As an initial step towards enabling the adaptation of (popular, and widely used) web search environments so that they can better serve children and ease their path towards information discovery, we introduce Recognizing Young Searchers (RYSe). RYSe leverages lexical, syntactical, spelling/punctuation, and vocabulary features that align with the Concrete Operational stage of development (originally identified by Jean Piaget) in an attempt to identify users that are in this stage. The concrete operational stage is commonly associated with children ages 7-11. Findings emerging from our initial empirical exploration using single queries formulated by children and sample queries from adults showcase the feasibility of relying on different cognitive traits inferred from the short text of a single query to distinguish those that are formulated by younger searchers.

Music is an important part of childhood development, with online music listening platforms being a significant channel by which children consume music. Children's offline music listening behavior has been heavily researched, yet relatively few studies explore how their behavior manifests online. In this paper, we use data from LastFM 1 Billion and the Spotify API to explore online music listening behavior of children, ages 6-17, using education levels as lenses for our analysis. Understanding the music listening behavior of children can be used to inform the future design of recommender systems.

Purpose: The purpose of this paper is to examine strengths and limitations that search engines (SEs) exhibit when responding to web search queries associated with the grade school curriculum Design/methodology/approach: The authors employed a simulation-based experimental approach to conduct an in-depth empirical examination of SEs and used web search queries that capture information needs in different search scenarios. Findings: Outcomes from this study highlight that child-oriented SEs are more effective than traditional ones when filtering inappropriate resources, but often fail to retrieve educational materials. All SEs examined offered resources at reading levels higher than that of the target audience and often prioritized resources with popular top-level domain (e.g. “.com”). Practical implications: Findings have implications for human intervention, search literacy in schools, and the enhancement of existing SEs. Results shed light on the impact on children’s education that result from introducing misconception about SEs when these tools either retrieve no results or offer irrelevant resources, in response to web search queries pertinent to the grade school curriculum. Originality/value: The authors examined child-oriented and popular SEs retrieval of resources aligning with task objectives and user capabilities–resources that match user reading skills, do not contain hate-speech and sexually-explicit content, are non-opinionated, and are curriculum-relevant. Findings identified limitations of existing SEs (both directly or indirectly supporting young users) and demonstrate the need to improve SE filtering and ranking algorithms.

We present StoryTime, a book recommender for children. Our web-based recommender is co-designed with children and uses images to elicit their preferences. By building on existing solutions related to both visual interfaces and book recommendation strategies for children, StoryTime can generate suggestions without historical data or adult guidance. We discuss the benefts of StoryTime as a starting point for further research exploring the cold start problem, incorporating historical data, and needs related to children as a complex audience to enhance the recommendation process.