Professional expertise is embodied in “translation”—transforming complex technologies into learning experiences tailored to different stages of cognitive development. I have designed a curriculum spanning ages 3 to 18, structured as: Understand AI → Use AI → Question AI → Create with AI → Evaluate AI → Lead with AI, with precise age‑specific segmentation.

• Ages 3–6: Nurture curiosity rather than impose preconceived knowledge, using voice‑based interactions, AI‑powered picture books, and image‑generation tools to transform imagination into sound and visuals.

•Ages 7–12: Transition from “answering questions” to “learning to ask questions,” lowering the barrier to entry for technological creation through visual programming, robotics, and gamified projects.

•Ages 13–15: Transition AI from a “learning assistant” to a “thinking partner,” using Socratic questioning to cultivate critical thinking and information literacy.

•Ages 16–18: Dive into real-world data engineering, model training, robotics, and embodied intelligence, while exploring the boundaries between efficiency and ethics, and moving toward innovation and responsibility.

On the same AI topic, a cognitive progression can be structured as “perception → experience → understanding → analysis → creation → reflection.” For abstract concepts, we use card games to determine “right or wrong,” have children role‑play as “robots” to iteratively refine their actions, and then advance to discussions on data quality, algorithmic bias, and AI ethics. This is precisely the kind of learning pathway that future schools must establish when designing AI curricula.

Reimagining Assessment: From Scores to Growth

I spearheaded the creation of the “AI Student Growth Passport,” which, while safeguarding student privacy and respecting teachers’ professional judgment, systematically documents evidence of students’ academic progress, language proficiency, project outcomes, research skills, creativity, teamwork, leadership, social responsibility, and personal reflection. Each semester, students are guided to address three key questions—“Where am I now? How have I grown? Where do I want to go next?”—shifting assessment from merely “certifying test scores” to “helping students understand how they are growing.” AI does not seek to “define a child”; rather, it helps teachers and students visualize and track each student’s developmental trajectory.

Elevate a single educational field trip into a long-term platform.

I have upgraded Maoming Shuchuang’s educational‑research program from a simple “visit” to the Yinghua AI + PBL Innovation Lab, where students tackle real‑world challenges such as “How can AI support elderly community members?,” “How can data help reduce energy waste on campus?,” and “How can AI be used to tell compelling stories about Chinese culture?” They engage in a full‑cycle process that includes research, data collection, AI‑assisted analysis, design, prototyping, testing, and public presentation. Teachers serve as project mentors, while AI acts as both a research assistant and a thinking partner.

Ensuring the implementation of the strategy through teacher professional development.

I am fully aware that the success of a school’s AI strategy in enhancing learning hinges not on software procurement, but on teachers. Accordingly, we have established an in‑school “AI Teaching & Innovation Academy,” structured across three tiers: AI for Efficiency (streamlining lesson preparation and providing feedback), AI for Learning (enabling differentiated instruction and formative assessment), and AI for Transformation (redesigning curricula to empower students to engage in AI‑supported inquiry). We also employ small‑scale action research, using measures such as student engagement, learning outcomes, and evidence of growth to address the central question: What has changed in student learning as a result of AI?

Uphold clear ethical boundaries.

The more we embrace AI, the more we need to define clear boundaries—this is precisely the instinct that my legal background has instilled in me. I have established the principle of “Human First, AI Empowered,” which encompasses academic integrity, data privacy, age-appropriateness, intellectual property, information accuracy, algorithmic bias, and students’ physical and mental well-being. A guiding rule runs throughout: AI provides the insight; teachers make the educational judgment.

Professionalism means that, beyond passion, there are frameworks, evidence, pathways, and boundaries.