Teacher PD
This page will contain information for the Teacher PD course currently under development.
Purpose
This purpose of this PD course is to assist teachers in developing class materials which demonstrate the power and utility of scientific computing. The course content will be largely teacher-driven, with material presented on requested subjects in computing.
Possible topics
The goal of the course is to assist teachers in developing their own content. As such, the teachers themselves will determine the direction of the course. To get started, we list some possible topics below.
- Computational thinking, necessary for understanding a wide range of disciplines, as well as an useful skill set in its own right.
- Computational thinking skills for educators; best practices in teaching computational skills to students
- Existing simulation/data analysis tools that can be used in discipline-specific classes
- Basic Python programming
- Methods for simulation
- Methods for data analysis
- Technologies for larger-scale computation
- Clusters, including in-class
- Cluster parallel computing
- GPU parallel computing
- Large-scale simulation techniques
- Large-scale data analysis techniques
To express desire for a particular topic, or to suggest others, please email Erik Spence (ejspence at scinet.utoronto.ca).
Lecture slides
Python Script for Interactive Ball on Vibrating Plate
Requires pyprocessing and pyglet (pip install pyglet; pip install pyprocessing)
Modified BCCD image used in lecture 6
Python examples and data set for lecture 7.
Big Data Challenge
The Stem Fellowship Journal, SciNet, and other organizations, are sponsoring a high school Big Data Challenge. Please share with your students!
Read more on Research & Innovation @UofT
Interactive tools
- Shodor's interactivate tools
- Gigaphysics
- Math and physics applets
- PhET interactive simulations
- Excelets
Educator resources
- Shodor's MASTER Tools
- San Diego Supercomputer Center's TeacherTECH
- HPC University Resources for Computational Modeling
- NASA's educator resources
- Economic modelling resources
- Earthquake engineering resources
- Capitol University's computational science modules
- Quantitative Environmental Learning Project