https://github.com/hnarayanan/thinkbot-xblock
A collection of edX XBlock components for numerical simulations.
https://github.com/hnarayanan/thinkbot-xblock
educational fenics javascript mechanics python simulation
Last synced: 2 months ago
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A collection of edX XBlock components for numerical simulations.
- Host: GitHub
- URL: https://github.com/hnarayanan/thinkbot-xblock
- Owner: hnarayanan
- License: agpl-3.0
- Created: 2013-04-08T16:36:28.000Z (about 13 years ago)
- Default Branch: master
- Last Pushed: 2013-07-11T01:53:04.000Z (almost 13 years ago)
- Last Synced: 2025-01-30T22:19:27.072Z (over 1 year ago)
- Topics: educational, fenics, javascript, mechanics, python, simulation
- Language: Python
- Homepage: http://thinkbot.net/
- Size: 146 KB
- Stars: 3
- Watchers: 3
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.TXT
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README
XBlock components for numerical simulation
==========================================
Copyright (C) 2013 Harish Narayanan
This project is released under the GNU Affero General Public
License. Please read LICENSE.txt for the complete terms.
Background
----------
This project aims to create a collection of XBlocks that allow
students to carry out simulations in mathematical physics and
instructors to pose exercises within this context. It does this by
connecting to [thinkbot](http://thinkbot.net/), a computing service
which offers a selection of scientific computing software through a
[RESTful
API](https://en.wikipedia.org/wiki/Representational_state_transfer).
In particular, the project initially aims to build three kinds of
XBlock components:
1. A component that allows students to interact with the results of a
precomputed numerical solution. Such demonstrations are used to
motivate the theoretical material covered in classes.
2. A component that allows students to dynamically interact in simple
ways with a numerical simulation, such as changing parameters.
3. A component that presents students with interactive programming
exercises tied to computational science.

Installation
------------
1. Install the [XBlock component
architecture](https://github.com/edX/XBlock) project
2. Source the corresponding `venv`, if you installed it in a virtual
environment (which you should have!)
3. Install the thinkbot related Xblocks from this project's root
folder:
$ pip install -e thinkbot
4. Run the Django development server for the XBlock workbench:
$ python manage.py runserver
5. Open a web browser to: http://127.0.0.1:8000 and find a link to
the thinkbot XBlock
Contact info
------------
If you're interested in finding out more about how to use this project
in your own course or are interested in contributing to it, please
write to me:
Harish Narayanan