Attentive

Inspiration

I realized that there were still many issues surrounding remote learning and how well students could absorb information when they were watching lectures on Zoom. This form of learning makes engagement between students and teachers much more difficult and also makes it harder for the teacher to determine how effective the lesson or lecture really was. In general, I wanted to create a program that would provide teachers and users in general with the ability to see how well their service, lecture, or meeting was being received by the audience.

What it does

Attentive is able to use data that has already been collected in order to determine the mood of the person on the webcam and it is also able to locate the eyes of that person and determine if that person is paying attention to the video.

Challenges we ran into

The main challenges that we ran into were being able to have the program determine the mood of the person in real-time because OpenCv made it very difficult to be able to gauge the mood of the person being recorded in real-time.

Accomplishments that we're proud of

I was proud of being able to create a working product before the hacking period ended, and was able to create this program in a language that I wasn't that familiar in.

What's next for Attentive

I just need to expand Attentive, whether it be the amount of moods and emotions that will be recognized or be able to store the information that is collected so that teachers will have a better idea of how their ideas were received. In addition, I also plan on adding the ability to have activities the students can participate by interacting with the display.

Built With

• python
• xml