STEM Mini-Lesson Plan: Creative AI Generation

Topic: Algorithmic Creativity: Using AI for Music and Video Synthesis (STEAM Integration) Target Grade Level:Middle School / Early High School (Adaptable) Time Allotment: 45 – 60 minutes

1. Learning Goals & Objectives (S-T-E-A-M)

Domain	Measurable Objectives (Students Will Be Able To…)
Science/Tech (S/T)	Define Artificial Intelligence (AI) and explain how it learns patterns from existing data (training sets).
Engineering (E)	Use parameters (input variables) to engineer a desired output from an AI tool (e.g., selecting genre, tempo, visual style).
Math/Art (M/A)	Synthesize two different AI-generated assets (music and video/image) into a coherent 30-second “AI Art Film.”

2. Materials & Tools

• Hardware: Computers or tablets with internet access.
• Software (Free/Accessible Examples):
  • AI Music Generator: Simple web-based composer (e.g., examples from Google’s Magenta project, or other simple music/beat generators).
  • AI Visual Generator: Simple text-to-image generator (emphasizing prompt engineering) or a presentation tool (like Google Slides/Canva) to combine generated images.
  • Video Editor: Simple online video combiner (if needed, otherwise students use presentation tools to sync).
• Visual Aids: Short video example of an AI-generated piece.

3. Lesson Procedure (The Engineering Process)

Time	Phase	Focus & Key Questions	Teacher/Student Activity
10 min	Engage: What is Creative AI?	Q: How does a computer know what music sounds like? Focus: Explain the concept of Machine Learning and Training Data. AI isn’t “thinking,” it’s recognizing patterns and creating something new based on those patterns.	Teacher shows a quick video demo of an AI-generated piece. Discussion on the difference between human and algorithmic creativity.
15 min	Experiment: Music Engineering	Challenge: Engineer a piece of music that sounds “Happy and Fast.” Focus: Parameter Input is crucial (the “Engineering” step). Students must select tempo, key, and instrumentation.	Students access the chosen AI music tool. They experiment with changing one parameter at a time and noting how the output changes. Goal: Generate a 30-second piece.
15 min	Experiment: Visual Engineering	Challenge: Generate a visual background that matches the mood of their music. Focus: Prompt Engineering. Discuss how specific words (e.g., “Vibrant, abstract, impressionist, high-contrast”) affect the visual output.	Students use a text-to-image generator (or select appropriate pre-generated images). They must iterate on their text prompt until the visual matches the mood of their music. Goal: Generate 3-5 images.
15 min	Synthesize: The Final Product (M/A)	Challenge: Combine the generated music and visuals. Focus: Synchronization and Coherence. Does the music match the visual pacing? (The “Art” step).	Students use a presentation tool (Slides/Canva) to sequence their images while playing their music, creating a 30-second “AI Art Film.”
5 min	Evaluate & Reflect	Q: What was the easiest/hardest parameter to control? What role did you play in the final creation?	Quick share-out of the “films.” Focus on the students’ choices (parameters) rather than the final aesthetic quality.

4. Assessment

Success Criteria:

1. Technical Proficiency (E): The student successfully uses the AI tool by manipulating at least two different input parameters (e.g., genre + tempo) to generate the music/video.
2. Synthesis (M/A): The final 30-second presentation/video has a clear, intentional connection between the music’s mood and the visual’s content.
3. Conceptual Understanding (T/S): The student can articulate one way the AI learned to generate the content (e.g., “It learned from thousands of pop songs/nature photos”).