Adam Grise

Appointed Fall 2019

Adam Grisé is the Systems and Data Analyst for the University of Maryland School of Music. His work in this role encompasses systems architecture, data collection, curation, analysis and School of Music demography.

Grisé earned his Ph.D. in Music Education from the University of Maryland in 2019. His research expertise centers on issues of equity, access and multiculturalism in secondary and postsecondary music education. Grisé’s dissertation examining persistence and attrition factors among aspiring musicians, educators and music educators was honored with the 2019 Outstanding Dissertation Award from the Council of Research in Music Education.

Grisé has been published in the Journal of Research in Music Education and has presented original research at the National Association for Music Education Music Research and Teacher Education National Conference, the College Music Society National Conference, American Educational Research Association Annual Meeting, the Society for Music Teacher Education Symposium, the Desert Skies Symposium on Music Education Research, the Big Ten Academic Alliance Music Education Conference and the Maryland Music Educators Association Conference. At the 2018 American Educational Research Association annual meeting, Grisé’s work showing demographic imbalances in the pathway to professional musicianship won the Outstanding Graduate Paper Award in Music Education. Grisé has worked as a freelance research consultant for the National Association for Music Education providing context and analytic insights into the 2016 NAEP Arts data.

Grisé is co-author of Introduction to Steel Band, a series of method and textbooks for K-12 classroom steel band instruction. He served for ten years as the musical director for a youth arts program, directing a nationally recognized youth steel orchestra. Grisé’s compositions and arrangements for steel ensemble have been featured by steel bands across the country and around the world. He remains active in the Caribbean music scene in multiple performance capacities.