Recommender systems

Abstract

The purpose of this chapter is to describe a software system that allows for discovering non-traditional education resources such as software applications, events or people who may participate as experts in some Learning Activity. Selecting the more suitable educational resources to create learning activities in the classroom may be a challenging task for teachers in primary and secondary education because of the large amount of existing educational resources. The iTEC Scenario Development Environment (SDE), is a software application aimed at offering supporting services in the form of suggestions or recommendations oriented to assist teachers in their decision-making when selecting the most appropriate elements to deploy learning activities in a particular school. The recommender is based on an ontology that was developed in a collaborative way by a multi-disciplinary team of experts. Its data set is fed not only from entries that come from registrations made by human users—using tools from the iTEC Cloud—but also from software agents that perform web scraping, that is, automatic enrichment of the semantic data with additional information that come from web sources that are external to the project. Therefore, the recommender system takes into account contextual factors when calculating the relevance of every resource. The SDE defines an API that allows third-party clients to integrate its functionalities. This chapter presents two success stories that have benefited from the SDE to enhance educational authoring tools with semantic web-based recommendations.