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.

Popular search engines (SE) favored by children are optimized neither to respond to their search behavior and abilities, nor retrieve resources that align with classroom standards. Further, attempts to adapt SE to support children's inquiries have been one-dimensional, e.g., satisfy users' reading skills or search expertise. To ease the process of locating resources relevant to children in the classroom, we introduce KORSCE, a ranking strategy designed to complement the functionality of existing SE. KORSCE employs a multi-objective approach to re-rank resources retrieved by popular SE to fit a specific target audience and setting based on varied criteria: appropriateness, readability, objectivity, and curriculum-alignment. Experimental results and insights from an expert appraiser showcase KORSCE'S ability to prioritize resources that assist children's information-seeking activities at school.