Playmeans: Inclusive and Engaging Data Science through Music
AbstractAccording 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 acad...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2023-05-01
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| Series: | Journal of Statistics and Data Science Education |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/26939169.2022.2138801 |
| _version_ | 1797773354144366592 |
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| author | Davit Khachatryan |
| author_facet | Davit Khachatryan |
| author_sort | Davit Khachatryan |
| collection | DOAJ |
| description | AbstractAccording 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. |
| first_indexed | 2024-03-12T22:05:16Z |
| format | Article |
| id | doaj.art-965041b75aea4465a1f35c12fbbc9101 |
| institution | Directory Open Access Journal |
| issn | 2693-9169 |
| language | English |
| last_indexed | 2024-03-12T22:05:16Z |
| publishDate | 2023-05-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Journal of Statistics and Data Science Education |
| spelling | doaj.art-965041b75aea4465a1f35c12fbbc91012023-07-24T16:50:04ZengTaylor & Francis GroupJournal of Statistics and Data Science Education2693-91692023-05-0131215116110.1080/26939169.2022.2138801Playmeans: Inclusive and Engaging Data Science through MusicDavit Khachatryan0Division of Mathematics, Analytics, Science, and Technology, Babson College, Babson Park, MAAbstractAccording 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.https://www.tandfonline.com/doi/10.1080/26939169.2022.2138801DiversityFunMachine learningSpotifyStatisticsWeb application |
| spellingShingle | Davit Khachatryan Playmeans: Inclusive and Engaging Data Science through Music Journal of Statistics and Data Science Education Diversity Fun Machine learning Spotify Statistics Web application |
| title | Playmeans: Inclusive and Engaging Data Science through Music |
| title_full | Playmeans: Inclusive and Engaging Data Science through Music |
| title_fullStr | Playmeans: Inclusive and Engaging Data Science through Music |
| title_full_unstemmed | Playmeans: Inclusive and Engaging Data Science through Music |
| title_short | Playmeans: Inclusive and Engaging Data Science through Music |
| title_sort | playmeans inclusive and engaging data science through music |
| topic | Diversity Fun Machine learning Spotify Statistics Web application |
| url | https://www.tandfonline.com/doi/10.1080/26939169.2022.2138801 |
| work_keys_str_mv | AT davitkhachatryan playmeansinclusiveandengagingdatasciencethroughmusic |