As technology continues to evolve and influence our lives, the demand for careers in science, technology, engineering, and mathematics (STEM) has only grown. However, challenging content and lack of valuable experience often prevents students from finding a sense of belonging in these fields, discouraging many from considering futures in STEM. Thus, alternative learning techniques that both introduce foundational concepts and engage students are essential to addressing this need. A common difficulty for many students is understanding how protein sequence and structure contribute to protein function, and how errors in proteins impact the overall function of a cell. To present these foundational concepts to introductory students, our team has developed a virtual authentic-learning tool that utilizes data sonification in which each amino acid in a primary protein sequence is assigned a musical note and rhythmic value based on its hydropathy. This software allows harmonious music segments to be composed from primary sequences of functional proteins. Moreover, this software may also be used to model disease-associated point mutations by creating dissonance in music segments, allowing the user to audibly identify mutations and understand how errors impact cellular symphony. Our hypothesis is that this data sonification learning module will both increase student understanding of the molecular basis of disease and improve student attitudes toward STEM. Our preliminary results show this activity changes student attitudes following presentations to middle school and high school student groups supporting this hypothesis and future expansion of the models.