The seven layers of complexity of recommender systems for children in educational contexts

Journal article (2019)

Authors

Emiliana Murgia Università degli Studi di Milano Bicocca

Monica Landoni University of Lugano

Theo Huibers University of Twente

Jerry Alan Fails Boise State University

M.S. Pera Boise State University

Affiliation

External organisation

Education Algorithm Interface Children Recommender systems Guidance Teachers Roles

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Published Date

2019

Language

English

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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.