Playmeans: Inclusive and Engaging Data Science through Music

Abstract

According to decades of research in educational psychology, learning is a social process that is enhanced when it happens in contexts that are familiar and relevant. But because of the skyrocketing popularity of data science, today we often work with students coming from an abundance of academic concentrations, professional, and personal backgrounds. How can our teaching account for the existing multiplicity of interests and be inclusive of diverse cultural, socioeconomic, and professional backgrounds? Music is a convenient medium that can engage and include. Enter Playmeans, a novel web application (“app”) that enables students to perform unsupervised learning while exploring music. The flexible user interface lets a student select their favorite artist and acquire, in real time, the corresponding discography in a matter of seconds. The student then interacts with the acquired data by means of visualizing, clustering, and, most importantly, listening to music—all of which are happening within the novel Playmeans app. Supplementary materials for this article are available online.

Keywords:

• Diversity
• Fun
• Machine learning
• Spotify
• Statistics
• Web application

Supplementary Materials

The supplementary materials for this article consist of the instructions on how to obtain login credentials from Spotify and a version of an assignment on Playmeans.

Acknowledgments

The author would like to thank the editor, the associate editor, and the two anonymous referees for the various comments during the review of the article. Those suggestions led to a noticeable improvement of the manuscript.