Inspiration
At a huge state school like PSU where class sizes of 100+ people are very common, it is almost impossible for professors to take all of the students feedback into consideration. Our goal with this hack is to give every professor a meaningful summary of all of their students SRTEs (Student Ratings of Teaching Effectiveness).
What it does
Our application takes in student reviews as input and generates a WordCloud consisting of the key words and phrases that occur most often to help the professor identify strengths and weaknesses in their teaching style. We have also passed the input to the IBM Watson's natural language processing API to gain the sentiment/emotion of the student's reviews.
How I built it
We used the Python Web Framework Flask to build our application. Our backend is built in Python and uses an open source WordCloud generator as well as IBM Watson's Natural Language Processing Library.
Challenges I ran into
Since our team's strength is in backend development our main struggle was in front end web development.
Accomplishments that I'm proud of
We were able to integrate multiple services and create a front end that would allow our user to interact with the data in real time.
What I learned
Various web technologies as well as the IBM Watson API.
What's next for ProfessorReviewSummarizer
A cleaner UI
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