M2M Learning Systems

Overview

M2M Learning Systems is a portfolio repository for structured homework, mock-exam, review, and knowledge-graph workflows. The public repository focuses on architecture, sanitized examples, and learning-system design rather than private coursework content. It avoids professor materials, private assignment text, graded solutions, and restricted academic data.

Why It Matters

Technical learning systems are strongest when they convert scattered coursework into a reviewable process: assignments, concept mapping, weak-point tracking, mock exams, and feedback loops. M2M demonstrates workflow design, structured data, dashboard architecture, and academic-integrity boundaries.

Core Features

• Homework and mock-exam workflow architecture
• Knowledge graph concept model
• Review queue and weak-point tracker
• Sanitized sample study plan
• Dashboard/portal design notes
• Academic-integrity publication policy

Architecture

graph TD
  A[Course Concepts] --> B[Knowledge Graph]
  B --> C[Practice Queue]
  C --> D[Mock Exam]
  D --> E[Review Loop]
  E --> B

Loading

m2m-learning-systems/
  docs/
    architecture.md
    study_workflow.md
    academic_integrity.md
  src/m2m/
    graph.py
    review.py
    schedule.py
  examples/
    sample_study_plan.md
  workflows/
    mock_exam_cycle.md

Tech Stack

• Python
• Streamlit-style portal architecture
• Markdown documentation
• Structured review workflows
• Graph and scheduling concepts

Review Docs

• Knowledge graph specification
• Architecture
• Study workflow
• Academic integrity

Quickstart

git clone https://github.com/shawsignaldev/m2m-learning-systems.git
cd m2m-learning-systems
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
pip install -e .
python examples/demo_review.py

Windows:

git clone https://github.com/shawsignaldev/m2m-learning-systems.git
cd m2m-learning-systems
python -m venv .venv
.venv\Scripts\activate
pip install -r requirements.txt
pip install -e .
python examples\demo_review.py

Example Output

Metric	Example
Concepts tracked	4
Review priority	networks
Mock exam status	scheduled

Project Status

Version 0.1 learning-systems release with concept graph primitives, review queue helpers, cycle scheduling, workflow docs, examples, and tests.

Academic Integrity

This repository should include only original summaries, sanitized examples, and personally authored tooling. Do not publish professor materials, private coursework instructions, graded solutions, or restricted datasets.