Difference between revisions of "Teacher PD"
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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. | 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. | |
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| − | * Computational thinking | ||
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* Computational thinking skills for educators; best practices in teaching computational skills to students | * Computational thinking skills for educators; best practices in teaching computational skills to students | ||
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* Methods for data analysis | * Methods for data analysis | ||
| − | * Technologies for larger-scale computation | + | * Technologies for larger-scale computation |
| − | + | ** Clusters, including in-class | |
| − | + | ** Cluster parallel computing | |
| − | + | ** GPU parallel computing | |
* Large-scale simulation techniques | * Large-scale simulation techniques | ||
* Large-scale data analysis techniques | * Large-scale data analysis techniques | ||
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== Relevant links == | == Relevant links == | ||
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Revision as of 11:11, 7 July 2014
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