LINEWAVES
LINEWAVES is an inclusive resource for teaching music using coding and computational methods. All materials are organized into modules that can easily be combined, customized, and integrated into existing curricula. Each module links musical concepts and coding lessons, with an emphasis on diverse examples by composers including Scott Joplin, Ruth Crawford Seeger, and Melanie Bolis.
View the latest modules here:
- PitchesThis module introduces the concept of musical pitches. In the western art… Read more: Pitches
- Installing Python LibrariesIn this module, we will explore how to install libraries or packages… Read more: Installing Python Libraries
- Classifying Genre Using Machine Learning, Part IIn this module, we will use machine learning to classify songs by… Read more: Classifying Genre Using Machine Learning, Part I
Modules reflect a range of platforms and methodologies, and are designed for diverse applications and skill levels. LINEWAVES modules can be used in a variety of contexts—from the undergraduate music theory curriculum to courses in the humanities and computer science. Check out our Guides to see how you can incorporate modules into your teaching.
Guiding Principles
LINEWAVES is a platform for digital pedagogy. Digital pedagogy is more than simply using technology in the classroom. It is a novel approach to teaching and learning that integrates digital technology in meaningful ways. LINEWAVES uses technology to increase inclusion, student-centered learning, and accessibility.
Inclusion
LINEWAVES modules promote inclusivity by drawing examples from a range of musical traditions, and by featuring the music of composers from underrepresented backgrounds. Every module contains at least one example by a composer from an underrepresented background. Composers featured in recent modules include: Marion Bauer, Amy Beach, Melanie Bolis, Duke Ellington, Francisca “Chiquinha” Gonzaga, J Rosamond Johnson, Scott Joplin, and Ruth Crawford Seeger.
Student-Centered Learning
LINEWAVES centers students’ learning by providing them with the tools to make and evaluate music theoretical claims independently. Critical inquiry using computer-based methods is a way to address those hard-to-answer questions that inevitably arise in the music theory classroom–from the concrete to the vaguely defined. Where have I heard this melody before? What is it that makes music sound cheerful? Mournful? Spooky? Majestic? These kinds of questions are consistently engaging for students, but that often fall by the wayside in traditional textbooks.
LINEWAVES also models independent inquiry for students’ future research. It illustrates how theoretical knowledge is entangled with the methods we use, and how it differs across different time periods and traditions. It also reframes the much-maligned “rules” of music theory as patterns and norms that can be evaluated empirically.
Accessibility
One of the biggest obstacles to integrating digital methods in the classroom is connecting the content in dense programming tutorials with meaningful musical activities. LINEWAVES bridges that gap, promoting mastery of musical concepts and code literacy hand in hand. It also utilizes and centralizes open educational resources, linking to supplementary online content, including other music theory resources (such as Open Music Theory) and databases devoted to composers from underrepresented backgrounds.
Some Final Thoughts
The methods found in these modules can be generalized and applied outside of the domain of music. Yet we must be careful not to overestimate the computer’s capacity and authority. Questions and claims must be tempered by critical reflection, and the researcher must acknowledge limitations and sources of subjectivity.
Other challenges abound, even though many are common to interdisciplinary work throughout the academy. For example, differences in disciplinary focus and methodology can often be reconciled through collaboration, even if the practice of conducting research with others is unfamiliar for many humanists.
Similarly, despite enormous advances in the field of music information retrieval (MIR) in recent years, the most developed and widely-used software focuses on the symbolic (i.e. notation-based) representation of music. This has serious implications not only for scholars’ access to particular canons of music, but also for what kinds of topics can be studied.
Despite these challenges—and to a large extent, because of them—there remains much good work to be done. In a recent interview in the journal Empirical Musicology, the music scholar David Huron—who has spent decades conducting computer-based musicological research and developing his own software—offered three pieces of advice for young scholars interested in doing computational research in music today:
- First, make a long list of questions that interest you. Good research is motivated by questions.
- Second, let your questions guide your research activities. Don’t be afraid to go wherever a question takes you… Disciplines are defined by the questions they ask, not by the methods they use.
- A final piece of advice is to beware of the siren call of computers… The tools of course are important. If you want to do this sort of work, then learning about computers and statistics is essential. But don’t lose sight of your goals.
Acknowledgements
LINEWAVES was created by Drake Andersen, Ph.D., Visiting Assistant Professor in the Department of Music at Vassar College. He can be reached at: drake [at] linewaves [dot] org
The following individuals have also contributed to LINEWAVES:
Daniel Fox
Tom Johnson
Emma Skinner