Visit this link to try out our new interactive jeopardy game for New France between 1645 and 1745! This is a great way to review content at the end of class.
You can also use this template link to integrate the above game into your own Canva slide deck for whiteboard display or to assign to students individually.
The Creation Process
A custom Jeopardy game is a fantastic way to review concepts and promote classroom engagement. Here is how I generated the above product quickly using artificial intelligence (AI), in case you would like to make your own.
- Curate and Generate Questions: I uploaded copyright-free teaching materials into NotebookLM and generated a “Flashcard” set of questions and answers based on the specific content. I used NotebookLM to help ensure the AI was pulling from my teaching materials specifically, unlike other AI tools, which would be more likely to also comb through random sources on the web. NOTE: Always verify which AI tools have been approved for use by your specific educational institution before uploading materials. You could also do this step without AI, by writing the questions and answers yourself, or with students.
- Extract the Data: Since NotebookLM currently does not have an export button, I used the NotebookLM Exporter Chrome extension to download the questions generated as a CSV file.
- Build with Canva AI: I uploaded the CSV into the Canva AI Coding Tool and used several prompts to generate an accessible, bilingual (French/English) Jeopardy-style game board for content review. From there I saved the HTML to embed in the website, but I could have also inserted the game into a Canva presentation, etc.
- Generate a Prompt Template: After I was happy with the final generation, I copied my chat history from Canva AI and uploaded it into Gemini. I prompted Gemini to create a prompt template from the chat that someone could use to generate identical games on different topics. You can adjust this prompt, then copy and paste it into Canva AI to create your own custom games. Using template prompts can reduce the number of AI generations needed to reach the desired output, minimizing the ecological footprint.
