AICE Introduction

AICE AI 素養測評

AICE 是面向青少年的人工智能核心素養測評。這個互動地圖把原有架構圖拆成可探索的能力模塊，展示從理論、應用、編程到算法實踐的完整路徑。

Explore Framework Download AICE Overview

[CORE][AICE_01]

AI Theory Integration

Builds the conceptual base for understanding artificial intelligence as technology, method, and social system.

  • AI foundational theory and common AI optimization methods
  • Introductory machine learning concepts and workflows
  • The relationship between AI and society
  • Digital foundations, information retrieval, and information technology
  • General technology awareness for primary and junior secondary stages

[FIELD][AICE_02]

Application Domains

Connects AI literacy to the real-world scenarios students already recognize in city life, homes, agriculture, and healthcare.

  • Smart city and smart transportation scenarios
  • Smart home and intelligent living applications
  • Smart agriculture and environmental sensing
  • Advanced healthcare and assistive technology examples
  • Case-based discussion of AI opportunities and limitations

[CODE][AICE_03]

Programming Design

Turns computational thinking into executable work through procedural programming and mainstream languages.

  • Algorithmic thinking and procedural programming logic
  • Python syntax, projects, and problem solving
  • C, C++, and language transfer for advanced students
  • JavaScript and web-based creative coding exposure
  • Project practice that links code to AI applications

[CONTROL][AICE_04]

Intelligent Control

Moves AI from screen to device through robotics, sensing, control systems, and electronic circuits.

  • Block-based robotics and mechanical structure exploration
  • Non-block robotics and programmable control systems
  • Drone and humanoid robot application contexts
  • Sensors, actuators, and electronic circuit foundations
  • Hands-on control projects that test reasoning and iteration

[MODEL][AICE_05]

Algorithm Foundations

Introduces the methods behind modern AI systems, from data and vision to language, learning, and knowledge representation.

  • Big data concepts and data-driven problem framing
  • Computer vision and image understanding examples
  • Natural language processing and communication tasks
  • Machine learning foundations and model evaluation
  • Knowledge engineering, including knowledge graphs and expert systems

[MAKE][AICE_06]

Product Structure

Frames AI learning as product making, combining structure, fabrication, immersive media, and presentation.

  • Structural building and product mechanism thinking
  • 3D manufacturing and design-to-object workflows
  • Laser cutting and digital fabrication awareness
  • VR and AR application exploration
  • Prototype presentation that links design intent to technical choices

Why it matters

Multi-stakeholder value of AICE

For Students

Gain nationally recognized AI literacy achievements that support progression planning and future opportunities.

For Educators

Pursue recognized AI teaching credentials and guide students in official competitions and project pathways.

For Schools

Enhance school visibility through participation in recognized initiatives and AI education programs.

For Society

Build stronger AI talent pipelines by aligning youth education with long-term technology development.

Logidemy pathway

From framework to exam-ready learning

Logidemy connects the AICE framework with school-friendly course planning, project practice, mock assessment, and exam coordination.

[01]

Map

Identify the student level and match learning goals to the AICE competency blocks.

[02]

Build

Use coding, robotics, AI applications, and maker projects to build evidence of understanding.

[03]

Assess

Prepare with checkpoints and mock assessment aligned to the official structure.

[04]

Certify

Coordinate course, registration, and exam arrangements through the Hong Kong operations pathway.

Registration

Registration & Inquiry

For school registration, curriculum alignment, or implementation support, contact the Hong Kong operations center.

Official Linktree Contact Us