NSF Award
1448915
This STTR Phase I project develops automated instruction for the music education market, replacing human labor with music analysis algorithms, and paper course materials with digital multimedia documents. Despite the positive effects of art education on achievement, many arts programs are being cut or underfunded; as a result these students are at higher risk of poorer grades and not completing their college degrees. Learning music requires extensive practice and individualized guidance, as taught in private lessons for hundreds of years. The proposed solution brings a unique and innovative software system to the marketplace that will automate and reinforce substantial parts of music theory instruction. Early results indicate that this technology can improve learning thereby reducing the need for remediation at higher grade levels and helping maintain the benefits of arts education in US schools even in the face of budgetary pressures. Numerous studies have demonstrated that increased emphasis on education in the arts stimulates intellectual capacity and creates wider benefits such as facility in STEM (Science, Technology, Engineering, and Mathematics) and interpersonal skills. This is a market of millions of students with extensions into larger markets, such as amateur musicians throughout the world.<br/><br/><br/>The key innovation of the software lies in its proprietary music analysis algorithms that enable substantial amounts of music theory instruction to be automated, including close to real-time correction, feedback and grading of complex, secondary and post-secondary exercises in tonal music analysis and composition. By using the software in place of paper instruction materials, a music student can practice composition and analysis as much as needed to master topics, receiving instantaneous feedback and guidance from the digital teacher. For music instructors, the technology completely removes the need to grade papers, reducing what now takes them hours of human labor per week to seconds at the push of a button. The software implements a multimedia document model that integrates all the common types of media used in music theory pedagogy: music notation (with or without automatic analysis), MIDI (Musical Instrument Digital Interface), text editing, images, vector graphics, video and audio playback. Early results indicate that this technology improves learning, thereby reducing the need for remediation at higher grade levels and helping maintain the benefits of arts education in US schools even in the face of budgetary pressures.
