The Seven Layers of Complexity of Recommender Systems for Children in Educational Contexts
Emiliana Murgia, Monica Landoni, Theo W.C. Huibers, Jerry Alan Fails, Maria Soledad Pera. 2019. “The Seven Layers of Complexity of Recommender Systems for Children in Educational Contexts”. In Proceedings of the Workshop on Recommendation in Complex Scenarios (CEUR 2019).
Abstract
Recommender systems (RS) in their majority focus on an average target user: adults. We argue that for non-traditional populations in specific contexts, the task is not as straightforward–we must look beyond existing recommendation algorithms, premises for interface design, and standard evaluation metrics and frameworks. We explore the complexity of RS in an educational context for which young children are the target audience. The aim of this position paper is to spell out, label, and organize the specific layers of complexity observed in this context.