Which grade levels is the "Learning by Doing" AI-themed solution designed for?

It is designed for Grade 4 through Grade 9, covering the entire compulsory-education stage with a progressive "hardware + programming" dual-track curriculum.

What does the "hardware + programming" dual-track curriculum include?

The hardware track uses kits such as Tianji, MiniCPU, RO-E, and the AI robot dog to teach building and sensor applications; the programming track covers block-based coding, Python, AI-assisted programming, and mini-program development.

Can schools without specialized teachers implement this solution?

Yes. ShengTong provides lesson plans, courseware, teacher training, and online teaching-research support to help school teachers quickly grasp the course concepts, hardware operations, and teaching methods.

How does this solution align with the Ministry of Education "Learning by Doing" pilot action requirements?

It is designed around the Guidelines for the "Learning by Doing" Pilot Action in Science Education in Compulsory Education, ensuring at least 1 task and 4 class hours per semester, and can be flexibly integrated into existing science courses and comprehensive practical activities.

'Learning by Doing' Pilot Action in Science Education · AI Theme

'Learning by Doing' AI-Themed Solution

Aligned with the Guidelines for the 'Learning by Doing' Pilot Action in Science Education in Compulsory Education (issued by the Ministry of Education), this is a dual-track "hardware + programming" AI-themed curriculum solution for all learning stages from Grade 4 through junior high school.

Learning Stages

Themes

Tasks

Class Hours

Policy Background

Guidelines for the 'Learning by Doing' Pilot Action in Science Education in Compulsory Education (issued by the Ministry of Education)

Notice from the General Office of the Ministry of Education

Text page of the Guidelines for the 'Learning by Doing' Pilot Action in Science Education in Compulsory Education

In July 2026, the Ministry of Education issued the Guidelines for the 'Learning by Doing' Pilot Action in Science Education in Compulsory Education, launching the 'Learning by Doing' pilot action in science education.

In strengthening curriculum implementation planning, the document requires, on the basis of strictly implementing the overall requirements of the compulsory education curriculum plan while keeping the total class hours unchanged, the coordinated use of cross-disciplinary thematic learning hours within science courses, as well as hours from comprehensive practical activities, local curricula, and school-based curricula, arranged flexibly in a centralized or distributed manner, to ensure each student completes no fewer than 1 task and no fewer than 4 class hours per semester.

Ecology & EnvironmentArtificial IntelligenceAerospaceEmerging IndustriesLife & HealthEarth's Mysteries

Example of the 'Artificial Intelligence' theme from the Guidelines for the 'Learning by Doing' Pilot Action in Science Education in Compulsory Education

Solution Overview

ShengTong Education Configuration Plan for the 'Learning by Doing' Pilot Action in Science Education in Compulsory Education

I. Overall Objectives

The ShengTong Education Configuration Plan for the 'Learning by Doing' Pilot Action in Science Education in Compulsory Education aims to build a science-and-innovation education solution covering multiple core fields such as information technology, engineering technology, and artificial intelligence for all learning stages from Grade 4 to junior high school. Horizontally, the plan connects six knowledge modules—hardware building, mechanical structures, sensor applications, programming development, AI interaction, and creative creation; vertically, it forms a coherent and progressive cultivation system across six school years, adapting to the cognitive development law and science-and-innovation ability growth path of primary and secondary school students.

II. Growth Objectives

Thinking literacy:Cultivate computational thinking, engineering thinking, design thinking, and innovative thinking; build systematic logical-analysis ability and cross-disciplinary integration thinking; and form a core thinking model for the intelligent era.

Comprehensive abilities:Improve hands-on practical ability, teamwork ability, creative-expression ability, and project-review ability; and develop a rigorous engineering attitude and sustained interest in science-and-innovation exploration.

Long-term development:Build complete digital literacy and AI literacy, stimulate the intrinsic drive for technology exploration, and lay a solid foundation for subsequent participation in science-and-innovation competitions, further study in informatics, and the growth of innovative talents.

III. Course Objectives

Knowledge dimension:Systematically master knowledge such as mechanical structure principles, electronic sensor applications, core programming syntax, basic AI concepts, and mini-program development logic, and establish a complete knowledge framework of engineering technology and information science.

Ability dimension:Possess the ability to build and debug smart hardware, computational-thinking and code-implementation ability, and AI-tool application and interaction-design ability; be able to independently complete software-hardware integrated science-and-innovation projects, and form engineering-practice ability in problem decomposition, solution design, and implementation debugging.

Application dimension:Be able to transfer programming and AI technology to real-life scenarios, complete the design and implementation of works such as smart devices, creative tools, and functional mini programs, and realize the scenario-based transformation of technical knowledge.

Six-Year Continuous · 'Hardware + Programming' Dual-Track Curriculum Overview

	Grade 4	Grade 5	Grade 6	Grade 7	Grade 8	Grade 9
AI Theme · Hardware Course Configuration Plan
Task Name	Smart Companion	Smart Sensing	Smart Living	Intro to Programming	Programming Stories	AI Robot Dog
Task Content	A Singing and Dancing Smart Companion Bionic-Sensing Junior Maker	Smart Plant Watering Smart Voice-Controlled Butler	Smart Desk Lamp Smart Environmental Music Station	Adventure in the Programming World Magic Transformations	Fantasy Adventurer Interstellar Commander	Robot Dog Launch: From Building to Action Smart Voice Interaction
Class Hours	8	8	8	8	8	8
AI Theme · Programming Course Configuration Plan
Task Name	Getting Started with AI	Unlocking Model Applications	Collaborative AI Programming	Creative Expression	Intro to Mini Programs	Mini Program Interaction
Task Content	Meet AI Image Recognition	Gesture Recognition Voice Dialogue	AI-Assisted Programming Design AI-Assisted Data Processing	My AI Agent Assistant AI Agent-Assisted Creation	Meet Mini Programs Mini Program Development in Practice	AI Mini Program Creation Mini Program Project Pitch
Class Hours	8	8	8	8	8	8

Hardware Courses

ShengTong Education 'Learning by Doing' AI Theme · Hardware Course Configuration Plan Examples

Grade 4

Theme Example: Smart Companion

A Singing and Dancing Smart Companion / Bionic-Sensing Junior Maker · 2 tasks in total

A Singing and Dancing Smart Companion

Suggested class hours: 4 class hours

Task Requirements

Learn the basic concept and classification of robots (industrial robots and special-purpose robots), get to know the controller of the Tianji programming kit (integrating a touchscreen, buzzer, microphone, tri-axis accelerometer, and dual-side encoded motors), and understand the principle of sound production (vibration of objects) and the relationship between pitch and vibration frequency, as well as how the built-in buzzer of the controller works.

In Class Hour 1, complete the basic build of the Tianji robot (building block pack 01), learn the names of each part and how to assemble them, power it on to experience the preset demo programs, and form a preliminary understanding of the intelligent system of 'sensor perception → program judgment → action execution'.

In Class Hour 2, learn the basic operations of touchscreen icon programming (add, delete, replace, insert icons), master basic movement commands such as forward, backward, turn left, and turn right, understand the correspondence between the 'count' parameter in the program and the number of wheel rotations, and be able to independently write a simple movement program and run it to verify.

In Class Hour 3, learn playback-type icon programming, master the use of nine sound effects and random sound effects, be able to combine movement and sound commands to write simple programs, and understand the difference between blocking and non-blocking icons (e.g., the different running effects of continuously moving forward versus moving forward N times).

In Class Hour 4, assemble the dancing robot (building block pack 02), learn the four components of the crank-rocker mechanism (crank, rocker, connecting rod, frame), understand the mechanical principle of converting circular motion into reciprocating swing, write a dance program, and hold a robot dance party activity.

Implementation Suggestions

In Class Hour 1, start with a discussion (What do you think a robot is?), guide students to discover the common features of various robots in life, then have them build the basic Tianji model and experience the demo programs. During assembly, let students check the number of parts themselves to build awareness of engineering standards.

In Class Hour 2, focus on programming operations, letting students try each movement icon step by step and observe the effects. Encourage students to predict the program's running effect before running it to verify, cultivating the habit of 'think first, then verify'.

In Class Hour 3, first introduce the principle of sound with everyday examples such as alarm clocks and phone ringtones, then program to experience different sound effects, with the focus on helping students understand the meaning of the random sound-effect icon. The programming difficulty lies in the difference between blocking and non-blocking icons—have students write programs using 'move forward twice + sound effect' and 'move forward continuously + sound effect' respectively, compare the running effects, and discover the difference themselves.

In Class Hour 4, first analyze the crank-rocker structure (with the help of video animation), then build the dancing robot step by step, write a dance program, and hold a robot dance party activity.

Teaching Implementation

You can start from everyday scenarios such as robot vacuum cleaners and food-delivery robots to discuss how AI enables machines to complete work 'automatically'; then extend to scenarios like smart speakers playing songs on request and shopping-mall guide robots with voice announcements, discussing how AI enables machines to 'speak' and interact with people.

Extension Directions

Introduce how AI voice assistants (such as XiaoAI and Siri) perceive user commands through sensors and respond, as well as AI music composition and smart music recommendation technologies, and discuss how AI 'learns' musical styles and creates melodies.

Bionic-Sensing Junior Maker

Suggested class hours: 4 class hours

Task Requirements

Learn the basic concept and function of sensors (converting physical quantities into electrical signals), get to know the two built-in sensors of the Tianji controller (microphone and tri-axis accelerometer), understand the concept and classification of bionic robots (hexapod robots, robot dogs, flapping-wing robots, etc.), and learn the basic principle and characteristics of belt drives.

In Class Hour 1, learn the microphone sensor, understand the principle that sound vibration drives the diaphragm to vibrate and generate electrical signals, master the three sensing icons of loud, soft, and medium sound, and program functions such as sound-triggered movement and automatic backward movement after collision detection.

In Class Hour 2, learn the tri-axis accelerometer, understand its applications in balance scooters, phone shake gestures, and drone stabilization, master posture sensing icons such as flat, vertical, shake, and rotate, program functions such as action-triggered sound effects and movement, and action-based change of movement speed, and understand the mapping relationship between sensor data and robot behavior.

In Class Hour 3, assemble the four-legged walking calf robot (building block pack 03), analyze how its crank-rocker structure enables the four legs to step alternately, program functions such as sensor-triggered movement and a prompt sound when placed vertically, and hold a calf racing activity.

In Class Hour 4, assemble the robot vacuum cleaner (building block pack 04), understand the structure of the rubber-band belt drive (driving wheel, driven wheel, rubber band), learn the protective feature of belt-drive overload slipping, program multi-bend route cleaning and random-movement cleaning, compare the difference between steering icons and single-motor rotation, and choose a steering method suitable for the robot vacuum cleaner.

Implementation Suggestions

In Class Hour 1, introduce with everyday sensors such as automatic faucets and automatic lights, then have students test the microphone's trigger sensitivity by clapping, singing, and tapping the table in various ways. Key step: guide students to discover the phenomenon that 'tapping the robot's shell can also trigger the microphone', then design a collision-backward program to cultivate inquiry thinking.

In Class Hour 2, introduce the accelerometer concept with a balance-scooter video, let students actually flip and shake the controller to observe value changes, then program to achieve action control. Changing the movement speed requires the sequence of 'set speed first, then set movement', which students easily omit.

In Class Hour 3, introduce the bionic concept with videos of spider robots and robot dogs; when building, pay attention to the symmetrical position of the pins on both sides of the legs (this is the key to normal walking), and before each run, adjust the motor's starting position so the two legs are staggered front and back. For the racing session, plan start and finish lines to add a sense of competition.

In Class Hour 4, introduce with a video of a real robot vacuum cleaner and discuss its working route. When building, the inside-outside direction of the rubber band is the key point—if installed reversed, the brush will rotate backward. In the programming session, first test the difference between the two steering methods, then guide students to choose single-motor steering (slower steering but the brush does not reverse, more suitable for vacuuming), and finally use random waiting time to achieve a random cleaning route.

Teaching Implementation

You can start from everyday scenarios such as self-driving cars' automatic obstacle avoidance and smart door locks' facial recognition to discuss how AI 'perceives' the surrounding world through sensors and makes judgments; then extend to scenarios like home robot vacuum cleaners automatically planning routes and Boston Dynamics' robot dogs overcoming obstacles, discussing how AI enables bionic robots to 'learn' to adapt to different environments and work autonomously.

Extension Directions

Introduce the voice-wake technology of smart speakers (such as 'XiaoAI'), the AI behavior recognition behind the phone shake gesture, and the AI path-planning technology of home robot vacuum cleaners (such as SLAM mapping), as well as the application of 'bionics + AI' in quadruped robots (such as Unitree), and discuss how AI enables robots to adapt to the environment more intelligently.

Grade 5

Theme Example: Smart Sensing

Smart Plant Watering / Smart Voice-Controlled Butler · 2 tasks in total

Smart Plant Watering

Suggested class hours: 4 class hours

Task Requirements

Learn the moisture conditions required for plant growth and understand the working principle of soil moisture sensors (FDR/TDR type). Use the MiniCPU controller to build an automatic plant-watering robot model, and program real-time soil moisture detection—when the moisture is below a set threshold, automatically start the water pump to water the plants; when the moisture meets the standard, stop watering, and display the current soil status through an LED indicator. Experience the intelligent system workflow of 'sensor collection → data judgment → automatic control', and preliminarily establish the concept of smart sensing and automatic feedback.

Implementation Suggestions

Proceed in four steps: 'build → detect → control → optimize';

In Class Hour 1, learn the sensor principle and complete the model building;

In Class Hour 2, program to achieve moisture detection and LED status display;

In Class Hour 3, achieve automatic water-pump control and threshold judgment;

In Class Hour 4, conduct system integration testing, group-test the watering needs of different plants, and record data.

Teaching Implementation

Teaching can be combined with classroom green plants or a campus plant corner, letting students first touch with their hands to feel the difference in soil at different dryness and wetness levels. Guide students to discuss the basis for threshold setting—different plants have different water needs—and encourage students to look up information and set parameters on their own.

Extension Directions

Introduce large-scale smart irrigation systems in smart agriculture, and discuss how AI optimizes irrigation strategies based on weather forecasts and soil data.

Smart Voice-Controlled Butler

Suggested class hours: 4 class hours

Task Requirements

Learn the principle of sound production and the relationship between pitch and frequency, and understand the basic common sense of safety prevention and the working principle of alarms. Use the MiniCPU controller to build an electronic keyboard model and a smart alarm model respectively, and control different keys through programming to output corresponding pitches (C major scale), understand the influence of time parameters in the program (such as 0.2 seconds, 0.4 seconds) on note duration, and realize the performance of simple music; further write programs to achieve abnormal situation detection (such as doors and windows opening/closing, objects approaching, etc.) and trigger sound-light alarms, understand the basic logic of the intelligent security system of 'sensor detection → condition judgment → trigger response', and learn to set reasonable trigger conditions to reduce false alarms. Experience the complete process of converting physical signals into digital audio output and safety response, and preliminarily establish the comprehensive application ability of sound-light interaction and intelligent detection.

In Class Hour 1, complete the electronic keyboard model building and basic pitch programming, and understand the correspondence between the frequency value triggered by a key and the pitch.

In Class Hour 2, arrange music and practice performance, experiencing the complete process of converting physical key signals into digital audio output.

In Class Hour 3, build the smart alarm model and complete basic detection programming, understanding the system logic of 'sensor detection → condition judgment → trigger response'.

In Class Hour 4, optimize the alarm logic and test different trigger conditions, and combine sound-light alarms to achieve comprehensive security functions.

Implementation Suggestions

In Class Hour 1, complete the electronic keyboard building and basic pitch programming. During teaching, first use electronic piano software to let students feel the pitch difference, and transition to hardware programming after building perceptual understanding. Guide students to discover the correspondence between the frequency value triggered by a key and the pitch they hear, and encourage students to try modifying frequency parameters on their own to observe changes.

In Class Hour 2, arrange music and practice performance. Group cooperation can be organized, with one person programming and one person performing, to cultivate collaboration skills.

In Class Hour 3, complete the alarm building and basic detection programming. The practical application of alarms can be discussed in combination with life scenarios such as home safety and campus safety, such as anti-theft door magnets and smoke alarms.

In Class Hour 4, optimize the alarm logic and test different trigger conditions. In teaching, set up a 'false-alarm challenge' session—deliberately create interference to let students judge whether the alarm is reasonable, guiding them to think about the scientific nature of condition parameter settings.

Teaching Implementation

You can start from everyday scenarios such as electronic pianos and smart doorbells to discuss how AI achieves interaction and detection through sound signals; then extend to scenarios such as home safety and campus safety, discussing how smart security systems achieve automatic alarms and protection through sensors.

Extension Directions

Introduce AI music composition (such as AI-generated pop songs) and smart accompaniment technology, as well as AI behavior recognition technology in smart security systems (such as abnormal behavior detection and facial-recognition access control), and discuss how AI changes the way music is created and enhances safety protection capabilities.

Grade 6

Theme Example: Smart Living

Smart Desk Lamp / Smart Environmental Music Station · 2 tasks in total

Smart Desk Lamp

Suggested class hours: 4 class hours

Task Requirements

Learn the basic characteristics of light and the working principle of the photosensitive sensor. Build a smart desk lamp model, detect ambient light intensity through the photosensitive sensor, and program the basic function of automatically turning on the light when the light is insufficient and automatically turning off the light when the light is sufficient. Further expand intelligent modes such as human sensing (the light turns on when someone approaches) and stepless brightness adjustment, and experience the complete design process of an intelligent lighting system from requirement analysis to function realization.

Implementation Suggestions

In Class Hour 1, learn the photosensitive sensor and complete the basic build;

In Class Hour 2, program to achieve light detection and automatic on/off;

In Class Hour 3, expand the human-sensing function (an infrared sensor needs to be added);

In Class Hour 4, conduct system integration, optimize the demonstration, and share the solution.

Teaching Implementation

Testing can be done in different lighting environments (turning off the light, drawing the curtains, shining a flashlight, etc.) to let students intuitively feel the sensor response. Encourage students to draw a 'light → turn on light' logic flowchart to cultivate computational thinking.

Extension Directions

Introduce the smart lighting system in smart homes (such as XiaoAI control and scene-mode switching), and discuss how AI learns user habits to achieve automatic dimming.

Smart Environmental Music Station

Suggested class hours: 4 class hours

Task Requirements

Learn the storage principle of digital audio, understand the evolution of music storage media from cassette tapes, CD/VCD/DVD to USB drives, and understand the harm of air pollution and the concept of PM2.5, and learn the working principle of air-quality detection sensors. Use the MiniCPU controller and audio module to build a USB-drive music box and a PM2.5 detector and air purifier combination model respectively, and program music playback, track switching, and sound-effect control (such as POP/ROCK/JAZZ modes), as well as real-time air-quality detection and data display, automatically starting the purifier when the pollution index exceeds a set threshold. Understand the basic process of digital signal storage and analog signal playback conversion, and experience the intelligent environmental-protection system workflow of 'environment monitoring → data judgment → automatic processing'.

In Class Hour 1, build the USB-drive music box model and complete the basic playback programming.

In Class Hour 2, achieve track switching and sound-effect mode adjustment, understanding the basic process of digital signal storage and analog signal playback conversion.

In Class Hour 3, build the PM2.5 detector and program to read air-quality data.

In Class Hour 4, achieve purifier linkage control and system debugging, experiencing the intelligent environmental-protection system workflow of 'environment monitoring → data judgment → automatic processing'.

Implementation Suggestions

In Class Hour 1, build the USB-drive music box model and basic playback programming. Students can be asked to collect pictures of music storage devices from different eras (cassettes, CDs, MP3 players, USB drives) in advance, discuss the changes brought by technological progress in class, and build a timeline awareness of technological evolution.

In Class Hour 2, achieve track switching and sound-effect mode adjustment, letting students experience various playback modes of digital audio.

In Class Hour 3, build the PM2.5 detector and program to read data. Teaching discussion can be combined with local AQI data or campus environmental monitoring, so that students pay attention to environmental issues around them.

In Class Hour 4, achieve purifier linkage control and system debugging. Guide students to think about the basis for data threshold setting—referring to national air-quality standards—and cultivate awareness of data-based decision making.

Teaching Implementation

You can introduce from two dimensions: the technological evolution of music storage devices and urban air-quality monitoring, discuss how AI plays a role in audio processing and environmental monitoring, and let students feel the close connection between technological progress and environmental protection.

Extension Directions

Introduce AI applications in audio processing (such as speech recognition, smart recommendation algorithms, and AI noise reduction), as well as the large-scale application of IoT technology in environmental monitoring (such as urban air-quality monitoring networks and AI pollution-source tracking and prediction systems), and discuss how AI changes lifestyles and protects the environment.

Grade 7

Theme Example: Intro to Programming

Adventure in the Programming World / Magic Transformations · 2 tasks in total

Adventure in the Programming World

Suggested class hours: 4 class hours

Task Requirements

Learn how electricity is generated and how it helps life and production, and talk about where electricity is used in our lives; learn the composition and functions of hardware devices, the names and functions of each key on the keyboard, as well as the function of magnets and how magnetism is generated, and find magnets in life; learn the sounds corresponding to different notes, get to know the three primary colors and try color matching; master the methods and functions of mouse single-click, double-click, and drag. In programming, learn loop statements with Mengmeng C and use repeat cards, learn to use condition cards and function cards (comparing the characteristics of function cards with other cards), learn to use play cards, and complete the comprehensive use of programming cards, reviewing the knowledge learned in Mengmeng's Home, Software Village, and Hardware Village. Understand the combined design method of life cognition and software/hardware programming, and card-based programming commands.

In Class Hour 1, learn how electricity is generated and its applications, and learn loop statements with Mengmeng C, using repeat cards to write loop programs.

In Class Hour 2, learn the composition and functions of hardware, the names and functions of keyboard keys, the function of magnets and how magnetism is generated, and learn to use condition cards and function cards.

In Class Hour 3, learn the sounds corresponding to different notes, get to know the three primary colors and try color matching, and use condition cards and function cards to complete small tasks.

In Class Hour 4, master the methods and functions of mouse single-click, double-click, and drag, learn to use play cards, complete the comprehensive use of programming cards, and review the knowledge learned in Software Village and Hardware Village according to class time.

Implementation Suggestions

In Class Hour 1, complete 'electricity cognition + loop programming'. You can start from a life scenario—ask the children 'what at home won't work when the power goes out', then talk about where electricity is used in life, guiding children to understand the process of electricity coming from power plants (thermal, hydro, wind) to our side. In the programming session, proceed with task decomposition: first let Mengmeng C complete a single action, then add repeat cards to make the action loop. Let children clap 3 times and stomp 3 times to experience the meaning of 'repeat' firsthand; remind students that the loop must have a count, otherwise the program will keep running and 'won't stop'.

In Class Hour 2, complete 'hardware cognition + condition and function programming'. You can start from 'what parts is a computer/robot made of', and sequentially learn hardware composition and functions, keyboard key zones (letter area, number area, function keys), and magnet functions (attracting iron, compass, maglev). In the programming session, first learn condition cards—using 'if... then...' to analogize traffic-light rules—then learn function cards—packing a group of cards into a 'tool' that can be called directly when used; through comparison, guide children to discover: a function card is like a 'toolbox', defined once and can be used repeatedly. Reminder: function cards are abstract for younger children and can be analogized with 'packing luggage' or 'writing a recipe'; pay attention to safety in magnet activities.

In Class Hour 3, complete 'sound and color cognition + card application'. You can start from a music class, first listen to the sounds of different notes, then say the three primary colors are like 'pigment magic'—red, yellow, and blue can be mixed into more colors—letting children try matching by hand. In the programming session, use the condition cards and function cards learned in Class Hour 2 to complete small tasks (such as doing different actions based on color conditions), achieving the application of what is learned and consolidating review. Reminder: using paint/crayons for three-primary-color mixing is more intuitive; give each child a chance to mix by hand.

In Class Hour 4, complete 'mouse operation + comprehensive programming'. You can start from 'finger command'—a single click is like tapping once, a double click is like quickly knocking twice on a door, and a drag is like moving something to a new position—letting children practice the three operations one by one. In the programming session, progress by levels: first learn play cards (let the work make sound), then combine loop, condition, function, and play cards to complete a small game or story; review Software Village and Hardware Village knowledge when time permits. Reminder: double-click is easily confused with two single-clicks; demonstrate by comparison; comprehensive tasks can have a basic version and a challenge version to meet different children's needs by level.

Teaching Implementation

You can start from 'electricity', the basic energy source, lead children to recognize the composition and functions of software and hardware, and then to multimedia elements such as sound and color; in programming, from loops (repeat cards) to conditions and functions, and finally to play cards and comprehensive application, forming a complete thread of 'from life cognition to software-hardware combined programming', guiding children to understand the core idea of 'using commands to make machines work'.

Extension Directions

Discuss electricity and new energy (solar, wind power), magnets and modern technology (maglev trains, MRI, compasses), sound and AI voice assistants, the three primary colors and screen display technology (RGB), touchscreens and gesture operations, etc., and explore how AI makes devices around us smarter.

Magic Transformations

Suggested class hours: 4 class hours

Task Requirements

Learn the interface layout of the programming software, and master the functions and usage of the menu bar, stage area, stage information, module area, sprite list, and script area; learn the biological characteristics of chameleons, the three primary colors of light, and the principle of how the eye recognizes object colors, learn the principle and application of touch sensors and the types and properties of force, and learn the structure, principle, types of motors, and the movement method of dual-drive robots. Skills: learn to upload backgrounds and sprites in the software, use the mouse to control sprite enlargement, reduction, copying, and deletion; write programs with RO-E to turn the LED on and off, learn to use software programming to send and receive broadcasts, and program to control RO-E to move forward, backward, left, and right. Understand the robot programming method that combines software operation with hardware control, and multi-role communication with comprehensive control.

In Class Hour 1, learn the software interface layout, learn to upload backgrounds and sprites, and master using the mouse to control sprite enlargement, reduction, copying, and deletion.

In Class Hour 2, learn the biological characteristics of chameleons, the three primary colors of light and the principle of how the eye recognizes colors, and write programs with RO-E to turn the LED on and off.

In Class Hour 3, learn the principle and application of touch sensors and the types and properties of force, and learn to use software programming to send and receive broadcasts.

In Class Hour 4, learn the structure, principle, types of motors, and the movement method of dual-drive robots, and learn to program to control RO-E to move forward, backward, left, and right.

Implementation Suggestions

In Class Hour 1, complete 'software interface cognition'. You can start from a 'software map', first let children freely explore the interface and guess what each area is for, then explain systematically. Recognize the functional areas in the order of 'stage → role → module → script', first demonstrate uploading a background, then uploading a sprite, and operate the mouse's enlarge, reduce, copy, and delete one by one. Use metaphors to help memory: the stage is the performance platform, and the sprite is the actor on the stage. Reminder: copy and delete are prone to misoperation; teach children to use undo in time.

In Class Hour 2, complete 'color cognition + LED programming'. You can start from the chameleon's 'color-changing magic', leading to the three primary colors of light (red, green, blue)—the three lights mixed can produce various colors—then learn the principle of how the eye recognizes colors. In the programming session, decompose by task: first turn the LED on, then turn it off, and finally challenge the 'blinking' effect. Reminder: the three primary colors of light are red, green, and blue (different from the pigment primary colors red, yellow, and blue); demonstrate with a phone screen or flashlight, and remind children not to stare directly at the LED when it lights up.

In Class Hour 3, complete 'sensor cognition + broadcast programming'. You can start from 'how does a robot know if it touches something', introduce the touch sensor as the robot's 'finger skin' that sends a signal when touched; then recognize the types of force (push, pull, gravity, etc.) and find forces in life. In the programming session, analogize broadcast with 'making a phone call': one role sends a broadcast, and another role performs an action after receiving it. Reminder: the names of the broadcasting and receiving roles must correspond one-to-one; this is where younger children make mistakes most easily.

In Class Hour 4, complete 'motor cognition + movement programming'. You can first observe RO-E's 'legs'—the motors—leading to structure, principle, and types, and recognize the motor used by RO-E. Movement programming progresses by levels: first learn forward and backward, then left and right turns, and finally design small tasks such as 'walking a grid / delivering packages' for comprehensive application. Reminder: younger children easily confuse left and right; first establish a sense of direction with 'the left hand side is the left side'; set the speed and time for movement commands to avoid overshooting.

Teaching Implementation

Starting from getting to know the programming software environment, to colors and LED lights (light), sensors and broadcasts (perception and communication), and then to motors and motion control (action), forming a complete robot control thread of 'software cognition → perception → communication → action', guiding children to understand the core idea that 'programs make robots see, hear, and move'.

Extension Directions

Discuss the three primary colors of light and screen display technology (RGB), chameleon camouflage and military camouflage, touch sensors and touchscreens and automotive collision-avoidance systems, motors and electric vehicles and drones, as well as wheeled motion control in autonomous driving, etc., and explore how AI makes robots perceive and act more intelligently.

Grade 8

Theme Example: Programming Stories

Fantasy Adventurer / Interstellar Commander · 2 tasks in total

Fantasy Adventurer

Suggested class hours: 4 class hours

Task Requirements

Learn the function and application of metal detectors, learn the process of how the ear hears sound and whose ears are the most sensitive in the animal kingdom, and learn the principle of piezoelectric buzzers; learn the properties and life applications of special light such as visible light, infrared, and ultraviolet, and learn light reflection; learn the invention and function of music boxes and the structure, sensing principle, and application of infrared sensors; learn the types, habits, and development history of dinosaurs, and the formation and significance of fossils. Skills: write programs to control RO-E to perform; move RO-E on the color board to control the warrior sprite in the software, grasp the counterattack timing, press the touch sensor, and reflect the laser to defeat Medusa; correctly paste color stickers on the curved line-following map according to the melody, and edit programs to make RO-E perform line-following; correctly paste color stickers on the intersection map and dig dinosaur fossils together with RO-E. Understand the comprehensive design method that combines sensor perception, program control, and story-based tasks.

In Class Hour 1, learn the function and application of metal detectors, the process of how the ear hears sound, and the principle of piezoelectric buzzers, and write programs to control RO-E to perform.

In Class Hour 2, learn the properties of special light such as visible light, infrared, and ultraviolet and light reflection, move RO-E on the color board to control the warrior sprite, and press the touch sensor to reflect the laser and defeat Medusa.

In Class Hour 3, learn the invention and function of music boxes and the structure and sensing principle of infrared sensors, paste color stickers on the curved line-following map according to the melody, and edit programs to make RO-E perform line-following.

In Class Hour 4, learn the types, habits, and development history of dinosaurs and the formation and significance of fossils, paste color stickers on the intersection map, and dig dinosaur fossils together with RO-E.

Implementation Suggestions

In Class Hour 1, complete 'metal detector cognition + sound programming'. You can start from 'where is the treasure hidden?', leading to the function and application of metal detectors in finding treasure; then explain how sound travels into the ear (sound wave → ear → brain), and hold an 'animal hearing contest' (bat, dog, owl); finally learn the principle of the piezoelectric buzzer 'powered on it vibrates, vibrating it makes sound'. In the programming session, decompose by task: first let RO-E make a single sound, then connect them into a small melody. Reminder: the buzzer principle can be analogized with 'tapping a drum head makes it vibrate and sound'; give children a simple score before performing, to avoid random pressing.

In Class Hour 2, complete 'special light cognition + Medusa battle'. You can start from the story—'Medusa's eyes emit petrifying light; what light should the warrior use to defeat her?'—first learn the properties and applications of visible light, infrared (remote control), and ultraviolet (counterfeit-detection light), then demonstrate light reflection with a mirror. The game programming proceeds step by step: first move RO-E on the color board to control the warrior sprite, then learn to observe Medusa's attack rhythm, and finally grasp the timing to press the touch sensor and reflect the laser. Reminder: 'counterattack timing' is the hard part; first slow down to demonstrate the pattern, then use a mirror as an analogy to explain reflection; there is no need to go deep into the angle formula.

In Class Hour 3, complete 'music box cognition + line-following programming'. You can start from 'why does a music box sing once it is wound', and tell the invention story of the music box; then learn the structure of the infrared sensor (emits infrared, receives reflected signal) and the sensing principle, linking to applications such as automatic doors and robot vacuum cleaners. In the activity session, paste color stickers on the curved line-following map according to the melody, then edit a program to make RO-E walk along the line. Reminder: the color stickers must be pasted straight and accurately; if pasted crooked, RO-E will deviate; the line-following program can first use the 'follow the edge' strategy, then optimize gradually.

In Class Hour 4, complete 'dinosaur cognition + fossil digging task'. You can start from 'where did the dinosaurs go?', recognize types such as Tyrannosaurus, Triceratops, and Brachiosaurus and their habits and development history, then explain the fossil formation process (death → burial → petrification → discovery by us), pointing out that fossils are an important clue for scientists to understand dinosaurs. In the task session, paste color stickers on the intersection map, and complete the step-by-step fossil-digging task together with RO-E. Reminder: designing the digging task as a step-by-step challenge is more fun; you can extend knowledge by linking 'fossils with oil and coal'.

Teaching Implementation

From sound and metal detection (perception), special light and reflection (perception and interaction), music boxes and infrared line-following (sensing and motion), to dinosaur fossil digging (comprehensive task), the four lessons form a progressive thread of 'perception → interaction → line-following → comprehensive adventure', with each project being a story-based task, guiding children to understand 'sensors let robots perceive the world, programs let robots complete tasks'.

Extension Directions

Discuss metal detectors and modern security checks and archaeological detection; sound waves and ultrasonic technology (bat sonar → submarine sonar); infrared and thermal imaging, remote control, and facial recognition; line-following and autonomous-driving lane keeping and robot vacuum cleaners; dinosaur extinction and earth evolution, and fossil energy (coal, oil), etc., and explore how AI empowers archaeology, detection, and modern technology.

Interstellar Commander

Suggested class hours: 4 class hours

Task Requirements

Learn the relationship among the metagalaxy, the Milky Way, and the solar system, and learn related scientific knowledge about black holes; learn what a robot is and how robots help humans, and learn the difference between humans and robots; learn vibration and waves, and the sound-production methods and timbres of different instruments; learn the types and history of pets and the benefits of keeping pets. Skills: move RO-E on the color board to control the spacecraft sprite; control the spacecraft to dodge buildings and planes, grasp the timing to fire missiles and defeat the villain; use RO-E's color sensor to input color cards to control each performer to play; use RO-E's color sensor to input color cards to raise a favorite pet sprite. Understand the comprehensive design method that combines scientific cognition with robot programming, and color sensing with multi-role control.

In Class Hour 1, learn the relationship among the metagalaxy, the Milky Way, and the solar system and related scientific knowledge about black holes, and move RO-E on the color board to control the spacecraft sprite.

In Class Hour 2, learn what a robot is, how robots help humans, and the difference between humans and robots, and control the spacecraft to dodge buildings and planes and grasp the timing to fire missiles and defeat the villain.

In Class Hour 3, learn vibration and waves, the sound-production methods and timbres of different instruments, and use the color sensor to input color cards to control each performer to play.

In Class Hour 4, learn the types and history of pets and the benefits of keeping pets, and use the color sensor to input color cards to raise a favorite pet sprite.

Implementation Suggestions

In Class Hour 1, complete 'universe cognition + spacecraft control'. You can start from 'where do we live in the universe', recognizing the relationship of Earth → solar system → Milky Way → metagalaxy like zooming in on a map level by level, then learn about black holes—with super-strong gravity, a 'cosmic vacuum cleaner that not even light can escape'. In the programming session, first move RO-E on the color board to control the spacecraft sprite, and add the small task of 'collecting energy' after mastering it. Reminder: the scale of the universe is hard for children to imagine; use the zoom-in analogy of 'home → city → country → Earth → universe'; mention black holes briefly, focusing on stimulating curiosity.

In Class Hour 2, complete 'robot cognition + defend-the-Earth battle'. You can start from 'what is a robot', let children list the robots they have seen (robot vacuum cleaners, factory robotic arms, movie robots), recognize the three abilities of robots (perceive, think, act) and their help to humans (doing dangerous work, doing repetitive labor, accompanying humans), then compare the difference between humans and robots (humans have emotions and creativity). The game programming proceeds by task decomposition: first practice the spacecraft dodging buildings and planes, then practice firing missiles, and finally grasp the timing to combo and defeat the villain. Reminder: dodging plus firing at the same time is difficult for younger children; be sure to practice each step until proficient before combining; use a prompt sound to help judge the 'timing'.

In Class Hour 3, complete 'sound-wave cognition + conducting performance'. You can start from 'where does sound come from'—touch your throat when speaking and you can feel the vibration, leading to vibration producing waves (sound waves). Then recognize the sound-production methods of different instruments (string plucking, wind blowing, percussion striking) and timbre characteristics, and play a small game of 'guess the instrument by its sound'. In the programming session, use RO-E's color sensor to input color cards (each color corresponds to a performer or a note) to conduct everyone to play together. Reminder: print the correspondence table between color cards and performers in advance and post it on the blackboard; analogize timbre with 'the same song sung by different instruments tastes different'.

In Class Hour 4, complete 'pet cognition + sprite raising'. You can start from 'do you keep pets at home', recognize pet types such as cats, dogs, fish, and birds, tell the history of pets (e.g., dogs were domesticated from wolves), and talk about the benefits of keeping pets (companionship, happiness, learning responsibility). In the programming session, use the color sensor to input color cards to raise a pet sprite, designing a raising flow of 'feed → grow up → learn a new skill'. Reminder: the raising programming can use counting to achieve 'feed several times to grow one stage'; you can extend the discussion to electronic pets and AI pets.

Teaching Implementation

From universe exploration (cognition) to robot recognition (human-machine relationship), sound-wave vibration (perception), to pet raising (emotion and comprehensive task), the four lessons form a progressive thread of 'universe cognition → human-machine relationship → acoustic perception → creation and raising', with each project being a combat or growth task of the interstellar commander, guiding children to understand 'robots are good helpers of humans, and programs let robots complete various tasks'.

Extension Directions

Discuss black holes and the frontier of astrophysics (gravitational waves, radio telescopes), China's space station and Mars exploration, robots and artificial intelligence (service robots, industrial robots), the future collaboration between humans and machines, sound waves and ultrasonic technology (sonar, B-ultrasound), instruments and acoustic engineering, the history of pet domestication, as well as electronic pets and virtual life, etc., and explore how AI changes our lives.

Grade 9

Theme Example: AI Robot Dog

Robot Dog Launch: From Building to Action / Smart Voice Interaction · 2 tasks in total

Robot Dog Launch: From Building to Action

Suggested class hours: 4 class hours

Task Requirements

Get to know the functions (fun interaction, voice-command response, simple programming initiation) and basic structure of the AI robot dog, understand the installation safety specifications (anti-static hazards, no hand-turning of motors), and understand the correspondence between the AI robot dog's four legs and the servo pins and the principle of standing at 90 degrees, master the servo angle control rule (decrease clockwise, increase counterclockwise) and action program writing (stand, lift right front leg, sit). Be able to independently complete the assembly of the head and body and the installation of the legs, use the power-on test mode to verify hardware functions such as the screen, RGB lights, motors, microphone, speaker, and WiFi, and calibrate the angles of motors 1–4; be able to use fold blocks to organize programs, understand the repeated-execution problem caused by Mixly loops and delays and the 'disable/enable' technique, and be able to combine buttons with 'if... else if... else' conditional judgment to achieve multi-action switching control.

In Class Hour 1, explain the functions of the AI robot dog and its 'head/legs/body' structure, emphasize anti-static measures and no hand-turning of motors, and complete the head and body assembly in groups.

In Class Hour 2, install the legs, enter the test mode to verify each hardware function, calibrate motors 1–4 to 90 degrees, and summarize and share with the '5 questions'.

In Class Hour 3, understand 'decrease clockwise, increase counterclockwise' and the 90-degree standing principle through a degree quiz, write the stand and lift-right-front-leg actions, and explain the repeated-execution problem caused by Mixly loop + delay and the 'disable/enable' block technique.

In Class Hour 4, write the sit action, introduce buttons and 'if... else if... else' to achieve multi-action switching control, troubleshoot occasional button failures, and extend the 'urinate' action.

Implementation Suggestions

In Class Hour 1, explain the functions of the AI robot dog and its 'head/legs/body' structure, emphasize anti-static measures and no hand-turning of motors; complete the head and body assembly in groups. Use group collaboration; before building, let students touch metal to eliminate static electricity, pay attention to hole alignment and the screw-tightening order, and leave the green anti-slip feet for installation at the end of the course.

In Class Hour 2, install the legs; enter the test mode to verify the screen/RGB lights/motors/microphone/speaker/WiFi; calibrate motors 1–4 to 90 degrees; summarize and share with the '5 questions'. Use questions such as 'what parts/functions does the robot dog have / why anti-static / what is the hardest installation step / what is still not installed' to guide students to reflect on the installation process.

In Class Hour 3, understand 'decrease clockwise, increase counterclockwise' and 90-degree standing through a degree quiz; write the stand / lift-right-front-leg actions; explain the repeated-execution problem caused by Mixly loop + delay and the 'disable/enable' block. Start from the perceptual cognition of 'servo angle and leg posture', and when explaining the 'disable/enable' block, let students compare the action difference with and without delay.

In Class Hour 4, write the sit action; introduce buttons and 'if... else if... else' to achieve multi-action switching; troubleshoot occasional button failures; extend the 'urinate' action. Remind students to touch only the head when pressing buttons to avoid mis-touch; emphasize the nested logic of conditional judgment and the fallback handling of 'default keep standing'.

Teaching Implementation

From understanding the structure to driving the action, build a complete learning chain of 'build → test → program → interact'. The building session emphasizes safety specifications (anti-static, no hand-turning of motors) and reflection on the engineering process; the programming session starts from the perceptual cognition of servo angles, guiding students to understand the control logic of 'angle → posture → action', and lets students discover program-behavior differences by themselves through comparative experiments (with/without delay, with/without disable-enable).

Extension Directions

Introduce the application of AI robot dogs in real scenarios such as family companionship, campus guiding, and logistics inspection, and discuss how service robots perceive the environment and act autonomously; extend to robot dog motion planning and action library design, and introduce the application of quadruped robots in dance performances, rehabilitation assistance, and disaster rescue.

Smart Voice Interaction

Suggested class hours: 4 class hours

Task Requirements

Understand the concept of the AI agent and its relationship with artificial intelligence (a three-layer evolution from early dedicated tools → large language models → proactive actors), get to know the layered structure of AI (large model LLM → AI tools → agent-building platform → AI agent Agent) and the relationships between layers; understand the AI robot dog's capabilities and the core chain of 'AI voice command → parse parameters → control hardware', be able to build a 'dog commands + smart Q&A' AI agent workflow on the Coze platform and publish an API to obtain the workflow_id and service access token; get to know WorkBuddy's working interface, model selection, and Token billing mechanism, be able to state clear requirements to WorkBuddy in natural language to generate a web mini-game (HTML) and publish it; master the '4 required pieces of information for AI' to let AI generate the AI robot dog's .mix program and download and verify it in Mixly; understand the AI robot dog's preset programs and the safety and responsibility of using AI.

In Class Hour 1, explain the concept of the AI agent, its relationship with AI, and the three development stages, and build the 'dog commands + smart Q&A' workflow on the Coze platform, publish the API to obtain the workflow_id and token.

In Class Hour 2, explain the AI robot dog's preset programs, and summarize with the '5 questions'.

In Class Hour 3, explain the four-layer structure of AI (LLM → tools → platform → Agent) and the WorkBuddy interface/Token, and use natural language to generate an HTML mini-game and publish it.

In Class Hour 4, explain the '4 required pieces of information', use natural language to generate the AI robot dog's .mix and download and verify it in Mixly, summarize common pitfalls and debugging tips, and emphasize the safety responsibility of the 'Three Don'ts' code.

Implementation Suggestions

In Class Hour 1, explain the concept of the AI agent, its relationship with AI, and the three development stages; build the 'dog commands + smart Q&A' workflow on the Coze platform, publish the API to obtain the workflow_id and token. Use the 'driver and navigation' analogy for the AI agent's 'perceive–decide–execute'; when building the workflow, guide students to write clear system prompts (role / skills / format / boundaries). Emphasize that this lesson focuses on the robot dog, removing the original 'humanoid robot control' node and all humanoid-action content.

In Class Hour 2, explain the AI robot dog's preset programs; summarize with the '5 questions'. Let students understand how the complete chain of 'AI voice command → parse parameters → control hardware' is implemented in the robot dog's preset programs.

In Class Hour 3, explain the four-layer structure of AI (LLM → tools → platform → Agent) and the WorkBuddy interface/Token; use natural language to generate an HTML mini-game and publish it. Start from 'what AI have you used' to guide students to organize requirements with 'background / constraints / rules / acceptance criteria'.

In Class Hour 4, explain the '4 required pieces of information'; use natural language to generate the AI robot dog's .mix and download and verify it in Mixly; summarize common pitfalls and debugging tips; emphasize the safety responsibility of the 'Three Don'ts' code. For the hardware session, remind students to understand the program before burning it; for common pitfalls, copy an existing .mix for reference, supplement hardware information, and restart the dog for debugging.

Teaching Implementation

Use the 'driver and navigation' analogy throughout the AI agent's core logic of 'perceive–decide–execute', from understanding the AI agent concept to building the workflow, then to using AI tools to generate applications and code, building a complete learning chain of 'cognition → building → generation → verification'. In the Coze platform session, guide students to write clear system prompts (role / skills / format / boundaries); in the WorkBuddy session, guide students to organize requirements with 'background / constraints / rules / acceptance criteria'; in the hardware session, emphasize understanding the program before burning it.

Extension Directions

Introduce the application of AI agents in smart homes, personal assistants, and customer service, and discuss the technical challenge of multi-agent collaboration and 'letting AI understand and execute'; extend to the trend of AIGC and human-AI collaborative creation, as well as the ethical responsibility of AI use.

Software Courses

ShengTong Education 'Learning by Doing' AI Theme · Software Course Configuration Plan Examples

Grade 4

Theme Example: Getting Started with AI

Meet AI

Suggested class hours: 4 class hours

Task Requirements

Observe AI applications around us (smart speakers, autonomous driving, mobile apps, etc.), understand the basic concept of artificial intelligence, and distinguish the relationship between AI, robots, and programming; then get to know the 'brain' of AI—the model—learn the capabilities and uses of different types of models such as large language models, image-recognition models, and speech-recognition models, and experience AI painting generation and object recognition. Establish the understanding that AI is driven by programming and imitates human learning behavior, and understand the application of different models in different scenarios.

Implementation Suggestions

1
Pose the Question
Guide students to observe AI applications in life such as smart speakers, autonomous driving, and mobile apps, and think about 'What is artificial intelligence?', 'Why can AI learn?', 'What is the difference between AI, robots, and ordinary programming?', and 'Does AI have a brain, and what is that brain?'.
2
Design & Implementation
Organize students to experience AI interactions such as doodle recognition and fruit classification; observe through the 'Bird Adventure' game how AI learns and gets stronger from failures; experience AI painting generation and object recognition, and learn the capabilities of different models such as language, image, and speech; use graphical tools and a simple-sketch dataset to complete model training and testing.
3
Research & Discussion
Combine the experience activities to discuss the characteristics of supervised learning, unsupervised learning, and reinforcement learning, and distinguish the differences between weak AI, strong AI, and super AI; compare the similarities and differences between human-brain learning and model training, discuss the impact of data quantity and quality on model effectiveness, and analyze the role of the three elements of data, algorithm, and computing power.
4
Share & Present
Groups report their new understanding of AI and models, demonstrate the trained or tested model results, share 'how the model learned', and exchange methods to improve model accuracy and scenarios where AI cannot replace human judgment.

Image Recognition

Suggested class hours: 4 class hours

Task Requirements

Learn the basic process of image classification and model training, use a graphical programming platform to collect image samples for apples and bananas and train a classification model, complete the 'Monkey Loves Fruit' interactive game, and preliminarily experience the complete process of 'collection → training → recognition → feedback'; then use image-recognition technology to achieve somatosensory control, map the camera recognition result to game direction-control signals, complete the 'somatosensory bouncing-ball' game, and comprehensively apply coordinate positioning, character control, and image recognition.

Implementation Suggestions

1
Pose the Question
Create the scenario 'what fruit does the little monkey like', and think about 'how to let AI recognize apples and bananas?', 'what needs to be prepared?', and 'what if recognition is wrong?'; experience the traditional keyboard-controlled bouncing-ball game, and think about 'can we control the paddle without a keyboard, in other ways?', and 'how does image recognition become a game operation?'.
2
Design & Implementation
Prepare apples and bananas, the two kinds of fruit; add the image-classification extension in the graphical programming platform, set categories and collect apple and banana images from multiple angles and distances; train the model and write an interactive feedback program after recognition to complete 'Monkey Loves Fruit'; learn stage coordinates and character positioning, build the basic bouncing-ball game (paddle movement, ball bounce, collision detection, scoring), and connect the classification model to the game to set the correspondence between recognition results and paddle movement directions.
3
Research & Discussion
Test the model's recognition effect at different angles, distances, and lighting, discuss 'why does AI sometimes recognize wrongly?', and analyze the impact of data diversity on recognition accuracy; test the sensitivity and accuracy of somatosensory control, and compare the advantages and disadvantages of keyboard control and somatosensory control.
4
Share & Present
Demonstrate the 'Monkey Loves Fruit' and 'somatosensory bouncing-ball' works, share training-data and debugging experience, discuss how to make the model recognize more accurately, and imagine what other games image recognition can control.

Grade 5

Theme Example: Unlocking Model Applications

Gesture Recognition

Suggested class hours: 4 class hours

Task Requirements

Learn the basic principle of keypoint-detection technology, understand the difference between keypoint detection of human hands, faces, and bodies, use human-hand keypoint detection to complete the 'rock-paper-scissors' gesture-recognition game, and experience the application of computer-vision technology in somatosensory interaction; then combine the Peking opera facial-makeup culture and the Sichuan opera face-changing intangible heritage to design a gesture-controlled face-changing interactive project, understand the meaning of facial-makeup colors (red for loyalty, white for treachery, black for uprightness, etc.), and combine the gesture-recognition model with traditional-cultural creative expression.

Implementation Suggestions

1
Pose the Question
Experience the 'Snowfield Racing' somatosensory game, and think about 'why can a palm control the car's movement?' and 'how does the computer know my gesture?'; enjoy Peking opera facial-makeup and Sichuan opera face-changing videos, and think about 'how is face-changing achieved?' and 'can AI and gestures control face-changing?'.
2
Design & Implementation
Learn the principle of human-hand keypoint detection; collect training data for the three gestures rock, scissors, and paper; train the gesture-classification model; write a program to achieve real-time human-computer battle; learn the meaning of facial-makeup colors (red for loyalty, white for treachery, black for uprightness, etc.), design the correspondence between gestures and facial makeups, train the gesture-recognition model, and use graphical programming to achieve the interactive effect of 'recognize gesture → switch facial-makeup style'.
3
Research & Discussion
Test the recognition effect under different angles, left/right hands, and lighting conditions, discuss the application of keypoint detection in VR, sign-language recognition, and smart homes, and analyze the reasons for inaccurate model recognition; discuss how AI makes traditional art 'come alive', analyze the sensitivity and false-trigger issues of gesture-controlled face-changing, and think about more possibilities of combining traditional culture with AI.
4
Share & Present
Demonstrate the gesture-battle and Sichuan opera face-changing works, challenge each other to experience the recognition effect, share experience in improving data and models, and evaluate the works' creativity and technical implementation.

Voice Dialogue

Suggested class hours: 4 class hours

Task Requirements

Learn the basic principle of speech recognition (sound → spectrogram → text recognition), use speech-recognition technology to add voice-cheering interaction to the new 'Tortoise and Hare' story game, and feel the convenience of voice interaction; then comprehensively apply speech recognition, large language models, and speech-synthesis technology to develop the 'poetry continuation' mini-game, experience the complete interaction chain of 'voice input → AI understanding → smart reply → voice reading', and feel the application of AI in the inheritance of traditional culture.

Implementation Suggestions

1
Pose the Question
Review the 'Tortoise and Hare' story, and think about 'can voice help the turtle win?' and 'how does the machine understand speech?'; launch the poetry challenge 'a lone smoke rises straight in the vast desert—what is the next line?', and think about 'can AI set the question while I continue the poem by voice?'.
2
Design & Implementation
Record voice commands such as 'cheer' as training data; train the speech-recognition model; connect the recognition result to the game to achieve the voice interaction of 'shout cheer → turtle accelerates'; describe the 'poetry-continuation question-setting and judging' requirement to the large AI model, use speech recognition to obtain user answers, use speech synthesis to read questions and feedback aloud, and use variables and loops to control multi-round dialogue and scoring.
3
Research & Discussion
Test the recognition effect under different speech rates, volumes, and noise environments, distinguish the difference between speech recognition and simple sound detection, and discuss the applications of speech recognition in life; test the accuracy of AI judging, discuss 'how does AI judge right or wrong?' and 'which poem lines are easily misjudged?', and analyze how the large model, speech recognition, and speech synthesis work together.
4
Share & Present
Shout cheer loudly to let the turtle win, hold a poetry-continuation challenge, demonstrate the works, and share the experience of voice-controlled games and the insights of AI-assisted traditional-culture learning.

Grade 6

Theme Example: Collaborative AI Programming

AI-Assisted Programming Design

Suggested class hours: 4 class hours

Task Requirements

Learn Python basics and GUI programming, understand the concept of GUI elements such as windows, buttons, and input boxes, and write practical small tools with a graphical interface (such as a calculator) with AI assistance, experiencing the process of human-AI collaborative programming; then analyze the three core components of a game (visual elements, interactive operations, game rules) and the main-loop mechanism, and complete small games such as Snake with AI-assisted programming, experiencing the development process of 'understand structure → describe requirement → AI generates code → debug and refine'.

Implementation Suggestions

1
Pose the Question
Experience GUI programs such as calculators and electronic clocks, and think about 'what common features do these programs have?' and 'how to make the computer display windows and buttons as I want?'; experience classic small games such as Snake, and think about 'how does the game keep running?' and 'how does the ball know it hit the wall?'.
2
Design & Implementation
Learn Python basics and GUI controls (windows, buttons, input boxes), describe the requirement of a 'countdown calendar' or 'pomodoro timer' to the AI assistant, generate, run, and debug the code; analyze the three core components of the game (visual elements, interactive operations, game rules), describe the Snake requirement to the AI, generate code and run it, and ask the AI for help with debugging and optimization based on problems.
3
Research & Discussion
Discuss the advantages and limitations of AI-assisted programming, analyze how to describe requirements clearly so that AI generates more accurate code, and check and optimize the AI-generated program; discuss the role of the game main loop, analyze why the game needs to continuously refresh the screen, and summarize the efficiency of AI-assisted programming and the points to pay attention to.
4
Share & Present
Demonstrate your first Python GUI program and self-developed game, share the experience of describing requirements to AI and the debugging process and development story, experience each other's works, and propose improvement suggestions.

AI-Assisted Data Processing

Suggested class hours: 4 class hours

Task Requirements

Understand the concept of data and various forms (numbers, text, images, sound, video), master the statistical analysis method of tabular data, use Python with AI assistance to statistically analyze tabular data such as class grades, and feel the practical value of data analysis; then learn the three components of a web page—HTML (structure), CSS (style), JavaScript (interaction)—and complete an interactive web project with functions such as automatic question generation, right/wrong judgment, and scoring with AI-assisted programming.

Implementation Suggestions

1
Pose the Question
Show the class grade table of 50 students, and think about 'how to quickly calculate the total score, average score, and ranking?' and 'what chart best shows the grade distribution?'; experience interactive web pages, and think about 'how is a web page made?' and 'what are HTML, CSS, and JS each responsible for?'.
2
Design & Implementation
Learn the concept and forms of data, install a third-party data-analysis library, describe statistical and visualization requirements to the AI, generate Python code to analyze and chart data such as class grades and sports records; use the 'house' analogy to understand the web-page trio (HTML = skeleton, CSS = decoration, JS = appliances), describe web-page requirements to the AI, generate HTML/CSS/JS code, and preview, debug, and optimize it in the browser.
3
Research & Discussion
Discuss what types of data different charts (bar chart, line chart, pie chart, etc.) are suitable for showing, analyze the learning or sports situation reflected by the charts, and check the correctness of the AI-generated code; discuss how the three-layer web structure works together, analyze how to adjust the prompt words to make the AI generate web pages that better meet the requirements, and explore what other functions web pages can achieve.
4
Share & Present
Demonstrate the data-analysis results and visualization charts, share the patterns discovered, and discuss how data helps us make decisions; demonstrate your own creative web page, share the design ideas and debugging experience, visit each other's pages, and propose improvement suggestions.

Grade 7

Theme Example: Creative Expression

My AI Agent Assistant

Suggested class hours: 4 class hours

Task Requirements

Get to know the concept and capabilities of the AI agent, understand the difference between AI agents and traditional AI Q&A tools (AI agents can directly operate computer files, etc.), use the AI agent to complete practical tasks such as desktop file classification and organization, and experience the value of AI agents in information management; then comprehensively apply the AI agent's search, information-integration, and PPT-generation capabilities to complete a three-day Beijing trip plan and generate an illustrated travel-plan PPT, experiencing the AI agent's comprehensive capabilities in information retrieval, content creation, and multimedia expression.

Implementation Suggestions

1
Pose the Question
Show a messy desktop to raise the problem, and think about 'why is manual file organizing so inefficient?' and 'why can DeepSeek only give a plan but not directly operate the computer?'; create the scenario 'Lele is going to travel to Beijing', and think about 'how to plan a three-day trip?' and 'what help can the AI agent provide in travel planning?'.
2
Design & Implementation
Introduce the concept and capabilities of the AI agent to students, guide them to try describing requirements to the agent, let the agent automatically create classified folders and move files, and compare the efficiency before and after use; compare traditional guide search with the agent planning method, choose a suitable travel-industry AI agent, describe the requirement of 'plan a 3-day Beijing trip and generate a PPT', and let the agent search for information and generate an illustrated travel plan.
3
Research & Discussion
Discuss the difference between AI agents and traditional AI Q&A tools, analyze the application scenarios of AI agents in information management and automated office work, and think about what AI agents can and cannot do; discuss the scientificity and rationality of the plans generated by AI agents, analyze how to optimize prompt words to obtain more accurate results, and explore the applicable scenarios of generalist AI agents and specialist AI agents.
4
Share & Present
Demonstrate the organized desktop and classification rules, share the experience of describing requirements to the AI agent, and discuss the precautions for using AI agents; demonstrate the generated travel-plan PPT, share good places to visit in Beijing and the planning ideas, and discuss the applicable scenarios of generalist AI agents and specialist AI agents.

AI Agent-Assisted Creation

Suggested class hours: 4 class hours

Task Requirements

With AI-assisted programming, develop a garbage-sorting interactive mini-game to consolidate environmental knowledge in the game, and experience the complete creation process from understanding game requirements → clearly describing them to AI → generating code → testing and refining; then comprehensively apply AI capabilities to build a personalized personal learning butler, achieving functions such as automatic organization of a wrong-question notebook, review-plan formulation, and learning-diagnosis report generation, and learn to accurately describe requirements, evaluate AI output, and experience the practical application of AI in self-management and learning planning.

Implementation Suggestions

1
Pose the Question
Conduct a garbage-sorting Q&A warm-up, and think about 'which bin should batteries go into?' and 'which garbage do children easily sort wrongly?'; create the scenario of piles of exam-review materials, and think about 'why don't we organize wrong questions and plans normally?' and 'can AI be my learning butler?'.
2
Design & Implementation
Discuss the complexity of the traditional game-development process, learn to use AI to simplify the path, clearly describe the requirement of the 'garbage-sorting interactive mini-game' to the AI, generate code and run tests; discuss the functions the learning butler should have (wrong-question notebook organization, review plan, diagnosis report, etc.), clearly describe the requirements to AI agents such as WorkBuddy, and check and adjust the AI output.
3
Research & Discussion
Test the game's playability and knowledge accuracy, discuss how AI-assisted programming lowers the development threshold, and analyze how the game helps consolidate environmental knowledge; evaluate the rationality of the AI-generated learning plan, discuss the advantages and boundaries of AI-assisted self-management, and think about which decisions must be made by oneself.
4
Share & Present
Demonstrate the garbage-sorting game works, share requirement-description and debugging experience, play each other's games and propose improvement suggestions; demonstrate each one's 'personal learning butler', share usage experience, and discuss how to make AI a real learning assistant rather than a replacement for thinking.

Grade 8

Theme Example: Intro to Mini Programs

Meet Mini Programs

Suggested class hours: 4 class hours

Task Requirements

Get to know the concept, characteristics, and basic architecture of WeChat mini programs, understand the difference between mini programs and traditional mobile apps, experience the convenience of mini programs being 'no installation needed, ready to use on open' and the technical architecture of 'render layer (wxml/wxss) + logic layer (js)' running in dual threads in parallel, and build an overall cognition of the mini-program world; then learn the complete product-design process from requirement analysis to interface prototype design, use the 'real-need formula' to distinguish true from false needs, evaluate requirement priority with the Maslow hierarchy of needs and the KANO model, and draw the mini program's functional structure and page prototype with mind maps and Rams' design principles.

Implementation Suggestions

1
Pose the Question
Guide students to recall the WeChat mini programs they have used (maps, ride-hailing, takeout, etc.), and think about 'what exactly is a mini program?' and 'what is the difference between it and an ordinary mobile app?'; using the scenario of a 'self-introduction mini program', think about 'how would such a mini program be designed?' and 'in what scenarios do students use mini programs every day?'.
2
Design & Implementation
Compare the differences between mini programs and traditional apps in development cost, architecture uniformity, and sharing methods, and understand the feature of mini programs being 'no download or installation, gone after use' and the technical architecture of 'render layer + logic layer' running in dual threads in parallel; learn the product-development process, use the real-need formula (user role / interaction scenario / usage frequency / usage purpose, etc.) to distinguish true from false needs, sort requirements with the Maslow hierarchy of needs and the KANO model, and refer to Rams' design principles to make the design simple and meaningful.
3
Research & Discussion
Discuss the background of the emergence of mini programs, analyze how dual-thread parallelism avoids web-page lag, and explore how mini programs change daily life; recognize common page structures (header, main content, navigation bar) and official component-library controls, discuss how to organize requirements into functions through mind maps, analyze the correspondence between technology and functions, and reasonably plan page jumps.
4
Share & Present
Experience a mini program integrated with artificial intelligence, share the usage feelings, and imagine what other life problems can be solved with mini programs; divide into groups and discuss requirements, each person draws a mini-program prototype page, goes on stage to share the design idea, and evaluates and improves with each other.

Mini Program Development in Practice

Suggested class hours: 4 class hours

Task Requirements

Install and get to know the WeChat DevTools (Education Edition), learn to create a mini-program project, understand the roles of the four types of files wxml, wxss, js, and json, modify the page structure and style by hand, and experience the implementation process of 'design draft → runnable mini program'; then learn the mini-program publishing process, master the methods of uploading, filling in the version number, and publishing for experience, and further improve the personal-introduction mini program—adding a personal photo, modifying the display information and name, understanding the data organization of variables and arrays, and completing and sharing your first publishable mini program.

Implementation Suggestions

1
Pose the Question
Show the designed mini-program design draft, and think about 'how to turn the idea on paper into a usable mini program on the phone?' and 'what tools are needed to develop a mini program?'; students have made a personal-introduction page in the simulator, and think about 'why can't I see it on the phone?' and 'how to share the mini program with friends?'.
2
Design & Implementation
Download and install the WeChat DevTools (Education Edition) from the official website, log in to the account and create the first mini-program project, and get to know the programming window (simulator, resource manager, code-editing area) and the debugger; recognize the four types of mini-program files (wxml structure, wxss style, js logic, json configuration), discuss the rule that the wxml tag language 'appears in pairs', and manually replace page files and modify wxml text and wxss color styles; create a project through a template and learn the publishing process, customize the mini-program name and icon, import the classroom program package, and upload the personal photo to the asset library and reference it by link.
3
Research & Discussion
Get to know the view and text components and relative paths in wxml, and analyze why you must click 'compile' after modifying the code to see the effect in the simulator; compare the advantages and disadvantages of the two image methods of network images and local asset library, and understand how variables and arrays in js store and read page data.
4
Share & Present
Manually modify the page content and style, observe the simulator changes, and demonstrate your first runnable mini-program page; change the personal introduction to your own name, photo, and hobbies, publish and scan the code to experience your mini program, complete the 'extreme challenge' to add new display items to the page, and visit and evaluate each other.

Grade 9

Theme Example: Mini Program Interaction

AI Mini Program Creation

Suggested class hours: 4 class hours

Task Requirements

Preliminarily understand the WeChat mini-program R&D process and requirement-analysis methods (5W1H, real-need formula), install and import the preset programs in the WeChat DevTools, modify the page content and style by hand, and prepare for creating your own mini-program works later; then understand the concepts and basic characteristics of artificial intelligence and generative AI, recognize that AI-assisted programming is a branch of generative AI, and with the WeChat mini-program AI assistant, quickly generate and publish an AI knowledge-card mini program by describing requirements in natural language.

Implementation Suggestions

1
Pose the Question
Combine 5W1H to guide students to think about 'what kind of mini program do I want to make?' and 'what life problem does it solve?'; guide students to distinguish 'scenarios where AI is used in life' from 'what is artificial intelligence', and think about 'what can generative AI generate?' and 'can AI help us write programs?'.
2
Design & Implementation
Learn the product-development process (requirement analysis → product design → program development → test and launch), and use the real-need formula to calculate true/false needs; download and install the WeChat DevTools and log in, import the classroom preset program, and get to know each area of the programming window; manually modify wxml text and wxss color styles, and observe the page changes after compilation; explain the definition of artificial intelligence and its four basic characteristics (learning ability, prediction ability, perception ability, behavior ability), recognize the relationship between generative AI and AI-assisted programming, and log in to the creation platform to use the WeChat mini-program AI assistant.
3
Research & Discussion
Get to know the four types of mini-program files wxml, wxss, js, and json, and discuss 'why recompile after modifying the code'; experience stating clear requirements to the AI assistant in natural language, make the 'AI knowledge card' mini program (introducing the four characteristics), and analyze the key functions and page structure of the 'Mood Garden' case.
4
Share & Present
Demonstrate the effect of modifying the personal-introduction mini program, share the product ideas conceived with 5W1H, and inspire each other's creative directions; publish and demonstrate the mini program generated with the AI assistant, share the understanding of 'AI-assisted programming', and discuss in what other works generative AI can play a role.

Mini Program Project Pitch

Suggested class hours: 4 class hours

Task Requirements

Comprehensively apply the hierarchy-of-needs theory and the 5W1H method to discover real problems in life, use the MVP (minimum viable product) idea to design the core functions of the mini program, and with the AI assistant, from requirement description to generation, trial, and fixing item by item, complete a mini-program work on the theme of 'AI and Life'; then learn the WeChat mini-program pitch rules and review criteria, master the writing and production methods of the project specification and demo video, as well as the complete process of registration, publishing, and material submission, and supplement advanced knowledge such as mini-program events, data binding, and local storage.

Implementation Suggestions

1
Pose the Question
Guide students to use 5W1H to analyze difficulties encountered in life, and think about 'what is the need behind this difficulty? and what groups of people also encounter it?'; show the pitch theme 'AI and Life' and key time nodes, and think about 'what do the judges value?' and 'what materials does my work need to submit?'.
2
Design & Implementation
Evaluate needs with the Maslow hierarchy of needs, determine whether identity verification is needed and how (focus on convenience), use the MVP idea to do only the 1–2 most core functions, and design according to the principle of 'number of pages → overall conception → detail conception'; describe requirements to the AI assistant in a fixed format to generate the work, try it from the beginning and record the abnormal functions item by item, follow the process of 'raise problem → AI generates → use again → check if solved' to fix problems, and hand complex errors to AI for smart repair; interpret the five major review dimensions and their weights, sort out the list of essential materials, and learn the complete process from registering on the official website to publishing the work, obtaining the AppID and version number, and finally submitting materials.
3
Research & Discussion
Use AI to assist in writing the project specification and generating the PPT, plan and record the demo video according to the structure of 'personal introduction + work demonstration + technical explanation + summary', and discuss the originality of the work and the boundary of AI-assisted writing; expand to learn the mini program's event mechanism, data binding, and local storage, laying the foundation for improving the work's functions and the competition defense.
4
Share & Present
Demonstrate your 'AI and Life' work and share the creation process, organize the project background, functions, process, and future outlook into a Word project file to prepare for competition submission; complete the material-submission drill of the work, visit and evaluate each other, and discuss the boundary of AI-assisted creation and the highlights of the work.