Jiayi Zeng(Cathy) & Weiyan Huang
1. Guiding Question / Focus Area
Our collaborative inquiry explores the following guiding question:
How can AI image-generation tools be used as creative supports in visual art education without replacing students’ original ideas, voices, and creative decision-making?
This inquiry grows out of our shared interests and complementary backgrounds. Weiyan is a first-year student in Instructional Technology and Media with experience in illustration and visual media, and she is interested in how AI conversations and tools can assist creative practice. Cathy is a second-year graduate student in Art Education at Teachers College with a background in fine arts, focusing on visual art processes and the role of emerging technologies in art education.
This topic is meaningful to our team because both of us encounter increasing pressure to integrate AI tools into creative and educational contexts, while also noticing concerns around originality, overreliance on AI outputs, and loss of student agency. Our inquiry responds to a real need among art educators: understanding how to use AI thoughtfully as an inspiration and exploration tool rather than a substitute for creativity.
2. Goals / Objectives
The primary goal of this project is to examine how AI image-generation tools (AICG) can be integrated into visual art education in ways that support creativity while preserving students’ creative autonomy.
For our team, this inquiry aims to:
Build practical and critical understanding of AI image-generation tools
Develop strategies for using AI as an inspiration generator rather than a final image-maker
Strengthen our AI literacy through hands-on experimentation and reflection
For our intended audience (art educators and students), our goals are to:
Demonstrate concrete classroom-relevant uses of AI tools in visual art learning
Offer guidance on prompt design, experimentation, and reflective use of AI
Encourage thoughtful engagement with AI that supports student agency and creative thinking
3. Plan
To address our guiding question, we will conduct a series of structured experiments aligned with the course timeline.
Step 1: Brainstorming and AI Feedback
We will collaboratively brainstorm visual art themes, classroom scenarios, and creative prompts. These ideas will be input into AI tools such as ChatGPT and Claude to receive feedback, variations, and conceptual extensions.
Step 2: Research and Context Building
We will research AI literacy frameworks, existing practices in art education, and challenges related to AI image generators, focusing on creativity, authorship, and ethics.
Step 3: AI Experimentation and Comparison
Using tools such as Stable Diffusion, Canva, Gemini, and 豆包, we will conduct parallel experiments:
One set using carefully refined prompts
One set using more direct or minimal prompts
We will compare outputs to analyze how prompt design affects creative control and alignment with original ideas.
Step 4: Website Development
We will design an educational website using a grid system to clearly document our process, experiments, comparisons, and reflections.
Step 5: Reflection and Revision
We will reflect on the effectiveness and limitations of AI-assisted creativity and revise our findings into educator-facing insights.
Timeline (aligned with course schedule):
Week 1–2: Brainstorming, AI feedback, and research
Week 3: AI experimentation and comparison + Website development and revision
4. Deliverables / Outcomes
A practice-based educational website documenting the inquiry
Visual examples comparing different AI-generated outputs
Written reflections on AI, creativity, and student agency
A short guideline for art educators on designing AI-supported creative projects