I spent part of this summer redesigning ENGL 105 (Composition and Rhetoric), a first-year writing course I’ve taught in various forms over twenty years. One of my most useful collaborators was CourseTuner, a custom GPT developed by CSUCI’s Teaching & Learning Innovations (TLi) team.

I provided CourseTuner with learning outcomes, assignments, and pieces of my course plan and asked it to look for places where they didn’t quite line up. It caught an outcome that a section of the course claimed to address even though the assignment never actually asked students to practice it. It helped me see places where instructions made sense to me largely because I’d been looking at them for years. It also suggested connections among readings, reflections, and activities that I could then decide whether I wanted to make more explicit. I didn’t always take its suggestions, any more than I would take every suggestion from a colleague, but I always learned something from considering them.

CourseTuner isn’t there to make the pedagogical decisions. It’s designed to help faculty examine the decisions we’re already making: what we want students to learn, how we’re asking them to practice it, and whether our assignments actually give them an opportunity to demonstrate it.

A familiar partner with a new kind of tool

I think CourseTuner is especially worth a look for faculty who don’t necessarily see themselves as AI users. Maybe you’ve inherited course outcomes that don’t seem to match an assignment, or you’re redesigning a course you haven’t taught for several semesters. Maybe an assignment works, but you can’t quite articulate why. Or maybe you’ve taught the course so many times that you need another reader to help you see what has become invisible through familiarity.

Those are course design questions, not AI questions.

And CourseTuner comes from a place faculty already know. TLi has long helped CSUCI faculty navigate changes in teaching and technology, not by treating technology as the goal, but by helping us figure out when and how a tool can support the learning we actually care about. CourseTuner feels like a natural continuation of that work.

Try it with something small

If you’re curious, don’t start by uploading an entire course and asking for a redesign. Bring CourseTuner one thing you’re already thinking about: an assignment, a set of learning outcomes, or a module that isn’t quite working. Ask what it notices and why. Then decide what, if anything, you want to modify.

That’s what I found most useful: another way to examine work I thought I already knew very well.

If you’re not sure AI has a place in your teaching, that might be a good place to begin. Learn more about CourseTuner and the learning design research behind it in Ana M. Peñaranda’s From Outcomes to Effective Learning with CourseTuner.

CourseTuner is available to CSUCI Faculty through their ChatGPT Edu accounts.

Stacey Stanfield Anderson is a Professor of English and Composition Director at Cal State Channel Islands