JDPLS Tutorial: Student Modeling

Student Modeling (BKT, DKT, AFM, PFA) lecture for the JDPLS program on March 6th, 2024.
Instructors: Prof. Tanja Käser, Vinitra Swamy from the ML4ED Lab

To prepare for the lecture, please read the student modeling research papers and refresh your python and Jupyter knowledge with the tutorial notebooks.

To make the lecture demonstration interactive, we'll run code on EPFL's interactive Jupyter Notebook cluster, Noto! Noto enables everyone to run python code in their browser, without needing an environment set up on your own machine. Here are the steps to get started with Noto.

Setup

If you're stuck somewhere, feel free to email Vinitra Swamy ([email protected]) and she will help you! Through the following steps, you will log in to Noto, copy the right files you need for the tutorial, and get started running code.

1. Go to the noto.epfl.ch website.
2. You will see a login screen with a big red button called Sign in with Tequila/SWITCHaai. Press this button.
3. You will come to a login screen with two options: If you are from EPFL or Use your Switch AAI Login (for students from ETH Zurich). If you are from EPFL (first image), sign in directly using your Tequila login. If you are from ETH (second image), select "ETH Zurich" from the dropdown menu and login with your campus credentials.
   
   
4. You will then see the following loading screen. Wait for less than a minute (usually) until your server spins up!
   
5. Now, you will be presented with a JupyterLab environment. Click on the git symbol (diamond with branches) on the left column.
   
6. Click on the "Clone a Repository" blue button (third one).
   
7. You will see a popup called "Clone a repo". In the space for a URL, copy-paste the following URL: https://github.com/epfl-ml4ed/jdpls-tutorial.git. Then click the "Clone" button.
   
8. Great! Now you've reached the step where you have all the files you need. Click on the jdpls-tutorial folder and the tutorial-preparation folder within that.
   
9. If it asks you to "Select Kernel", please select the Tensorflow Kernel from the dropdown menu. You can also select a kernel by clicking on the top right corner of the notebook.
   

You're all set! Run through the Tutorial1_1.ipynb notebooks and Tutorial1_2.ipynb notebooks to refresh your understanding of the Jupyter notebook environment and Python. The solution with all the example code is included in the Tutorial1_2_sol.ipynb notebook.

Updating new material

On the day of the lecture, you can complete the following steps to have all of the relevant material.

Once you have your repository set up as per steps 1 through 8 above, click on the git symbol in the left column. Then, click on the first cloud symbol on top! This should let you recieve new files that we've added for the lecture.