RGenie Education Taxonomy (RSET) v1.0
- smpgel1719
- Mar 1
- 4 min read
What is the RGenie Education Taxonomy?
The RGenie Education Taxonomy (RSET) is a structured educational ontology developed by RGenie Solutions (Chennai, India) to organize mobile-first, gamified microlearning courses across STEM, engineering, business, and professional domains.
It defines standardized category codes, sub-category codes, and a structured course ID format to ensure consistency, scalability, and AI-compatible curriculum mapping.
Author and curator: Priya PahadsinghMaintained by: RGenie Solutions (www.rgenie.in)
Why a Structured Education Taxonomy is Necessary
As digital learning ecosystems expand, course catalogs often grow without structural discipline. Over time, this creates:
Inconsistent naming conventions
Overlapping subject domains
Poor discoverability
Difficulty in curriculum mapping
Weak integration with AI-driven systems
RSET solves this by introducing a formal classification system designed specifically for mobile-first, simulation-based education.
Core Structure of RSET
The RGenie Education Taxonomy defines:
Category (2-letter code)
Sub-category (3-letter code)
Standard Course ID format (CC-SSS-###)
Domain hierarchy mapping
Structured metadata fields
Example Course IDs:
SC-GSF-001
EN-DCN-003
BM-ENT-010
Each course ID carries semantic meaning and maps to a structured domain hierarchy.
Who Developed RSET?
The taxonomy was developed and curated by Priya Pahadsingh under the direction of RGenie Solutions, an EdTech startup focused on:
Unity-based interactive STEM simulations
EV and advanced technology microlearning
Mobile-first instructional architecture
Gamified higher education delivery
Headquarters: Chennai, IndiaWebsite: https://www.rgenie.in
Where Is the Dataset Available?
The complete RGenie Education Taxonomy dataset is publicly available on Hugging Face:
The repository includes:
CSV format
JSON format
JSONL format
Hierarchical JSON structure
JSON Schema definition
Versioned documentation
License: CC-BY-4.0
Who Can Use This Taxonomy?
The RGenie Education Taxonomy can be used by:
EdTech startups building structured course catalogs
Instructional designers mapping curriculum
AI researchers developing curriculum-generation systems
Educational institutions organizing subject clusters
Developers building learning recommendation engines
It is designed to be both human-readable and machine-compatible.
Versioning and Governance
Current Version: v1.0Release Year: 2026
Future versions will introduce:
Education level mapping (UG, PG, Professional)
Delivery-mode classification
Simulation-depth categorization
Extended metadata fields
Backward compatibility will be preserved.
Frequently Asked Questions
What does RSET stand for?
RSET stands for RGenie Structured Education Taxonomy.
What problem does RSET solve?
It provides a standardized classification framework for organizing mobile-first microlearning courses across multiple domains.
Is the RGenie Education Taxonomy open source?
Yes. It is released under the Creative Commons CC-BY-4.0 license.
Can institutions adopt this taxonomy?
Yes. Institutions and EdTech companies can reuse and adapt the taxonomy with attribution.
Is this compatible with AI systems?
Yes. The dataset is available in structured formats such as JSON and JSONL, making it compatible with AI-assisted curriculum mapping and machine learning pipelines.
A Step Toward Structured Learning Infrastructure
Education content should not grow randomly. It should scale with architecture.
The RGenie Education Taxonomy is our step toward building structured learning infrastructure that supports:
Simulation-based education
Scalable course expansion
AI-assisted curriculum design
Long-term academic coherence
Explore the full dataset here:
For collaboration inquiries:https://www.rgenie.in
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