to be generic, i.e., independent of the application domain and serious games. To achieve this, we propose an architecture that organises the knowledge in three layers: domain concepts, pedagogical resources and serious game resources. This work has been conducted in the context of Cognitive Linguistic Elements Stimulations Project (CLES). This project targets the development of an online serious game dedicated to persons with cognitive disabilities. In order to validate our approaches, we conducted experiments in the context of CLES project. These experiments are based on comparative method that compares the results generated by our system with that of an expert. The results of the evaluations, conducted with a domain expert and end users, are also presented.