Critical Thinking and Artificial Intelligence
Grappling with ChatGPT in the Undergraduate Music Theory Classroom
DOI:
https://doi.org/10.15763/issn.2994-7073.2026.39.17-38Keywords:
artificial intelligence, LLMs, Large Language Models, music theoryAbstract
This article outlines the details of a critical thinking and Artificial Intelligence (AI) curriculum unit to give instructors one suggestion for how they might productively include the use of AI in their music theory classrooms. I share the different lessons and the assignment that I provided for my students, followed by a report of student responses and my assessment strategies. I conclude this article by encouraging music theory instructors to bring discussions of AI into the classroom in order to promote more meaningful learning outcomes—ones that extend beyond simply teaching students that ChatGPT and other Large Language Models (LLMs) are inappropriate to use. This AI unit encourages undergraduate music theory students to more thoroughly understand and experience the impacts of LLMs on critical-thinking skills.
Downloads
References
Attas, Robin. 2016. “Teaching What We Do and How We Do It: Using a Miniconference Assignment to Dig Deep into Musical Analysis.” Journal of Music Theor y Pedagogy 30. DOI: https://doi.org/10.71156/2994-7073.1182
Du, X., Du, M., Zhou, Z. et al. 2025. “Facilitator or Hindrance? The Impact of AI on University Students’ Higher-Order Thinking Skills in Complex Problem Solving. International Journal of Education Technology in Higher Education 22, no. 39. https://doi.org/10.1186/s41239-025-00534-0. DOI: https://doi.org/10.1186/s41239-025-00534-0
Ferenc, Anna. 2016. “Promoting Metacognitive Reflection in Music Theory Instruction.” Journal of Music Theory Pedagogy 30, no. 2. https://doi.org/10.71156/2994-7073.1183. DOI: https://doi.org/10.71156/2994-7073.1183
Gerlich, Michael. 2025. “AI Tools in Society: Impacts on Cognitive Offloading and the Future of Critical Thinking.” Societies 15, no. 1: 6. https://doi.org/10.3390/soc15010006. DOI: https://doi.org/10.3390/soc15010006
Henshaw, Florencia. 2023. “Catch My Errors If You Can: The Relative Value of Peer Editing in the Language Classroom.” Northeast Conference on the Teaching of Foreign Languages, no. 90:31–41.
Irish, Andrea L., Michele W. Gazica, and Vincent Becerra. 2025. “A Qualitative Descriptive Analysis on Generative Artificial Intelligence: Bridging the Gap in Pedagogy to Prepare Students for the Workplace.” Discover Education 4, no. 48. https://doi.org/10.1007/s44217-025-00435-4. DOI: https://doi.org/10.1007/s44217-025-00435-4
Kshirsagar, Pravin R., D. B. V. Jagannadham, Hamed Alqahtani, et al. 2022. “Human Intelligence Analysis through Perception of AI in Teaching and Learning.” Computational Intelligence and Neuroscience 2022, no. 1. https://doi.org/10.1155/2022/9160727. DOI: https://doi.org/10.1155/2022/9160727
Martin, Nathan. 2008. “The Tristan Chord Resolved.” Intersections: Canadian Journal of Music 28, no. 2. DOI: https://doi.org/10.7202/029953ar
McGee, Deron L. 1993. “The Power of Prose: Writing in the Undergraduate Music Theory Curriculum.” Journal of Music Theory Pedagogy 7. DOI: https://doi.org/10.71156/2994-7073.1056
Miserandino, Marianne. 2025. “Authentic and Creative Assessment in a World with AI.” Teaching of Psychology 52, no. 3: 267–72. https://doi.org./10.1177/00986283241260370. DOI: https://doi.org/10.1177/00986283241260370
Ripley, Angela. 2020. “Post-Tonal Postcards: Communicating Analysis and Reflection through Prose Writing.” Journal of Music Theory Pedagogy 34. DOI: https://doi.org/10.71156/2994-7073.1214
Rogers, Lynne. 2017. “Asking Good Questions: A Way into Analysis and the Analytical Essay.” Journal of Music Theory Pedagogy 31. DOI: https://doi.org/10.71156/2994-7073.1242
Shahzad, Muhammad Farrukh, Shuo Xu, and Hira Zahid. 2025. “Exploring the Impact of Generative AI-Based Technologies on Learning Performance through Self-Efficacy, Fairness & Ethics, Creativity, and Trust in Higher Education.” Education and Information Technologies 30, no. 3: 3691–3716. https://doi.org/10.1007/s10639-024-12949-9. DOI: https://doi.org/10.1007/s10639-024-12949-9
Sullivan, Miriam, Andrew Kelly, and Paul McLaughlan. 2023. “ChatGPT in Higher Education: Considerations for Academic Integrity and Student Learning.” Journal of Applied Learning & Teaching 6, no. 1. https://doi.org/10.37074/jalt.2023.6.1.17. DOI: https://doi.org/10.37074/jalt.2023.6.1.17
Walter, Yoshija. 2024. “Embracing the Future of Artificial Intelligence in the Classroom: The Relevance of AI Literacy, Prompt Engineering, and Critical Thinking in Modern Education.” International Journal of Educational Technology in Higher Education 21, no. 15. https://doi.org/10.1186/s41239-024-00448-3. DOI: https://doi.org/10.1186/s41239-024-00448-3
Wang, Shuyue, and Pan Jin. 2023. “A Brief Summary of Prompting in Using GPT Models.” Qeios. https://doi.org/10.32388/IMZI2Q. DOI: https://doi.org/10.32388/IMZI2Q
Winograd, Peter, and Peter Johnston. 1982. “Comprehension Monitoring and the Error Detection Paradigm.” Journal of Reading Behavior 14, no. 1: 61–76. https://doi.org/10.1080/10862968209547435. DOI: https://doi.org/10.1080/10862968209547435
Viet, Nguyen Khoa. 2025. “The Use of Generative AI Tools in Higher Education: Ethical and Pedagogical Principles.” Journal of Academic Ethics. https://doi.org/10.1007/s10805-025-09607-1. DOI: https://doi.org/10.1007/s10805-025-09607-1
Zamora, Ángela, Suárez, José Manuel, and Diego and Ar dura. 2018. “Error Detection and Self-Assessment as Mechanisms to Promote Self-Regulation of Learning among Secondary Education Students.” The Journal of Educational Research 111, no. 2: 175–85. https://doi.org/10.1080/00220671.2016.1225657. DOI: https://doi.org/10.1080/00220671.2016.1225657
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Hannah Benoit (Author)

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.