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Given a roster of students generates a semester long cold call list that ensures that students are picked randomly and fairly.

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The Cold Call List

Given a roster of students, generates a semester long cold call list that ensures that students are picked randomly and fairly.

Inspired after a day in class where a student was cold-called in sequential classes – and as a bid to procrastinate on building outlines for my administrative, antitrust, and constitutional law final exams – I created "The Cold Call List," which painlessly generates a semester long cold-call list that is designed to do the following:

  • Students are picked randomly and fairly for cold-calls
  • Enforce a minimum number of cold-calls to other students before a given student is eligible to be cold called again
  • Ensures that all students are cold-called the same number of times in a semester

Great! How Can I Use It?

Currently, you need a slight amount of technical know-how and have Python, numpy and pandas installed on your computer. If you're missing the packages run pip install -r requirements.txt in your terminal.

Then: 0. Have a csv with one column called Names and unique names for each student in that column

  1. Open list_gen.py
  2. Edit pd.read_csv('your/csv/goes/here')
  3. Edit n the number of times you want to cycle through your roster this semester
  4. Edit m the minimum number of cold calls to other students before a given student is eligible to be cold called again
  5. Run list_gen.py and it will write your new cold call list

That is not very user friendly to non-technical people

Yeah, sorry about that. My roadmap is as follows to improve.

Roadmap

  • GUI to handle user input
    • Maybe run as a ipynb file in the meantime?
  • More robust roster info
    • Handle .xslx files
    • Handle files where student names are split across a first name and last name column
  • Package the program so it runs self contained?

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Given a roster of students generates a semester long cold call list that ensures that students are picked randomly and fairly.

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