Smart Classroom

Currently, we have an optimized chat that allows certain messages to be upvoted as a visual signal for teachers to answer important questions and gauge class understanding for certain concepts, which, after collecting data from teachers, would be very useful.

Inspiration

As students ourselves, we have begun to notice a huge problem in online education around the idea of a closed classroom. In normal online classes, these days, students are usually muted while listening to the teacher talk through problems, lectures, etc.. Oftentimes, many students openly ask questions in a physical classroom, but don't feel this same openness in an online setting, stifling understanding. Those who do ask questions usually do so in the chat of Zoom or Google Meets. However, unlike a physical classroom, these messages get crowded out and oftentimes, a teacher misses out on a crucial question. Read further to see Smart Classroom's novel approach to these problems.

Technologies Used

To develop our product for this hackathon, we used Flask, a Python web development framework, to create the backend for the chat app and the login system. Flask was a main tool. We also used HTML and Javascript to integrate the chat app with the login system.

Challenges

At first, we had to decide and prioritize what features we were going to create in the timeframe. To solve this, we talked about immediate problems with the current education system. In terms of technical issues, there were a few. A notable one was when you click on the different upvote buttons, the same one iterator in the first bubble is updated, not a new one for the poll upvotes. However, we were able to work around this by storing the previous iterator in another variable and manipulating the Flask messages to reset the counter.

Accomplishments

We were successfully able to create a chat app, a login system with database analysis that separates student views from teacher views, create an upvote feature, and a successful poll feature.

Our Future Plans

Due to time constraint, we could only do only so much. However, we have many future plans. An example is integrating natural language processing or NLP. We have a working NLP model that detects the teacher's voice. All we have to do is integrate it with the chat to create an efficient process of automatically creating polls for understanding and more. Others include gaining more traction from teachers to see what features they would like, making it into an app to distribute to colleges that optimize the in class experience better.

At the end of the day, Smart Classroom is the first step to a more effective online classroom approach that allows for an optimal understanding of content for students.

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