Adapt|OER

Flask-Admin based web application that serves as an dashboard for e-learning content produced with the Adapt Authoring Tool. The Adapt Authoring Tool integrates with MongoDB to store and manage learning materials, in different layers: courses, articles, blocks and components (interactive and presentative). The Authoring Tool only gives you an overview of courses, not their contents, which makes it hard to reuse them for Open Educational Resources (OERs) or any other format. Below is a breakdown of its architecture, design patterns, and dependencies.

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Architecture Overview

Tech Stack

• Backend: Flask (Python) for API and server-side rendering
• Database: MongoDB (via PyMongo)
• Admin Panel: Flask-Admin for managing SCORM content
• Frontend: Flask templates (Jinja2)
• Authentication: Flask-Login for user management (assumes User is authenticated in Adapt Authoring Tool)
• Internationalization: Flask-Babel for multilingual support
• SCORM Integration: SCORM-compatible learning modules
• Forms & Validation: Flask-WTF and WTForms
• File Handling: Handles ZIP files for packaging quizzes and learning content

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Key Components and Responsibilities

Application Core (app.py)

• Initializes the Flask app
• Configures database connection (MongoDB)
• Sets up authentication (Flask-Login)
• Defines routes for user authentication, course content, and quiz generation
• Serves as the entry point

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Authentication & User Management

• Uses Flask-Login to authenticate a single admin user.
• @login_required decorator ensures restricted access to the admin panel.
• Session handling is done via Flask’s built-in session mechanism.

Key methods:

• login() → Handles login requests and verifies credentials
• logout() → Logs out the user
• load_user() → Retrieves authenticated user from session

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Admin Panel (Flask-Admin)

• Provides a dashboard for managing courses, content objects, questions, and media.
• Uses ModelView subclasses to manage MongoDB collections.

Admin Views:

• CourseView → Manages e-learning courses
• ContentsView → Handles learning content and taxonomy
• QuestionView → Manages quizzes and assessments
• PresentationView → Handles text-based learning components
• GraphicView → Manages image-based content
• GlossaryView → Stores glossary terms and definitions

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SCORM Integration

• Uses pipwerks.SCORM to track progress and completion within the LMS.
• Learning content is managed in MongoDB, where:
  • contentobjects store course units
  • blocks store sections within units
  • components store questions, media, and text elements

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Content Filtering & Organization

• filter_components_and_blocks() extracts and groups components into learning blocks.
• get_related_content_index() finds related content items in a course.
• fetch_and_nest_content() recursively structures content hierarchies.

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Quiz & Assessment Handling

• Supports dynamic quiz generation using prepare_quizzes() and compose_quiz().
• Uses Flask routes to generate, bundle, and deliver quizzes as SCORM packages.
• Uses transpile_bson.py to convert MongoDB BSON data into JSON-compatible format.

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Dependencies

Library	Purpose
Flask	Web framework
Flask-Login	User authentication
Flask-Admin	Admin dashboard
Flask-WTF	Form handling
Flask-Babel	i18n support
PyMongo	MongoDB integration
WTForms	Form validation
ZipFile	ZIP file handling
Requests	HTTP requests
BeautifulSoup	HTML parsing for glossary and text processing
Werkzeug	File security utilities

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Key Features

✅ SCORM-Ready: Generates SCORM-compatible packages for LMS integration.
✅ User Authentication: Admin-only access using Flask-Login.
✅ MongoDB-Based CMS: Stores, manages, and retrieves learning content.
✅ Dynamic Quiz Generation: Filters, modifies, and bundles quizzes as ZIP files.
✅ Multi-Language Support: Flask-Babel for translations.
✅ Admin Panel: Manages courses, components, and glossary.

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Summary

This project is a SCORM-compatible e-learning content manager that integrates MongoDB, Flask-Admin, and Flask-Login to provide an admin dashboard for managing quizzes, courses, and media assets. It follows best practices in design patterns to ensure scalability, modularity, and efficiency.