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Case Registry • Public entry page
Case Type Case Report Status Completed

AAB-CASE-2025-LL-003

5-day mini AI summer camp (Grades 3–5; approx. ages 8–10) at an afterschool center in Diamond Bar, Southern California. The camp combined short educator-led AI concept lessons with hands-on Scratch projects (programming, data collection, pattern-based behavior, game creation, and introductory reinforcement learning concepts).

This page documents a real-world educational activity for registry purposes. It is descriptive (not a controlled study) and does not imply endorsement of any specific tool.
AgeElementary (8–10) SettingAfterschool center AI FunctionConceptual AI + Pattern behavior PedagogyProject-based learning Risk LevelLow Data SensitivityNone

Implementing Organization

1
Organization Type
Afterschool center
Location
Diamond Bar, Southern California, USA (suburban)
Primary Facilitator Role
Undergraduate and graduate CS students; technical educators

Learning Context

2
Setting Type
  • Informal learning
  • Afterschool center
  • In-school (K–12)
  • Private program
Session Format
Mini AI Summer Camp
Duration
5 days
Group Size
~10 students
Devices
Individual device
Constraints
  • No individual logins allowed
  • No personal data collection
  • Time-limited setup and teardown
  • Poor Wi-Fi signal

Learner Profile (Non-identifiable)

3
Age Range
Grades 3–5 (approx. ages 8–10)
Prior AI Exposure (Assumed)
No prior experience with generative AI tools assumed
Prior Programming Background (Assumed)
No prior programming background assumed

Educational Intent

4
Primary Learning Goals
  • Build foundational understanding of what AI is and what AI is not
  • Introduce how AI learns and creates using age-appropriate metaphors
  • Develop basic computational thinking through Scratch programming
  • Encourage creative expression through game and character design
Secondary Learning Goals
  • Understand data collection and patterns as inputs to AI systems
  • Explore human decision-making vs AI behavior
  • Practice iteration, testing, and refinement
  • Build confidence in presenting and explaining technical ideas
What This Was Not
  • Not a formal AI theory course
  • Not advanced machine learning instruction
  • Not focused on standardized performance metrics

AI Tool & Learning Materials

5
Tool & Platform Types
  • AI concept instructional slides (educator-led)
  • Scratch programming environment
Learning Materials Included
  • AI concept slides: What is AI / AI or Not AI; Natural vs Artificial intelligence; How AI learns; How AI creates
  • Scratch projects: basic programming, data collection, game creation, AI character generation, pattern generation, and introductory reinforcement learning concepts
AI Role
  • Conceptual AI model
  • Creative system
  • Tutor
  • Evaluator
Languages
English
Safeguards
  • No personal data collection
  • No student accounts created

Activity Design

6
Overall Structure
5-day mini AI summer camp combining short concept lessons with hands-on Scratch projects
Activity Flow
  1. Introduction to AI concepts
  2. Demonstration of Scratch examples
  3. Student project development
  4. Iteration and refinement
  5. Daily reflection and discussion
  6. Final mini showcase of student Scratch projects
Human vs AI Responsibilities
  • Human: Designing logic, collecting data, creative decision-making
  • AI: Simulated pattern-based behavior and responses
Scaffolding Strategies
  • Step-by-step templates
  • Visual demos
  • Peer support
  • Educator guidance

Observed Challenges (Educator-Reported)

7
  • Variation in prior Scratch experience
  • Limited time for deeper project extension
  • Technical constraints due to weak Wi-Fi
  • Debugging challenges for younger students

Design Adaptations Made

8
  • Simplified project scope
  • Increased visual demonstrations
  • Flexible pacing
  • Emphasis on creativity over correctness

Reported Outcomes (Descriptive, Not Measured)

9
Engagement
High attendance and sustained participation
Learning Signals
  • Correct identification of AI vs non-AI examples
  • Ability to explain how data affected behavior
  • Understanding of patterns and feedback loops
  • Increased confidence during project demos
Educator Reflection
Students demonstrated strong engagement and were able to explain AI ideas through their Scratch projects.

Ethical & Privacy Considerations

10
  • No personal data collected
  • No student names recorded
  • No online accounts created

Evidence Type

11
  • Practitioner observation
  • Activity documentation
  • Student project demonstrations
  • Learning analytics
  • Longitudinal assessment

Relevance to AI Education Research

12
Potential Research Use
Informal AI learning; Early AI literacy; Project-based learning
Relevant Research Domains
Learning sciences; Computer science education; AI literacy

Case Status

13
  • Completed
  • Planned expansion
  • Scaling across sites

AAB Classification Tags

14
Age
Elementary
Setting
Afterschool center
AI Function
Conceptual AI, Pattern-based behavior
Pedagogy
Project-based learning
Risk Level
Low
Data Sensitivity
None