The focus of our class this week was how to teach in an era where AI is widely available. Plagiarism and unethical use of AI is a common issue, and it can be difficult to detect and prove when students break these rules. AI-detection softwares are notoriously untrustworthy and create a large percentage of false positives, which negates the purpose and can potentially negatively impact students who did nothing wrong. Some of the solutions to this include allowing AI for beneficial purposes, making clear boundaries and guidelines, and trying to avoid the circumstances that cause students to want to cheat in the first place.

As a music teacher, I will primarily be teaching performance-focused classes, so plagiarism or unethical use of AI by students is somewhat irrelevant as there would be few instances to even attempt it. With that said, I am looking for ways to integrate other musical traditions and knowledge into the band classroom, some of which can not necessarily be taught through the medium of traditional band repertoire. I would be interested in finding ways to implement inquiry or research projects on a range of topics in my music classes, and those are where AI can pose a big issue. For inquiry-based learning, consistent check-ins and work blocks where I can actively see students working would be the main strategies I use to prevent these issues. I am also curious about the idea of a one-on-one interview with students as part of their project – by asking questions related to the subject that are not directly quoted in the (potentially AI-generated) essay or project, it should be easy to determine whether or not the student really spent time to research and understand the topic.