Course Center/"Learning by Doing" AI Practice – Grades 4–6 (Software)
"Learning by Doing" AI Practice – Grades 4–6 (Software)
Elementary24 lessons
Course Overview
This course follows the main line of “Experience — Apply — Create,” guiding students step by step into the world of artificial intelligence to understand AI principles, master programming skills, and develop computational thinking through practice. In Grade 4, students learn basic AI concepts and principles, experience technologies such as AI painting and object recognition, train image classification models by hand, and complete interactive games and motion-sensing control projects. In Grade 5, they learn AI model technologies such as keypoint detection and speech recognition, develop projects such as gesture battles, Sichuan opera face-changing, and poetry line continuation, and feel the charm of AI empowering traditional culture. In Grade 6, they learn a new paradigm of AI-assisted programming, use Python to develop GUI tools, games, data analysis, and interactive web pages, and experience a human–AI collaborative development workflow.
Included Courses
Grade 4
8 class periods
Grade 5
8 class periods
Grade 6
8 class periods
Competency Goals
Self-Directed Learning
Actively explore AI application principles, discover and solve problems independently in model training and programming practice; use AI tools to assist learning while critically evaluating the accuracy of AI outputs and adopting AI-generated results with care.
Independent Decision-Making
When choosing data, adjusting parameters, and deciding on plans in AI model training and programming projects, collect information for comparison and analysis, and make reasonable choices based on independent judgment.
Self-Management
Independently plan progress for model training, programming debugging, and project development; allocate class time reasonably; record each test result and adjust the optimization direction accordingly.
Engineering Thinking
Understand the engineering flow of AI systems—“data collection → model training → test and validation → application deployment”—and evaluate and optimize solutions under constraints such as data volume and hardware performance.
Computational Thinking
Decompose AI interaction and programming tasks into the algorithm flow of “input → process → output,” use variables, loops, conditions, and other programming structures for abstract modeling, and analyze and fix program errors.
Design Thinking
Design AI interactive games and applications from user needs, iteratively improve function and experience based on test feedback, and create products users truly need.
Cultural Understanding
In projects such as Sichuan opera face-changing and poetry line continuation, understand the fusion of AI technology and traditional culture, begin to recognize possible cultural bias in AI training data, and think about ways technology can pass on culture.
Communication & Collaboration
Clearly describe programming needs to an AI assistant and integrate AI-generated code with personal creativity; express ideas effectively and listen to others in group projects to complete works together.
Critical Thinking & Innovation
Identify errors and limitations in AI-generated content (code, text, images), independently evaluate their reasonableness; propose personally creative improvements based on existing AI capabilities.
Course Advantages
Real Training, Real Experience
Students personally collect images and record speech, train image classification, gesture recognition, and speech recognition models, and understand that AI ability comes from training through the full real process of “data collection — model training — invoke and verify.”
Stepwise Progression
From experiencing AI applications, to deeper model applications, then to AI-assisted programming—three stages rise in a spiral so beginners can keep up step by step.
AI-Assisted Programming in Practice
With support from an AI coding assistant, students use Python to develop GUI tools, games, data visualization, and interactive web pages, experiencing early the human–AI collaborative workflow of “describe needs → AI generates → debug and refine.”
AI Empowers Traditional Culture
In projects such as Sichuan opera face-changing and poetry line continuation, AI technology is deeply fused with intangible cultural heritage and classical poetry, letting students feel the charm of technology passing on culture through programming practice.
