The Seven Layers of Complexity of Recommender Systems for Children in Educational Contexts

Emiliana Murgia, Monica Landoni, Theo Huibers, Jerry Alan Fails, Maria Soledad Pera

Research output: Chapter in Book/Report/Conference proceedingChapter

10 Scopus citations
1 Downloads (Pure)

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.

Original languageAmerican English
Title of host publicationCEUR Workshop Proceedings
StatePublished - 1 Jan 2019

Keywords

  • children
  • education
  • guidance
  • interface
  • recommender systems
  • roles

EGS Disciplines

  • Computer Sciences
  • Educational Technology

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