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While there is a growing body of research that explores the integration of music and coding in learning environments, much of this work has either emphasized the technical aspects of computer language design or music as a motivational context within which to learn computer science concepts. In this paper, we report on a study in which five undergraduate students with experience in both music and coding completed two creative musical tasks: one using conventional instruments and tools and one using Python code in an online music + coding environment. Inspired by the work of Christopher Small (1998. Musicking: The Meanings of Performing and Listening. University Press of New England), we describe music + coding as a set of interlocking processes which we call computational musicking and explore how practices from both domains are reimagined in this new hybrid context. We introduce semiotic theories of translation and transcription to make sense of the computational musicking process and describe strategies that participants devised in their creative process.
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A Case Study of Middle Schoolers’ Use of Computational Thinking Concepts and Practices during Coded Music Composition
Researchers and practitioners have demonstrated various benefits of introducing computational thinking (CT) through music com- position coding. While researchers have studied the impacts on participant attitudes towards CT and their learning of CT concepts, more case studies are needed on both learning CT concepts as well as CT practices, i.e., the processes of constructing music coding projects. This paper presents a case study of middle schoolers in an informal learning environment focused on integrating music composition with coding in TunePad. Specifically, we collected and analyzed logs of coding events, final code products, and surveys to explore both CT concept use and CT practices exhibited by the par- ticipants as they completed open-ended music coding activities to create their own melodies with specific music and CT requirements and recommendations
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- Award ID(s):
- 2048793
- PAR ID:
- 10322529
- Date Published:
- Journal Name:
- 27th ACM Conference on Innovation and Technology in Computer Science Education
- Volume:
- 1
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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