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Step 5: Concept Taxonomy

Overview

This taxonomy organizes the 500 concepts into 10 balanced categories to facilitate navigation, color-coded graph visualization, and curriculum planning. The categories are the same 10 groupings used when the concept list was generated (see Concept Enumeration), now formalized with short TaxonomyID codes for use in the dependency CSV and JSON graph. No category exceeds 30% of the total — see the full per-category concept listing and balance analysis in the Taxonomy Distribution Report.

Taxonomy Categories

TaxonomyID Category Name Description Actual %
FOUND Foundational Concepts Core electrical theory: voltage, current, resistance, power, circuit topology, units, and safety — the vocabulary every later topic depends on 19.0%
PASV Passive Components Resistors, capacitors, diodes, LEDs, and potentiometers — components that don't switch or amplify on their own 15.0%
ACTV Active Components & ICs Transistors (BC547/2N2222), the 555 timer IC, and the 74HC595 shift register, including pin-level detail 12.6%
BRDG Breadboarding & Assembly Hands-on skills for wiring a solderless breadboard, troubleshooting, and the optional perfboard/solder packaging step 11.6%
INPT Input Components Switches, buttons, wired AND/OR switch logic, and light sensing (photoresistor, dark detector) 8.0%
OUTP Output Components LEDs, RGB color mixing, LED strips, motors, and buzzers — anything a circuit uses to produce an effect 8.0%
PWR Power Systems Batteries, USB power, voltage regulators, buck converters, the XR2206 signal generator, and solar cells 8.0%
MEAS Measurement & Testing Using a multimeter and systematic troubleshooting procedures 7.6%
DLOG Digital Logic & Boolean Boolean reasoning and building AND/OR/NOT/NAND/NOR/XOR gates from transistors, plus a simple RS latch 6.0%
CAPS Advanced Circuits & Capstone Projects Timing/memory circuits and named real-world projects (busy board, solar night light, LED noodle), culminating in capstone planning 4.2%

Design Notes

  • Category order doubles as a dependency safeguard. Every concept's dependencies were required to reference only concept IDs lower than its own ID (IDs 1-500 were assigned in this same category order). This guarantees the dependency graph is a valid DAG by construction — no separate cycle-repair pass was needed, and analyze-graph.py confirmed zero cycles and zero self-dependencies (see Graph Quality Analysis).
  • Category order is a concept-knowledge order, not a strict lesson-teaching order. For example, Output Components (LEDs, motors) are ID-numbered after Active Components (transistors) because some output-driving concepts genuinely need transistor knowledge — but individual concepts like "Light Emitting Diode" still resolve to a shallow position in the actual dependency graph (few, foundational prerequisites), so the graph-viewer's computed levels — not the raw category order — are what determine pedagogical sequencing for chapter planning.
  • taxonomy-names.json maps each TaxonomyID to its human-readable name for the graph viewer legend, and color-config.json assigns each a distinct named CSS color from the recommended palette (see learning-graph.json).

Full concept listings for each category are in Concept Enumeration (by topic) and Taxonomy Distribution Report (by taxonomy, with balance analysis).