Course Plan
This 8-lesson course, aligned with CSTA and AI4K12 standards, teaches students AI camera applications, sensor control, and programming through project-based learning. Each 45-minute lesson follows the 5E instructional model, engaging students in real-world problems, hands-on exploration, and building comprehensive projects like a smart farm system. Students learn face detection, motion detection, and self-learning mode, integrating these into practical applications such as panoramic surveillance, warehouse monitoring, and an automatic feeder.
1. Course Overview
Based on the BOSON Barnyard Kit, this course targets G3-G5 (ages 8-12) students. Through 8 lessons (45 min each) of project-based learning, students will master AI camera applications, sensor control, and programming logic, ultimately building a smart farm integrated system.
The course aligns with CSTA K-12 CS Standards (2017) for G3-G5 and the AI4K12 Guidelines (AAAI/CSTA). Each lesson unfolds through the following five phases:
5E Instructional Phases
| Phase | Name | Purpose |
|---|---|---|
| E1 Engage | Engage & Spark Interest | Present real-world problems or scenarios to spark student curiosity and inquiry, leading to the key question of the lesson. |
| E2 Explore | Hands-On Exploration | Students connect hardware, observe phenomena, test different conditions, and record findings, building an intuitive understanding of AI principles through exploration. |
| E3 Engineer | Build & Program | Plan algorithm logic (e.g., flowcharts, pseudocode), write and download programs in MakeCode/Mind+ to implement core functions. |
| E4 Experience & Challenge | Experience, Optimize & Challenge | Add customization on top of basic functions or solve real-world usage problems; deepen understanding through challenge tasks. |
| E5 See More | AI Knowledge: Extension / Ethics / Bias | Connect to broader knowledge — discuss extension knowledge, ethical issues, and bias related to the technology. |
Course Structure
- L1: Basic Hardware (onboard sensor + light strip control)
- L2, L4, L6: AI Exploration (Face Detection → Motion Detection → Self-Learning Mode)
- L3, L5, L7-L8: Comprehensive Projects (Panoramic Surveillance → Warehouse Monitoring → Scarecrow → Auto Feeder)
2. Course Outline
| # | Lesson Title | Hardware | Description / AI Knowledge | CSTA | AI Standards |
|---|---|---|---|---|---|
| L1 | Farm Control Board | micro:bit + Breakout Board + LED Light Strip | [Function] Use the onboard sensor to detect ambient light and automatically control the LED light strip on/off, creating a light-controlled smart lamp. | 1B-CS-01 | — |
| L2 | AI Exploration: Face Detection | micro:bit + Breakout Board + AI Camera + Buzzer | [Function] Display a pattern on the LED matrix when the AI camera detects a face; show nothing when no face is detected. [AI Knowledge] ① Concept and principles of face detection ② Explore factors affecting detection: lighting (bright/dark), angle (front/side), distance (near/far), occlusion (eyes/mouth/mask/photo) |
1B-AP-13 | HUMANS AND AI - The Choice to Use AI REPRESENTATION AND REASONING - Understanding Representation SOCIETAL IMPACTS OF AI - Individual Impacts |
| L3 | Farm Panoramic Surveillance | micro:bit + Breakout Board + AI Camera + Servo + Buzzer | [Function] The servo rotates the AI camera left and right to scan, solving the blind spot of fixed-angle detection and achieving panoramic face detection surveillance. | 1B-AP-10 | — |
| L4 | AI Exploration: Motion Detection | micro:bit + Breakout Board + AI Camera + Buzzer | [Function] The AI camera detects moving objects in the frame with three adjustable sensitivity levels. Triggers an alarm when motion is detected. [AI Knowledge] ① Motion detection principle: pixel change between adjacent frames ② Three sensitivity levels: Low (large change), Medium (medium change), High (small change) ③ Motion detection vs. face detection |
1B-AP-10 | MACHINE LEARNING - Sensing REPRESENTATION AND REASONING - Reasoning |
| L5 | Farm Warehouse Monitoring | micro:bit + Breakout Board + AI Camera + LED Light Strip + Buzzer | [Function] Integrates motion detection + LED strip + buzzer with arm/disarm mode switching to create a warehouse security monitoring system. | 1B-AP-09 | — |
| L6 | AI Exploration: Self-Learning Mode | micro:bit + Breakout Board + AI Camera | [Function] Teach the AI to recognize specified objects (e.g., tools/animals) through self-learning mode, mastering the complete AI workflow: data collection → model training → inference. [AI Knowledge] ① Complete AI workflow: data collection (multi-angle photos) → model training → inference ② Self-learning mode vs. traditional programming |
1B-AP-10 | MACHINE LEARNING - How Computers Learn MACHINE LEARNING - Building and Using AI Models MACHINE LEARNING - Data |
| L7 | Bird-Repelling Scarecrow | micro:bit + Breakout Board + AI Camera + Servo + Buzzer | [Function] When the AI detects a bird intrusion, the servo activates the scarecrow and the buzzer sounds. Uses nested conditionals and loops for smart bird-scaring. | 1B-AP-10 | — |
| L8 | Automatic Quantitative Feeder | micro:bit + Breakout Board + AI Camera + Servo + Motor | [Function] Learn the visual features of cows and sheep separately. When the AI detects a cow or sheep, automatically dispense feed; when other animals are detected, do nothing. | 1B-AP-12 | — |
Was this article helpful?