artitudinale1 / JSskillstracker

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JS Radar

Join the chat at https://gitter.im/mcelearr/JSskillstracker

What

JS Radar is a curated repository of JS knowledge that guide users towards quality sources, enables individual users to track their progress and displays their progress through a radar chart.

Why

JS Radar is developed by learners for learners. It solves 2 big JS learner pains:

1. Where do I start?

New starters can be overwhelmed with content. JS Radar guides you through from the building blocks to more advanced topics by providing curated, quality content. There are a lot of free (and paid) coding tutorials, books, videos and more out there. JS Radar distills the best bits down and guides learners on a development path.

2. Where do I need to improve?

Are you comfortable with topic x but have a blind spot for topic y? By graphically showing you where you still need to improve, JS Radar pushes you towards unfamiliar ground that you need to master to become a JS ninja.

How

Users are provided with curated content for each subskill which they can use to learn about that topic. They then self-assess whether or not they think they have mastered it and use the content provided (or other content) to do so. The percentage completeness for any skill on the chart is based on the percentage of sub-skills that the user indicates are complete for that skill. Skills on the chart get progressively harder as you go clockwise but sub-skills do not have to be 'completed' in any particular order.

Contribute

JS Radar needs you to help find quality content, contribute to design and feel, and to write and review the code that powers it.

  • Check the issues to see if there is an issue you would like to help out with (or create your own if you have an idea!).
  • Assign yourself to the issue.
  • Create a new branch with a descriptive name.
  • Make your changes then create a pull request.
  • Wait for someone to review your work, give you feedback and merge your pull request.
  • Repeat.

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Languages

Language:JavaScript 95.0%Language:HTML 3.9%Language:CSS 1.0%