- open source STEM learning app backed with neo4j (and vue / quasar)

The aim of (github) is to highlight the shortest paths to the greatest insights (i.e. optimizing access to 'ah-ha!' moments).

It ties a hierarchical STEM knowledge framework to the learning materials (images, videos, etc) that most effective teach them.

Going a step beyond 'simplistic' tagging of learning resources with related concepts, the 'tag' schema includes clustering synonyms and also supports translations. The tags are also nested hierarchically, (i.e. double-slit experiment-->quantum mechanics-->physics-->disciplines) in order that resources tagged with a highly specific term (ex 'double slit experiment') can be returned when querying for a related, more general term (ex 'physics').

It still very early in development, only basic functionality such as exploring tags and viewing resources is in place. Several features including interactive graph exploration (with vis.js) and resource discussions are being worked on.

Curious to hear any thoughts or constructive criticism.