A Recommender System as a Support and Training Tool
Ilaria Torre, Simone Torsani · 2016
The research project we present in this paper concerns an ontology-based recommender for teacher training and support. An important issue in Computer-Assisted Language Learning education is the complexity of exploiting technology in order to enhance language teaching. The integration of technology into language education is a rather complex achievement, which implies the ability to understand the potential of a tool for language development in different settings. Thus, the aim of the project is to exploit content-based techniques to recommend the most suited instructional design solutions given the mentioned conditions. The tool provides step-by-step recommendations and explanations and is also able to generate scenarios so that it can be used as a valuable training tool. In this context, the paper presents an example of step-by-step recommendation and the semantic modeling of learning tasks, competences and activities. Finally it reports the results of a study aimed to evaluate the correctness of the recommended solutions and explore the potential impact on the end users.