Reimagining Film Studies in Canvas with Personalization, Accessibility, and Creative Choice

This article began as part of my work in the Canvas Certified Educator (CCE) program—but the journey quickly became something more. Through the process of revising and reflecting, I realized that my original film studies module could be more than an assignment. It could become a real model for how AI can support inclusive, personalized learning in humanities education.

I first designed this module in CCE Core 1 as a unit on The 400 Blows by François Truffaut, part of the French New Wave. The goal was to help students analyze film techniques—like mise-en-scène, sound, and editing—while exploring their own interpretations of a chosen scene.

But for Core 3, I reworked it to align more closely with Universal Design for Learning (UDL) principles and to better support student agency, accessibility, and creativity. I also integrated feedback from a peer review process, which helped me strengthen reflection opportunities and add optional AI-powered tools in a more thoughtful way.

Key Design Features in Canvas

Here’s how I redesigned the module using Canvas tools:

• Structured Modules to guide students from context to creation
• Multimodal Materials like captioned videos, accessible readings, and embedded YouTube explainers
• A Scaffolded Scene Analysis Assignment that allows students to choose their format: essay, storyboard, voice-over commentary, or AI-assisted visual analysis
• Peer Review with clear prompts focused on constructive feedback
• Rubrics aligned with interpretive, technical, and creative learning outcomes
• UDOIT Accessibility Checks to ensure inclusive access at every step
• Optional AI Support via Shotdeck (a database of high-quality film stills) to help students identify stylistic patterns and deepen their visual literacy

The Role of AI: Optional, Not Essential

While the title of the lesson is “Scene Analysis with AI Support,” I made it clear that AI tools like Shotdeck are optional. The core learning objectives can be met through traditional analysis and personal reflection. That said, giving students the opportunity to use AI to enhance their analysis opens the door for more creative, comparative, and inquiry-based learning.

The key insight here: AI doesn’t need to be central to every activity—but when thoughtfully introduced, it can expand how students explore and express their understanding.

What I Learned—and What’s Next

This project pushed me to think deeply about how to blend pedagogical intention with emerging tools. More than just a tech integration, this was about designing a learning experience that is:

• Personalized – letting students choose how to express insight
• Inclusive – removing barriers through accessibility best practices
• Reflective – inviting learners to connect analysis to their creative thinking
• Ethical – framing AI not as a shortcut, but as a partner in visual literacy

Next steps? I plan to implement this lesson in future courses, gather authentic student feedback, and continue exploring ways to support film analysis through ethical, AI-assisted approaches.

📽️ Watch the Presentation

Want a quick walkthrough of the module design and my reflections? Watch the 5-minute YouTube video:

I’m always thinking about how AI might support more inclusive, creative learning—especially in the humanities—and this was one step in that direction.

Here’s to crafting learning experiences that are curious, creative, and responsibly AI-powered.