As we all are students, we sometime find it difficult to focus in the class and miss the instructions and bonus points given by the professors to paying attention and answering questions. we wanted the class to be more engaging.
What it does
Our application is for keeping students on task during lecture. At the start of class, the professor fills out a form with the class name, a phrase, and the number of times times they are going to say the phrase. A code is generated or manually inputted. Students log into the app by scanning the code. Once logged in, it is their responsibility to keep track of the amounts of times the professor says the key word. Students press the button whenever they hear the word. At the end of class, students receive a score based on how engaged they were. If students leave the app, the current score will turn into the final store.
How we built it
We built an IOS app for the students and a web app for professors to set up the class code and see the analytics. We used Firebase as our live database.
Challenges we ran into
There was a lack of documentation in the AWS Transcribe API as well the Rekognition API. We realized a few hours in that major features in AWS Transcribe API were missing. It wasn't supported for IOS development.
Accomplishments that we're proud of
We made unique product in 24 hours. We learned how to use machine learning API's from AWS.
What we learned
What's next for Helm
We wanted to implement it with AWS Transcribe to track how many times the professor says he words in real time but AWS Transcribe do not support this functionality at this moment. We would like to implement it in future with better analytics features.