SBIR Phase I: Mnemonic Optimization of Music and Songs

This SBIR Phase 1 project aims to produce songs that are optimized for learning and memory. While music has long been recognized for its mnemonic properties (e.g., the ABC song, the 50 states song, etc.) and is widely used as a memory aid in the context of early childhood learning, music-based educational products for the broader K-12 market are rare. Music is unique in its ability to engage learners, make learning enjoyable, and transfer information into memory more readily. Yet, music is predominantly experienced as an entertainment medium. The goal of this research is to position music as a credible pedagogical tool by scientifically crafting songs that support the learning of critical academic skills and concepts - offering today's learners a relevant, effective and efficient medium for boosting learning outcomes. The technical innovation proposed is a scientific framework for mnemonically optimized music and songs. This research features two distinctive innovations: 1) isolation and identification of the mnemonic drivers of songs, and 2) operationalization of these drivers as parameters for the creation of songs optimized for learning. Methods employed include computational and statistical modeling, expert input, and behavioral measurement. The potential impact of this research addresses a pressing academic need -- how to teach students using pedagogy that is relevant, engaging and scientifically sound. If proven feasible, this research will fuel creation of a unique musical form designed specifically to enhance memory and learning, with application to K-12 learning and beyond. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.