Abstract
Smile and Learn is an Ed-Tech company that runs a smart library with more that 100 applications, games and interactive stories, aimed at children aged two to 10 and their families. The platform gathers thousands of data points from the interaction with the system to subsequently offer reports and recommendations. Given the complexity of navigating all the content, the library implements a recommender system. The purpose of this paper is to evaluate two aspects of such system focused on children: the influence of the order of recommendations on user exploratory behavior, and the impact of the choice of the recommendation algorithm on engagement. The assessment, based on data collected between 15 October 2018 and 1 December 2018, required the analysis of the number of clicks performed on the recommendations depending on their ordering, and an A/B/C testing where two standard recommendation algorithms were compared with a random recommendation that served as baseline. The results suggest a direct connection between the order of the recommendation and the interest raised, and the superiority of recommendations based on popularity against other alternatives.
Highlights
Introduction and BackgroundSmile and Learn’s smart library is an application in the educational technology (Ed-Tech) space which is aimed at children
In this paper we have described and evaluated the behavior of a recommender system in the scope of an Ed-Tech application aimed at children aged 2–10 and their families
The smart library gathers thousands of data points based on user interaction and uses that information to generate tailored reports and recommendations
Summary
Introduction and BackgroundSmile and Learn’s smart library is an application in the educational technology (Ed-Tech) space which is aimed at children. As of December 2018, the platform features a total of 107 games, which are grouped according to Gardner’s theory of multiple intelligences [1]. The application registers thousands of data points as a result of user interaction. The initial interaction with the application requires choosing among a large set of alternatives that are organized according to broad categories. The different games are grouped in so-called “worlds”, with each world corresponding to an intelligence: science (naturalistic), spatial (visual-spatial), multiplayer (group-interpersonal), logic (logical-mathematical), literacy (verbal-linguistic), emotions (emotional-intrapersonal), and arts (artistic). There is one additional world named after the user, which consists on a virtual village where the child interacts with characters to improve her wealth.
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