I am working on a research project about adaptive educational games and thought of making one to learn about "machine learning".

The purpose is to supplement classroom lectures, while the goal is to enhance the ability of students to remember and explain basic concepts, and apply them in new situations.

Being a mystery fan, and given it is a popular theme for games, I am thinking of various plots and mechanics for my game.

Here is what I have till now:

Game objective (could be one or more of these): treasure hunt, escape the building, find a missing person, catch the culprit.

Game world: people, places, items.

Mechanics: visit places, meet people, search/inspect items, find clues, progress in the game.

Now I am stuck at imagining how to embed machine learning content in the game.

Any ideas would be helpful!

Note: This is my first post here. If this thread is not appropriate for such discussion, please guide me to an appropriate resource.

Kind Regards

Perhaps you should examine the “machine learning” goal in more detail and reason back to the game?

Machine learning is a broad topic, so likely you should make some selection in sub-topics of it you want your users to learn. Try to order the sub-topics in some way.

Then, try to make that more concrete. What do you expect the user to to learn about each single sub-topic? At the technical side, what must eventually happen to get “the” answer? what input of that is be supplied by you / the game, and what input is done by the user in order to learn?

Finally, what must the game supply to enable the user to collect or create that input?