Apollo

Fall 2025. How can a physical + digital experience create a better learning experience using artificial intelligence? This was a collaborative project with two graphic design students and one other industrial design student.

We interviewed college students and young professionals who have to learn new skills at their job. This was done in order to understand how Al is used to learn, and any emotions that come the the process.

"I learn best when I can see what I'm supposed to do and then do it myself, either right after or as it's being explained"

"I want to still be in control, like 80% if I'm giving a number value. I don't like to use Al generally."

"Most models are generally yes men. If you tell it something is a problem, most of the times it'll agree with you and try to rationalize it after."

Learners run the risk of becoming over-reliant on Al systems, which may hinder development of independent problem solving skills.

Researching existing products that use new technologies helped us understand what already exists, and what technologies are advancing.

Physical User Flow
1. The user is working on their own and they run into a problem.
2. They turn on the AI device for guidance.
3. The AI device scans their environment and provides feedback via projection.
4. The learner turns the device off and resumes individual work.

Digital User Flow
1. The user wants to recap previous work and learn more.
2. They open the digital app on their computer and can view all previous work that was scanned.
3. The learner can interact with an AI language model that understands what they have been working on.
4. The user continues learning with the AI via quizzes, study guides, reviewing mistakes, etc.

The intial concepts were focused on ways to hide the camera, and understanding how this object would fit into a desk environment. Prototypes helped visualize how much space this object would take up on a desk.

This foldable desktop device was presented to Lenovo for feedback. It was clear that the form was too complicated and the cameras were too large.

The concept envolved to a modular set of three units, where the environment scanner unit could be removed and taken on the go.

The user is working and Apollo is turned off. When the user wants feedback on their work so they lift up the cameras.

When they press the power button, Apollo starts scanning work and tracking the user's eyes. Feedback is given by projecting on top of the user's work.

When on the go, the user can bring the environment scanner to keep Apollo up to date.

Any past work can be viewed later and expanded upon in the Apollo desktop app.