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ETL Learning System

A comprehensive note-taking and knowledge management system designed for left handed graduate students, particularly those with ADHD. Based on the Extract-Transform-Load (ETL) data pipeline metaphor.

Philosophy

This system addresses common challenges in graduate education:

  • Information overload during lectures and readings
  • Scattered notes that are never reviewed
  • Decision paralysis about where to write things
  • Inconsistency in note-taking methods
  • Poor retention of material, important dates, and tasks

Solution: A streamlined, three-stage workflow that separates capture from processing, minimizes decisions, and creates both physical and digital reference materials.


System Overview

EXTRACT (Capture)          TRANSFORM (Process)        LOAD (Store)
───────────────────        ───────────────────        ───────────────────
Raw notebook          →    Weekly sessions       →    Refined notes
- Chronological            • 60-90 minutes            • Cornell method
- Minimal structure        • Format decisions         • Jupyter notebooks
- Zero friction            • Refinement               • Knowledge base

The Three Stages

1. EXTRACT (During the Week)

  • Capture everything in one A5 notebook chronologically
  • Use simple symbols: • □ ? * > !
  • Date header format: [DATE] | [TYPE] | [SOURCE]
  • No organization, no decisions - just write

2. TRANSFORM (Sunday/Monday)

  • 60-90 minute weekly processing session
  • Scan raw notes, mark pages with sticky tabs
  • Decide: Code-heavy? → Jupyter. Conceptual? → Cornell.
  • Process notes using templates

3. LOAD (Storage)

  • Physical: B5 Cornell notebook for concepts/theory
  • Digital: Jupyter notebooks for code/examples
  • Knowledge base: Markdown docs with course summaries

Quick Start

Prerequisites

  • One notebook (raw capture) A5 preferred
  • One notebook (refined notes) B5 preferred
  • One nice pen
  • GitHub account
  • Jupyter installed (pip install jupyter)

Setup Steps

  1. Clone this repository:
   git clone https://github.com/[username]/etl-learning-system.git
  1. Copy templates to your learning repo:
   cp -r templates/ ~/your-learning-repo/
  1. Read the guides:

  2. Print the weekly checklist:


Repository Structure

etl-learning-system/
├── templates/
│   ├── notebook/
│   │   └── notebook_template.ipynb          # Jupyter notebook template
│   ├── physical/
│   │   ├── cornell_template.md              # Cornell method guide
│   │   └── raw_capture_symbols.md           # Symbol reference
│   └── checklists/
│       ├── weekly_processing.md             # Weekly routine checklist
│       └── setup_checklist.md               # Initial setup checklist
├── guides/
│   ├── WORKFLOW.md                          # Complete workflow guide
│   ├── PHYSICAL_NOTES.md          
93FE
          # Raw capture & Cornell method
│   ├── DIGITAL_NOTES.md                     # Jupyter notebook guide
│   ├── KNOWLEDGE_BASE.md                    # Docs structure guide
│   ├── GIT_WORKFLOW.md                      # Version control guide
│   ├── ADHD_STRATEGIES.md                   # ADHD-specific tips
│   ├── WHY_THIS_WORKS.md                    # Support for this learning concept
│   └── VISUAL_DIAGRAMS.md                   # Pictures help brain understand
├── examples/
│   ├── sample_raw_notes.jpg                 # Photo of raw capture
│   ├── sample_cornell_notes.jpg             # Photo of Cornell notes
│   ├── sample_notebook.ipynb                # Example Jupyter notebook
│   └── sample_knowledge_base/               # Example docs structure
└── assets/
    ├── workflow_diagram.png                 # Visual workflow
    └── decision_tree.png                    # Format decision tree

Who This Is For

  • Graduate students managing multiple courses
  • People with ADHD who struggle with organization
  • Anyone overwhelmed by scattered notes
  • Students who want to retain more information
  • Technical students who need both code and concept notes

Key Features

For ADHD Brains

  • Single capture point - one funnel, no decisions about "which notebook"
  • Simple symbols - consistent, intuitive, minimal choices
  • Chronological only - no complex categorization
  • Processing ritual - structured weekly session
  • Visual completion - cross out processed pages/sections

For Learning

  • Writing by hand - better retention during capture
  • Spaced repetition - weekly processing reinforces learning
  • Multiple formats - concepts in Cornell, code in Jupyter
  • Knowledge base - searchable reference for future use
  • Version control - track your learning development over time

For Technical Content

  • Jupyter templates - structured code documentation
  • Git integration - professional portfolio building
  • Markdown docs - cross-referenced knowledge base
  • Tool references - quick lookup for Docker, Git, etc.

Documentation

Guides

Templates


Customization

This system is designed to be adapted. Common modifications:

Symbols: Adjust the symbol set to meet your needs +|- Timing: Process on different days if Sunday/Monday doesn't work Tools: Use VS Code instead of Jupyter, Obsidian instead of markdown Scope: Start with just school notes, expand to other life areas later


Contributing

Have improvements or adaptations? Contributions welcome!

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/improvement)
  3. Commit your changes
  4. Push and create a Pull Request

License

MIT License - feel free to use and adapt for your own learning journey.


Acknowledgments

This system combines proven note-taking methods:

  • Cornell Method (Walter Pauk, 1940s)
  • Bullet Journal (Ryder Carroll, 2013) - simplified symbols
  • ETL Pipeline (Data engineering metaphor)
  • Zettelkasten principles (Niklas Luhmann)

Designed specifically for graduate students with ADHD, tested in a Data Science Masters program.


Questions?

Open an issue or start a discussion. Happy to help you adapt this system!


"The best note-taking system is the one you'll actually use."

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My constantly evolving note-taking strategy for learning with ADHD

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