Digital tools for STEAM education and Makers pedagogy
student training
Online, September 2025 - March 2026

This long-term practical course will focus on the tools that are interesting to implement STEAM education, and will address the way to practically realize the activities of experimentation, analysis, understanding, modeling, simulation, and spreading.
It will include learning how to use Python, implementation of methods of numerical computation, use of computer-based simulation and visualization, and geometrical computation.
After introduction sessions, this course will be project-based, with practical tasks to be done by attendees on a voluntary basis, and presenters will act essentially as coaches and tutors.
Following the success of the November 2024 – May 2025 edition of the course, and given that this year’s students are different, the content will remain largely the same—although the course materials have since been updated, namely the examples of application.
Program

Follow this link to attend online sessions when scheduled.

Saturday 20, September - First steps with Python and Jupyter notebooks

Objective of this session is that attendees will :
  • be able to use Python and Jupyter notebooks on their computers (local installation or online setup),
  • be comfortable with the notebook user interface of Jupyter,
  • have a good idea of the bases of the Python language,
  • be prepared to read (namely) the introductive book :

Saturday 11, October - First steps with Python and Jupyter notebooks (cont'd)

Prerequisites of this session is that attendees are :
  • able to use Python and Jupyter notebooks on their computers - they have a working local installation or they now how to access an online setup like Collab or Capytale),
  • comfortable with the notebook user interface of Jupyter, and know how to manage files in the local Jupyter server or how to upload a file into an online server.
Objective of this session is that attendees will :
  • be able to basically use the Python language through Jupyter notebooks.
  • be motivated to read or continue reading the introductive book :

Saturday 15, November - Graphics computations using Matplotlib

Prerequisites of this session is that attendees are :
  • able to basically use the Python language through Jupyter notebooks on their own computer (local or online setup).
Objective of this session is that attendees will :
  • be able to use matplotlib library of Python to define and compute graphics results
  • consider developing a jupyter notebook to explore a research project requiring graphics computations.

Saturday 13, December - Simulation and graphics with Python - using Turtle Graphics

Objective of this session is that attendees will :
  • be able to use turtle graphics library of Python to draw graphics
  • consider developing a jupyter notebook to explore a research project requiring graphics computations.

Saturday 17, January 2026 - Randomness

Objective of this session is that attendees will :
  • understand how computers can mimic randomness
  • consider developing a jupyter notebook to explore a research project requiring randomness.

Saturday 31, January - Matrices

Objective of this session is that attendees will :
  • understand what are matrices as used by computers for numerical computations
  • be able to define and compute with matrices in Python, namely with the help of the numpy library
  • consider developing a jupyter notebook to explore a research project requiring matrices.

Saturday 14, March - Multi Agent simulation

Objective of this session is that attendees will :
  • get a good idea of what is multi-agent simulation
  • be able to define and compute some animation in Python, namely with the help of the Matplotlib library
  • consider developing a jupyter notebook to explore agents behaviours through multi-agent simulation.
More

Install Python and Jupyter locally

or alternatively

Course material

Jupyter notebooks are interactive documents.
Interact with Jupyter notebooks require accessing to a Jupyter notebooks server that can be locally installed (see above) or using an existing available server, as for example the Google Colab server.
Jupyter notebooks can be read online with nbviewer.

About the Course

  • A report (in french) from the Lycée Val de Durance attendees on the second session of the course.