Python with matplotlib as a module-development technology leveraging existing graduate research skills¶

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Description¶

Python is an interpreted language typically used for desktop applications or server-side scripting rather than browser-run web applications. The article notes "the advantage for module authors is that many graduate students are already familiar with Python and its associated scientific data analysis and visualization modules (numpy, and matplotlib) from their research experience." Matplotlib visualizations can be made animated and interactive via an object-oriented interface adding buttons, switches, and sliders.

Design Implications¶

Context¶

Requirements¶

• Users must download and run the software on their computers and have the Python framework already installed, unless modules are hosted on web-ready MOOC platforms.

Constraints¶

• A stated disadvantage is that it "requires users to download and manually run software on their computers."

Target Learners¶

• graduate students authoring modules
• upper-level undergraduate and graduate students using modules

Target Learning Goals¶

• simulation of astrophysical processes
• radio spectra interpretation

Claims¶

Related Elements¶

• JavaScript with the d3.js library as a web-native module-development technology
• Wolfram Computable Document Format as a module-development technology
• WorldWide Telescope as a module-development technology requiring the least technical experience

Examples¶

• Instructor recommendations for running a module-development course project

Key Sources¶

• Nathan E. Sanders, Chris Faesi, Alyssa A. Goodman. (2013). A New Approach to Developing Interactive Software Modules through Graduate Education. https://arxiv.org/abs/1308.1908