Automatic Code Generation for Language-Learning Applications

Abstract

Language-learning applications define exercises that are pedagogical tools to introduce new language concepts. The development of this type of applications is complex due to the diversity of language-learning methodologies, the variety of execution environments and the number of different technologies that can be used. This article proposes a complete Model-Driven Architecture (MDA) approach, from the definition of the Computational Independent Model (CIM layer) to the Implementation Specific Model (ISM layer), and the process of the necessary transformations for the automatic generation of the source code (in HTML and JavaScript) of language-learning applications. To carry out the model-to-model and model-to-text transformations, the ATLAS Transformation Language (ATL) and Acceleo transformation languages have been used respectively. The proposal has been validated through the modeling and the complete automatic generation of source code of two Learning Activity Mechanisms (LAM), which are used within methodologies such as Duolingo and Busuu: LAM Image-Audio-Text and LAM Audio-Text Options.