How Deep is Your Knowledge?

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  Title screen

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  Find all the sea creatures!

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  Daily Dive!

Inspiration

I was inspired by Gapminder, which I learned about as part of an assignment in my high school statistics class. The premise behind Gapminder is that many people think they know the world better than they actually do. However, due to their biases, they often end up scoring worse on a multiple-choice questionnaire with three choices than they would have by just guessing. I wanted to turn this into an actual game, where you play against a starfish that just guesses the answer to each question.

What it does

This game pits the player against random choice while answering 10 difficult multiple-choice questions about the world (like poverty rates, comparisons between 50 years ago and today, greenhouse gases, etc...) by introducing a starfish that guesses each question. Each time you get a question right, you descend deeper, representing your deeper knowledge. Furthermore, there are also different zones and creatures you can unlock by diving deeper, as well as a rank given after the quiz is over. At the end, there is also a link to a video that teaches people on how to be less ignorant about the world.

How I built it

I used the Gapminder question dataset (https://github.com/open-numbers/ddf--gapminder--ai_worldview_benchmark/blob/master/ddf--entities--question.csv) and filtered out any rows that had no questions using r, putting the cleaned dataset into a json file. After that I needed help from Claude to use typescript to sample 10 random questions from the dataset and a separate seed for a daily 10 questions that resets every day, as well as the progression and user interface. Claude also helped with creating the sea creatures using basic shapes and curved lines, along with color gradients.

Challenges we ran into

We had problems with designing the visuals (for the creatures especially) and the overall user interface since none of us had good experience with that field before.

Accomplishments that we're proud of

We are proud of the progression system we built and how the visuals ended up turning out, as well as the finished product that uses an actual dataset with real data and teaches the public about it in a fun way.

What we learned

We learned a lot about typescript since most of the project is in typescript. In terms of structure, we learned how to use real datasets for actual projects and how to introduce the public to information through an interactive interface.

What's next for How Deep is Your Knowledge?

Endless mode and global leaderboards are in the works :)

Built With

• framer
• node.js
• r
• tsx