Inspiration
The lack of support from academic advisors and uncertainty about professor difficulty
What it does
Provides a smart scheduler with schedule difficulty based on professor and course data.
How we built it
Using scraped data from ratemyprofessor and kaggle datasets we integrated that into lovable and requested the schedule algorithm.
Challenges we ran into
Our data was old and we had to use smaller datasets with accurate data. We also were forced to only focus on the CSE major based on time constraints.
Accomplishments that we're proud of
It provides a good basis for a personalized schedule for CSE students.
What we learned
It takes a lot of time to make use of large datasets like professor ratings across a whole university.
What's next for OSU Smart Scheduler
If we could have access to the student evaluation reports that Ohio State does at the end of every semester that would greatly improve our smart advisor because it allows us to know what professors teach what courses and how good they are based on active student responses.
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