Cadence: Using AI to Support Music Theory Learning Beyond the Classroom
Quynh Nguyen, Hunter College
Bio
I am a concert pianist and music professor in the Music Department at Hunter College, where I teach piano instruction, music theory, chamber music, and music performance. My work combines artistic performance, pedagogy, and student-centered mentorship. As both performer and educator, I am committed to helping students develop musical literacy, technical skill, confidence, and a deeper understanding of music as a language of expression, discipline, and cultural connection.
Course Setting
I teach Music Theory 101 through the Hunter College Now program, which provides high school students with access to college-level coursework. The course introduces foundational concepts in music theory, including notation, rhythm, scales, intervals, chords, key signatures, and basic analysis. My students come with varied levels of musical background, so the course emphasizes clear explanations, guided practice, and applied learning.
Problem of Practice
In Music Theory 101, I notice that students begin the semester with very different levels of musical background. Some have years of training, while others are complete beginners. In class, I can explain concepts, answer questions, and respond to individual needs. However, outside of class, some students become confused while completing homework or reviewing course materials and are unsure how to find reliable help beyond the textbook. This may affect their confidence, curiosity, preparation, and willingness to participate in class discussions.I would like to provide an additional resource aligned with the course textbook that can encourage deeper engagement with music theory concepts by assisting students to review music theory concepts outside of class, ask clarification questions, scaffold understanding, and help students come to class better prepared with questions and ideas.
How might I use an AI-supported supplemental resource to increase the number of students who review music theory concepts outside of class, ask clarification questions, and participate in class discussions?
Strategy
The pedagogical strategy I implemented was the use of an AI-supported music theory tutoring tool aligned with course materials and the Straus Elements of Music textbook. The AI tutor was designed to provide students with low-pressure, accessible support outside of class by answering questions, explaining concepts step-by-step, and encouraging reflection rather than simply giving answers. I instructed students to use the tool when reviewing for exams, clarifying unfamiliar concepts, or preparing questions before class discussions.
The strategy was implemented as a supplemental resource rather than a replacement for instruction. In class, I continued modeling exercises, explaining notation, and guiding practice activities, while the AI tool extended opportunities for engagement beyond class hours. The rationale behind this strategy was to increase student curiosity, confidence, and independent learning, especially for students hesitant to ask questions publicly. Research on scaffolding and learner-centered instruction suggests students engage more deeply when they receive timely feedback, guided questioning, and opportunities for self-paced exploration. The strategy aimed to create a more interactive learning environment that encouraged preparation, reflection, and active participation in class discussions.
Documentation
Survey Responses on AI Tutor "Cadence"/ Music Theory Class
This shows examples of students’ questions and interactions with AI agent. Click through to see.
Figure #1: Survey Responses on AI Tutor "Cadence"/ Music Theory Class
Final Exam for Music Theory S2026
This is an example of a completed final exam. Click through to see.
Figure #2: Final Exam for Music Theory S2026
Measuring Impact
Measurements of Grade Percentages
Graph shows final grade for Spring 2026 is much stronger: more A grades, fewer NC/under-credit outcomes. Spring 2025 looks more polarized: many As, but also many NCs.
Figure #3: Measurements of Grade Percentages
Comparisons for S2025 VS S2026
Graph shows final grade for Spring 2026 is much stronger: more A grades, fewer NC/under-credit outcomes. Spring 2025 looks more polarized: many As, but also many NCs
Figure #4: Comparisons for S2025 VS S2026
Analysis
The strategy was highly effective in encouraging critical thinking, increasing student engagement, and improving students’ understanding of music theory concepts. Students appeared to engage more deeply with course materials through the AI tutor, Cadence, which provided additional support outside the classroom. The tool encouraged students to ask questions more freely, review concepts independently, and reflect on topics introduced during lectures. In many cases, students demonstrated stronger participation in class discussions and greater confidence when completing assignments and assessments. These outcomes suggest that the strategy addressed the Problem of Practice by improving both engagement and access to individualized support.
Student feedback on effectiveness, ethical AI use, and formative assessments also helped shape the configuration of the AI agent. The strategy enhanced learning by offering immediate feedback and allowing students to revisit difficult concepts at their own pace, which is especially valuable in a sequential subject like music theory.
However, important limitations remain. The AI tutor was most useful for suggesting, scaffolding, and prompting reflection, but it could not replace instructor guidance in applied skills such as rhythm practice, note reading, listening, and music writing. It also produced errors in clefs, staves, notation, and visual examples. Therefore, the AI tutor should be used as a supplemental support tool, not as an authoritative source for accurate music theory instruction.
Recommendation
In music theory, CN and EC professors should use AI tutoring strategies as supplemental learning supports to encourage deeper engagement. These tools are most effective for helping high school students review terminology, scaffold complex concepts, and reflect more deeply on course material outside of class. Instructors should use caution in skill-based disciplines such as music theory, where accurate notation, rhythmic practice, listening, and music writing are essential. Because AI-generated visuals and notation examples as of now still contain inaccuracies or misleading information, professors should frame the technology as a guided study aid rather than an authoritative source. This strategy works best when paired with instructor oversight, class discussion, and opportunities for students to verify and apply concepts collaboratively.
