Co-Creating a Chinese Vocabulary Game using ACP interactive generator and Claude Code for adding Data Analytics with Master Teacher XueHui

Co-Creating a Chinese Vocabulary Game with Master Teacher XueHui

This year, I had the opportunity to collaborate with Master Teacher XueHui, whom I first met at SNEF, to design an interactive Chinese vocabulary game together with data-driven learning analytics. The project started from a simple question: how might we make 词语学习 more engaging while also giving teachers meaningful insights into how students learn words such as “闯祸”“珍宝”“碎片”“愤怒”等? https://vle.learning.moe.edu.sg/my-drive/module/view/be0253ed-6cd4-419a-b5e0-fbf2bd27ba55/section/102315956/activity/102319748

From Conversation to Collaboration

I first met XueHui during a session at SNEF where we discussed how technology and data could strengthen Chinese language learning. Drawing on her experience working with many teachers and schools, she shared common vocabulary difficulties and misconceptions students often face.

After the session, we continued our conversation and decided to co-design a concrete learning resource that could demonstrate both strong pedagogy and meaningful analytics.

Designing the Interactive Vocabulary Experience

Together, we translated our ideas into an interactive activity within the VLE module “词语游戏”.

Students can choose between 学习模式、练习模式 and 测验模式, adjust 语速和音调, and toggle 拼音与声调颜色 to support differentiated learning needs.

Each vocabulary entry displays the character, pinyin, and a student-friendly explanation—for example:

闯祸：做错事，惹麻烦
珍宝：很珍贵的宝贝

This design allows students to connect meaning, sound, and usage within a single interactive environment.

Designing Questions for Learning Analytics

Once the interactive flow was stable, I focused on designing questions that would generate useful learning analytics, rather than simply recording scores.

For each key word, I created items that target different levels of understanding:

recognising the word
matching it with its meaning
applying it in a short contextual sentence

The system logs student actions, beginning with events such as:

“互动开始：学生进入学习界面 (t = 0s)”

From there, additional data points can be captured, including accuracy, response time, and number of attempts. Together, these metrics provide a clearer picture of how confidently students understand each word.

This allows teachers like XueHui to identify vocabulary that consistently causes hesitation—perhaps “不禁” or “怀疑”—and adapt instruction accordingly. For words students struggle with, we designed scaffolded questions that gradually increase in difficulty, allowing teachers to observe improvement across attempts.

Building the Analytics with Claude Code

To implement the data analytics component, I used Claude’s coding capabilities to help generate the event-logging structure behind the activity.

With Claude Code, I defined how each student interaction—entering the interface, viewing word lists, and attempting answers—would be captured in a timeline such as:

t = 0s 🎯 互动开始：学生进入学习界面

Using AI to assist with the coding significantly sped up the development process and helped ensure that the 学习分析 (learning analytics) layer integrated smoothly with the “词语学习 - Question with Data Analytics” activity.

Looking Ahead

Working with Master Teacher XueHui demonstrated how classroom expertise and thoughtful technology design can combine to create richer vocabulary learning experiences.

Our next step is to further develop the analytics dashboard so teachers can easily see patterns in student learning. By sharing these tools and approaches with more schools, we hope to support a broader shift toward data-informed 华文词语教学. Tools used are:

https://iwant2study.org/lookangejss/slsZipper/Code_to_ZIP_Converter/

https://iwant2study.org/lookangejss/appXapiIntegratorAgent/

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