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: Contribution to journalConference articleScientificpeer-review

9 Citations (Scopus)

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 languageEnglish
Pages (from-to)5-9
Number of pages5
JournalCEUR Workshop Proceedings
Volume2449
Publication statusPublished - 2019
Externally publishedYes
Event3rd Workshop on Recommendation in Complex Scenarios, ComplexRec 2019 - Copenhagen, Denmark
Duration: 20 Sept 201920 Sept 2019

Keywords

  • Algorithm
  • Children
  • Education
  • Guidance
  • Interface
  • Recommender systems
  • Roles
  • Teachers

Fingerprint

Dive into the research topics of 'The seven layers of complexity of recommender systems for children in educational contexts'. Together they form a unique fingerprint.

Cite this