Inspiration

Throughout our school careers, participation has always been a very big part of student-engagement, learning and the grading process. However, it is hard for teachers to calculate how much a student participated and remember exactly what they said to analyze this properly. We wanted to create an audio-based tool that automatically records students and tally's up the number of times they spoke automatically and records their response for future use. This way, the teacher can automatically see how much each student participated instead of having to remember hours or days after the discussion. We would use some form of data analysis to calculate a score for each student, which would allow the teacher to personalize their teaching methods

What it does

This audio-based tool that automatically records students and tally's up the number of times they spoke automatically and records their response for future use. By using the keyword "Ok Hound", the audio detection turns on, records the student's name and their response. It puts this into a database that the teacher can access at any time and even repeat the audio. It also has a tally and a visual representation of the frequency of student responses.

How I built it

We built the mainframe using android studio, houndify and firebase. At first, we were planning to use react-native, node.js and express but we ran into many issues with the framework and connecting the houndify to the react-native platform. Instead, we decided to use android studio because we are more familiar with java and the structure of the framework.

Challenges I ran into

We ran into many challenges when implementing our database, with most problems arising from library version issues when connecting android studio with Firebase, while maintaining Houndify functionality. We lacked the experience necessary to address such problems, but successfully built both modules, one for speech functionality, and the other for connecting to Firebase. Due to our struggle to connect the application to the database, we could not implement our original plans for advanced data analysis for participation quality.

What's next for Particip8

We want to keep developing particip8 in the future by connecting it to the firebase successfully and using more specific audio-detection. We need to construct the data analysis portion, in which instructors can download a spreadsheet of all the data. We also want to update the UI to make it more user friendly.

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