CSCE Capstone
Student Site for Individual and Collaborative Activites
![](https://capstone-csce.uark.edu/files/2020/11/new-1.png)
Let's Rethink the Online Classroom.
By creating an emotional and gesture tracking system, we can restore a small piece of human interaction by emulating how a real classroom would function. Creating a Chrome extension that can read in a student’s emotion or capture certain gestures in real time and relay that back to the teacher can provide a small sense of normalcy. Teachers can easily see who is interested, confused, or have left the class as naturally as they could if they were face-to-face. This will remove the awkward silences when a question is asked and can also help teachers learn how engaging they truly are in lecture.
![Ourteam Our Team.](https://capstone-csce.uark.edu/files/2020/11/Untitled_Artwork-3.png)
![0-2](https://capstone-csce.uark.edu/files/2020/11/0-2.jpg)
Allison Frye
B.S.C.S Class of Spring 2021
![Q9DUISje_400x400](https://capstone-csce.uark.edu/files/2020/11/Q9DUISje_400x400.jpg)
Caleb Duke
B.S.C.S Class of Spring 2021
![1584909519931](https://capstone-csce.uark.edu/files/2020/11/1584909519931.jpg)
Cassidy McManus
B.S.Cmp.E Class of Spring 2021
![0](https://capstone-csce.uark.edu/files/2020/11/0.jpg)
Ryan Rau
B.S.C.S Class of Spring 2021
![0-1](https://capstone-csce.uark.edu/files/2020/11/0-1.jpg)
Gage Robinson
B.S.Cmp.E Class of Spring 2021
![Untitled_Artwork](https://capstone-csce.uark.edu/files/2020/11/Untitled_Artwork-2.png)
Sprint 1 (11/7 - 1/11) - Preliminary Research ✓
- Iron out DB structure
- Determine best languages for backend
- Explore AWS Rekognition capabilities & limitations
- Explore other methods of training ML models for use in our app
- Look into limitations of browser extension
Sprint 2 (1/11 - 1/25) - Initial Setup ✓
- Get both our DB and base Backend set up on servers
- Set up AWS environment, ensuring team members have access
Sprint 3 (1/26 - 2/9) - Merge Components Together ✓
- Backend: Basic CRUD operations on DB, set up for connection to and from extension and AWS
- AWS: Set up Rekognition models, get ready for it to accept data from backend
- Browser Extension: Prepare for communication with backend, create background task for image handling, get access to user’s camera
Sprint 4 (2/10 - 2/24) - Merge Components Together ✓
- Link up extension to send and receive info from backend
- Link up backend to send and receive data from AWS
Sprint 5 (2/25 - 3/11) - Expand AI & Start Reporting Page ✓
- Begin expanding upong ML models, adding more emotions/ gestures
- Begin teacher reporting page
Sprint 6 (3/12 - 3/26) - Continue Expanding ML/ Reporting Page ✓
- Further expand upon ML models and reporting page
- Begin to look inot additional features
Sprint 7 (3/27 - 4/12) - Continue additional features ✓
- Continue with additional features
- General optimization & testing project wide
Sprint 8 (4/13 - 4/27) - Final Touches, Report, Optimization ✓
- Clean the project up, final touches, final report, etc…
Future Work
- Improve accuracy of data which would require more time and different types of people
- Would like to analyze live video streaming, but expensive
- Size/scalability (not really good with lots of people)
- A full statistics page for a student to evaluate their reactions
Contributions
- Caleb Duke
- Did all UI/UX for all services
- Assisted in developing the tiling system
- Assisted in AWS Rekognition research
- Allison Frye
- Developed starter code for Springboot application
- Developed chrome extension and pinned tab
- Cassidy McManus
- Developed multiple Springboot endpoints, specifically for classes, users, and rosters
- Ryan Rau
- Developed predective modeling for emotions
- Assisted in AWS Rekognition research
- Responsible for running all services on virtual machines
- Gage Robinson
- Developed multiple Springboot endpoints, specifically for lectures and emotions
Deliverables