sTutor

For the students by the students.

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Inspiration

The best way to learn is to teach, but teaching someone sure feels dreadful. We are here to help you get over this fear. How about discussing a difficult topic with your own classmates? You learn, your classmates learn and its a win win for both parties. That does not look so terrible now..!! does it? Every uni student goes to college and attends the lectures but how do we know that they understood everything that has been taught in a lecture ? A civil engineer undergraduate who has just shifted their career to computer science will surely not understand an operating systems lecture perfectly. He needs HELP ! who is he going to ask for it ? Yes ! you guessed it ! No, not the TA. They have "office hours". So here we are sTutor.

What it does

sTutor is an efficient application for any undergraduate/graduate students. In most of the scenarios, a student don't get chance to ask doubts to the professor because they have not understood a concept/chapter/lecture. It is easier to ask doubts to your peers than a professor and as we said best way to lean is to teach.

After a user successfully logs in they will be presented with two option:

  • To host a new group study session

  • To join an existing session that matches their topic of interest

To become a tutor the user will be providing parameters like subject, topic, duration, place, max-attendees, discussion material. In a similar way the user who looks for a session can enter their information, and can choose from the list that he thinks is the best match!

How we built it

  • Started by firing up Mongo Db Atlas and creating cluster instance with Google Cloud Platform.
  • We love JavaScript and here comes MERN stack.
  • Then some schema drawings on the white board.
  • A little bit of data here and some data there.
  • Express.js now comes to the rescue. Routing URLs like 90s ISD calls.
  • We were all exhausted and you can feel that in our bootstrapped UI.
  • Analytics is in our DNA, hence no matter what, we managed to cook up a WordCloud using Jupyter Notebook and Python with NLP.

Challenges we ran into

  • Planning a schema in around 3 hours without normalization is really a mess.
  • Organizational problems.

Accomplishments that we're proud of

  • We have created a functional website in a limited amount of time. AND IT WORKS!
  • Everyone tried new APIs and tools for the first time on the project.

What we learned

  • Problems can be solved with ease during planning phase, but require a lot of work after 50% of the development is completed.

What's next for sTutor

  • Develop a sTutor as fully fledged web application.
  • Make the database more robust.
  • Enhance the UI design, and add more functionality to the website.
  • Reach to a number of students using the system, so that we have traction for conducting analysis.
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