I'm involved in a community service tutoring club at the University of Chicago called Phoenix Tutoring. We work with CPS students in the south-side Chicago community, and I've always found it really rewarding. Lately I've been trying to come up with a way to streamline our process with some technical infrastructure.

Plug-and-Play Tutoring - Instant set up of a community service tutoring program at any college campus. Tutoring programs require a level of technical infrastructure, in particular:

• A mechanism for enrolling students
• A mechanism for undergrads/grads to apply to be tutors
• A mechanism to match tutors and students, once enrolled and admitted
• A calendar to track when tutoring sessions will occur

A good technical infrastructure would also include certain ‘luxuries’, including:

• Automated reminder emails to tutors and tutees based on the calendar
• A mechanism to collect basic analytics: most in-demand subjects, times, etc.
• A mechanism to collect feedback
• A mechanism to re-match tutors and tutees, on a semester to semester basis, based on said feedback

The idea of Plug-and-Play Tutoring/TutorPages is to provide a black box that requires only basic, surface-level inputs from the users and abstracts away all technical complexity, providing features like this as well as room to grow more and build up new capabilities.

For our Treehacks project, we're building a website allowing the user to showcase all tutors and students in their program. We're also putting together a matching algorithm to match tutors to students optimally by distances between n-dimensional preference vectors.

Creating dynamically updated websites has been challenging, as we're fairly new to web development.

While we've run into some technical challenges, we're proud to be working on a project with the intent to make community service easier and more streamlined across the country. We're optimistic about our approach for a matching algorithm and we're proud to have a coherent, condensed project.

Though we haven't moved forward with implementing our website with it, we've learned a lot about the Reflex API. We've also learned a lot about github pages, which we will be using.

Though in the 36hr format of Treehacks we of course can't perfectly implement every niche detail of a product like TutorPages, in the future we'll be continuing to work on it. As we've planned it out there's an ever-growing depth - for example, one key element we'd like to add is log-in and private access for different members of the organization, tutors, parents, students, admin, etc.

Taking lists of lists of tutor and tutee information read in by text from our student enrollment/tutor application forms, we make Tutor and Tutee python objects. For a total offering of n subjects and k times, we provide helper functions to 1) take the distance formula on two n-dimensional vectors/points and 2) find overlaps out of lists of <= k times of availability. Using these helpers, we match every tutee to one tutor, with only tutors having the possibility of remaining unmatched. We do this as follows: after making sure the potential-match tutor and tutee are available at the same time, we optimize for similarity of subject preference vectors: tutors that are most comfortable tutoring a given subject are paired with students most in need of help with that subject. Finally, we produce Session objects from our matching dictionary, and store them. We should be left with a grouping of Session objects which can be queried for information about the tutor and tutee, the time, subjects being tutored, and so on.

• Tutor Signup form: https://bit.ly/tutorPagestutor
• Student Signup form: https://bit.ly/tutorPagesStudent

• Fork the repo
• Replace [email protected] in _config.yml with your email address. Refer to formspree for more information.
• Clone the repo onto your local machine
• Download the results of your tutor signup form and student signup form (see above), and replace the current tutorinfo.xlsx and studentinfo.xlsx forms in your local repo. Open and run the pipeline.py file from the pythonfiles folder on your local machine, and your pairings will appear!

If you haven't installed Conda yet, you can download and install Miniconda or Anaconda from the official website: Miniconda | Anaconda.

Open a terminal or command prompt and create a new virtual environment using Conda. Replace <env_name> with your desired environment name.

conda create --name <env_name> python=3.8

Activate the virtual environment:

• On Windows:

  conda activate <env_name>

• On macOS and Linux:

  source activate <env_name>

Navigate to the directory containing your requirements.txt file. Then, use pip to install the required packages:

pip install -r requirements.txt

Replace requirements.txt with the actual name of your requirements file if it's different.

To verify that the packages were installed correctly, you can check the list of installed packages in your virtual environment:

pip list

Once you're done working in the virtual environment, you can deactivate it:

conda deactivate

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