Poll Anywhere
Full Stack Project of a classroom response system, developed for the Tufts Electrical and Computer Engineering Department and endorsed by Tufts Professor, Dr. Steven Bell.
Uses Machine-Learning (k-means) to dynamically determine the optimum number of required clusters and allocate each student response to the respectivec cluster.
Poll Anywhere
Technical Overview
- Frontend: ReactJS, NextJS, Typescript, HTML/CSS, Bootstrap UI, Node
- Backend: Python, Beanie, FastAPI, MongoDB, Cloudinary, Auth0 (user authentication)
- Tools: React Hooks, Scikit Learn, GitHub
User Functionality
Product is a responsive web application that users can access across multiple devices and viewports. Initially, users are required to login/signup using a Google account verified through Auth0 and JSWebToken. Next, the user lands on the dashboard and is able to view courses that they are a student in, as well as courses that they themselves instruct. Users are able to create courses, and join already existing courses through the course code.
User Functionality: Student
When opening a specific course, the student is taken to the question landing page where any live questions to be responded are rendered. If not question is live, then the student does not have to do anything. Questions currently supported are multiple-choice and free-response, though we are currently working on Drawing Questions and Ranking-order questions.
User Functionality: Instructor
After a course is created, instrucor is able to add lectures (set of questions for a given day). Within a lecture, instructor is able to add questions, view clustered-responses and response information, manage rosters, track participation statistics and manage course settings.
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