coals: A Python repository from sparkslabs

A Dynamic Adaptive Learning System
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Overview:

This repository contains:

  * packages/
    - coals/
      - The core adaptive learning system codebase
      - a script `coals` - this loads the resources, and runs through the
        tutorial.  Note; this is a prototype to test the resources, edit
        flow, json serialisation and inference algorithms
      - This provides debian/ubuntu packaging
        - requires python3-stdeb and devscripts to be installed
      - Packaging is derived from python packaging so is suitable for
        pypi, launchpad, etc as well
      - Go to this directory and type "make"

    - ecs_core/
      - A simple ECS core - which is used to represent the resources and
        concepts in the system
      - This provides the JSON serialisation/deserialisation mechanism and
        opens the door to simplifications down the line.  This requirement
        for JSON serialisation is what is different from other ECS systems
      - The focus on using the JSON serialisable ECS means that alternative
        front ends can be written in other languages, while being able to
        interoperate on a data level.
      - Same packaging options as `coals`.

  * examples/
    - integration/
      - This contains a simple example of what a tutorial can look like.
      - concepts/ - contains some example concept files.
      - resources/ - in this example this is empty until populated from
                     one of:

        - resources_explicit/ - Contains resources with explicit fine
                   grained control of conceptual dependency constraints

        - resources_implicit/ - Contains resources with simple dependency
                   constraints based on resources not concepts.  However,
                   the conceptual dependencies are inferred.  Inferred
                   dependencies are never as good as the explicit ones, but
                   the conversion to conceptual dependencies mean the
                   dynamic behaviour still operates correctly.

    - content_flow/ - A snapshot of the resources from the resource flow. 
                   These show what "real" content looks like in the system

    - resource_edit_flow/ - An authoring workflow

      - WIP/ - place for editting files that are WIP.  Contains
               subdirectories - one per editor.  These allow editors
               to "claim" files while working remotely.

      - 0.tostart - Resources to start are in here
      - 1.question_outlines - Once the questions are written, they move here
      - 2.outline_answers - Once answers have been written they move here
      - 3.rearranged_answers - The answers get rearranged to something
             readable and moved here

      - 4.language_simplified - Once the language has been simplified they
             move here.  Once happy they can be copied into "resources/"
             (see below)

      - concepts/ - Completed concepts can be put here
      - resources/ - Completed resources can be put here
         - If there are resources/concepts in the last two directories,
           their behaviour can be tested by running `coals` in that
           directory.


  * build_core_tutorial.py - This is a script to generate the initial set of
    resources that were put into 0.tostart/.  This isn't strictly necessary,
    but includes the grid of resources to be written at the top by
    concepts/learning levels.
sparkslabs/coals
