CC Fest’s first panel asked how to teach creativity through creative coding when AI can make almost anything. Amy B. Woodman, senior program manager at the Processing Foundation and a former classroom teacher, brought together three colleagues: Daniel Schneider, a former Tucson high school math and computer science teacher who has written middle school and AI curricula for Code.org and now Hello World CS; David DeLiema, a learning scientist at the University of Minnesota who studies failure and play in learning; and Adrienne Gifford, in her 21st year teaching middle school computing and STEM and a collaborator with the University of Washington’s Center for Learning, Computing, and Imagination. They had written questions for each other in advance without sharing answers, so the conversation unfolded like a podcast.
Woodman opened with her worry: making is how we learn to think, discover our tastes and preferences, learn to judge, and learn to express ourselves. If AI makes things for us, she asked, what happens to that? Schneider said that rooms where standards and policies are written now focus on technical skills, AI careers and even staying ahead of other countries, and that this narrative leaves out students’ own desire to create. He argued that if self-expression is the goal, AI complicates the path but does not change the goal, and offered a counterpoint: his 70-year-old father used AI to finally build the quirky website no consultant understood.
DeLiema described debugging as full of open-ended, creative choices: what counts as wrong, what to blame, how to intervene, and what you want to learn from the moment. “There’s humor, there’s joy, there’s empathy. It’s human interaction. It’s human connection,” he said of the conversations around broken code. He described students who sang to each other when something failed and worried about handing that social process to a tool. Pointing to Courtney Cazden’s research on prompts, he noted that a hint only works if you already have the knowledge it cues, which is why learners have to own their learning process.
Gifford reported that her seventh graders made identity-based pixel art in Python with an optional AI agent, and almost none chose to use it. In reflections, they said they wanted their work to be authentic, that their ideas were better than AI’s, that they preferred help from teachers and peers, and that they had concerns about artists’ work and water use. Twelve-year-olds, she said, are asking the same questions as artists and researchers, and students should be able to question, change or reject the tools. What they want protected is agency over their creative process, not speed. She suggested next year’s panel feature students.
Woodman described the Art + Code curriculum for art teachers, guided by Seymour Papert’s idea that educators create conditions for invention rather than provide ready-made knowledge. Tutorials such as Build a World and a shared Drawing Tool give learners challenges just out of reach, results that are clearly their own, and communal moments where they use each other’s work. She also cited the balance of order and chaos in Aleksandra Jovanić’s existing Take a Spline for a Walk tutorial, connecting constraints in a drawing system to the judgment a maker develops. Saber Khan closed by urging teachers to make their classrooms places where skeptical voices are heard.
Three takeaways
- Ask the students. Gifford’s seventh graders mostly declined an optional AI helper, citing authenticity, their own ideas, human help and ethics (00:14:58–00:18:28).
- Debugging is creative and social. Noticing, blaming and fixing are open-ended choices, and the talk around them builds connection (00:10:00–00:13:50).
- Design challenges just out of reach. Papert’s “conditions for invention” guided tutorials where every learner’s result is different and shared (00:19:24–00:24:52).
Try it
Editorial suggestion, adapted from Gifford’s classroom: on your next creative coding project, make an AI helper optional and ask students to write a short reflection on whether and why they used it. Share what they say with them, and with colleagues.
Watch and explore
Replay: Watch on YouTube
- Art + Code curriculum class on OpenProcessing (link shared in chat by Saber Khan)
- Panelist bios are on the CC Fest website.
From the original program
Published before the event
Teaching Creativity Today
When AI can write the code for us, what parts of creative coding are worth preserving? Creative coding has never been only about producing working code; its value is also in experimenting, getting stuck, debugging, making unexpected discoveries, and developing your own way of making. This panel explores what learners gain through that process, what may be lost when AI removes friction, and how we might design educational experiences that preserve the most valuable parts of learning.
About the presenters
Amy B. Woodman
she/they
Amy Woodman is a Senior Program Manager at the Processing Foundation, where she supports open-source contributors, creative coding education, and programs that expand access to technology as a medium for expression. An educator, curriculum designer, and ceramic artist, she is especially interested in how creative coding can build agency and creative confidence and how we can protect the messy, exploratory process of making and learning in an AI-rich world.
Daniel Schneider
he/him
Dan taught high school math and computer science for several years, and now writes curriculum for Code.org and Hello World CS. He learned Processing in college, taught p5js in summer camps (where you can be really creative), wrote lessons for Code.org's Game Lab built on top of p5 play, and sometimes tinkers with ml5js.
David DeLiema
he/him
David DeLiema is an educational researcher who studies the conversations, designs, and processes that shape how learning emerges from moments of impasse. In research-practice partnerships that foreground the knowledge and voices of teachers, students, and parents, his research examines cognitive and psychological processes in the context of social interaction, technology-rich settings, play-based activities, and embodied movement. In studies of children pretend-playing as bees trying to find nectar, middle schoolers debugging broken code, and youth working on challenging puzzle-based video games, his work provokes reflection on the open-ended, power-laden, and everyday nature of turning impasses into learning.
Adrienne Gifford
she/her
Adrienne Gifford (she/her) is a public school computing and STEM teacher, curriculum designer, and researcher in the Seattle area. She loves collaborating with students to explore creative, identity-inclusive, and culturally responsive approaches to teaching and learning about computing. Her recent work has focused on creative coding with tools like p5.js and Wordplay, both with students and in collaboration with other educators and researchers.