After The AP

Data Science Challenge

Presented by:

AP Stats & AP CompSci teachers: Do you have 1-2 weeks of class time after the AP Exam? If so, utilize this free project to extend your students’ learning using real data, state of the art tools, and advanced models. Using modern data science skills, your students will tackle the following challenge -

Challenge: Predict which colleges “pay off” the most

With college costs rising, debt is top of mind for many students. Using big data from the Dept of Ed, students build their own models to evaluate the best and worst colleges for conquering student debt. Then, they’ll make predictions about the schools they may soon be attending!

What will students learn?

  • A gentle introduction to coding in the open-source R language (popular in academia and industry)

  • Skills for working with real, raw data

  • Modern statistical modeling techniques, including multiple regression and machine learning

Competition (Optional): The top student models nationwide - in terms of accuracy in predicting student loan default rates - will be recognized as winners of the National Data Science Challenge (a great achievement to include on college or work applications)! Submitting to the competition is optional. See the end of Notebook 4 for details. Submission deadline: June 7, 2024.

What teachers and students NEED:

  • Knowledge from completing a full-year course in ONE of the following: AP Stats, AP CompSci A, or AP CompSci Principles. We provide supplemental materials for learning the coding and for learning the stats.

  • 1-2 weeks of class time after the AP Exam

  • Internet access and computers, laptops, or Chromebooks (all materials are run online, no software needed)

What teachers and students do NOT NEED:

  • Prior exposure to coding, as long as they have some background in statistics (e.g. AP Stats)

  • Prior exposure to stats, as long as they have some background in coding (e.g. either AP CompSci course)

  • Special software or computing power. We provide everything online, free of charge!

  • Money - everything is free to access.

Teachers: Getting Started

Timeline:

  • April 19, 2024: Deadline for teachers to register for challenge (see Step 1 below). Note: Registering is not a commitment to using the challenge.

    • After registering, teachers can explore the project materials (see Steps 2-3 below). Try to complete these steps >1 week before using the project with students.

  • May 6, 2024: First day that teachers can start using challenge with students (see Step 4 below). Start dates can be later, but no students can start the project before May 6th.

  • June 7, 2024: Submission deadline for optional student competition.

Lottery notice (if necessary): We've received a lot of demand for the data science challenge. Our goal is to accommodate every classroom, and we're working around the clock to update our server capacity to make it happen. However, if demand grows too large, we'll use a random lottery to determine the classrooms that will be cleared to use the challenge with students. In the event that a lottery becomes necessary, results would be shared April 22nd.

Note: The class registration deadline for the 2024 challenge (April 19, 2024) has passed, but teachers can still explore the materials themselves.

The deadline to register for the 2024 challenge has passed. However, teachers can still use the materials (without sharing with students) to explore the content themselves and plan for the 2025 challenge. Simply follow Steps 2-3 below to get teacher access and check out the project yourself!

Step 1: Teacher Registration (complete by April 19, 2024)

Step 2: Access the Canvas Course (try to complete >1 week prior to starting project with students)

  • We are using the free version of the Canvas learning management system to house all the project resources and code. To simplify things, teachers will access the Canvas course in a similar way to their students. In addition, the teacher interface on Canvas will be identical to the student interface. Use the following steps to join as a teacher:

  • Navigate to canvas.instructure.com/register and click I’m a student.

    • Note: Even though you’re the teacher, you’re still going to click “I’m a student.”

    • Note: If your school already uses Canvas, you should still complete this step. Often, campuses use a version of Canvas that’s specific to their school/district. However, for this project, you’ll be using the free general version of Canvas. So, you may have to register for a new account on the general Canvas using a private browser window.

    • Note: Please make sure to remember your username. When logging in, sometimes Canvas will ask for your email, but it actually wants your username. Remembering your username will help you get back into the course.

  • Enter the teacher join code: MDPRTL

  • Enter the rest of your information. Please use the same email as the one you provided in the Google Form from Step 1.

  • Click “Start Learning”

  • Begin exploring the Canvas course. Then, watch the walkthrough video to learn the key features of using the Canvas and code notebooks.

Step 3: Explore the Teacher Resources (try to complete >1 week prior to starting project with students)

  • Utilize the following teacher resources to help you run the challenge:

Flarum Support Forum (teachers only —> no students)

Coding questions? Trouble accessing Canvas? Did you find a typo? To get in contact or get support, join our free Flarum forum. It’s an online platform where you can reach out, ask questions, report typos, and search through already resolved issues. When creating your account, use invite code: datasciencerules. Please do not invite your students.

Step 4: Launch project with students (May 6th or later)

All registered teachers (or, in the event of a lottery, all lottery winners) will receive an email shortly before May 6th with instructions for registering students. Classes are welcome to start the challenge after May 6th, but no students may start the challenge before that date. Plan for the challenge to take 1-2 weeks of class time. Note: Students submissions to the optional prediction competition are due June 7, 2024.