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ERIC Number: EJ1396132
Record Type: Journal
Publication Date: 2023
Pages: 11
Abstractor: As Provided
ISBN: N/A
ISSN: N/A
EISSN: EISSN-2693-9169
"Playmeans": Inclusive and Engaging Data Science through Music
Khachatryan, Davit
Journal of Statistics and Data Science Education, v31 n2 p151-161 2023
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.
Taylor & Francis. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A