Recommendation systems (RS) have traditionally targeted adult users, who can directly and explicitly identify their wants and needs, and are often willing to provide feedback in ther form of ratings and reviews. This is rarely, if at all avaiable from younger populations. As such, existing algorithmic solutions are not responding to children’s needs. RS for children have only recentry began to be studied, and are primarely related to RS in education-related enviroments. When focused on this particular audience, the role of RS needs to be reformulated, as it is not sufficient for RS to identify items that match users’ preferences and interests. Instead, it is imperative they also consider children’s needs from multiple perspectives: educational developmental, and engagement, to name a few. The research agenda established for this area is focused on designing and developing RS that best serve and respond to young users.


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