README.md

---
language: en
license: apache-2.0
tags:
  - text-classification
  - education
  - taxonomy
  - blooms-taxonomy
  - learning-objectives
datasets:
  - custom
metrics:
  - accuracy
  - f1
widget:
  - text: "Students will recall the basic principles of thermodynamics"
    example_title: "Remember Example"
  - text: "Learners will explain the difference between mitosis and meiosis"
    example_title: "Understand Example"
  - text: "Apply Newton's laws to solve motion problems"
    example_title: "Apply Example"
  - text: "Analyze the causes and effects of climate change"
    example_title: "Analyze Example"
  - text: "Evaluate the effectiveness of different teaching methodologies"
    example_title: "Evaluate Example"
  - text: "Design and implement a database management system"
    example_title: "Create Example"
pipeline_tag: text-classification
---

# Bloom's Taxonomy Classifier

## Model Description

This model classifies educational learning objectives according to **Bloom's Taxonomy** (revised version), which categorizes cognitive processes into six progressive levels of complexity.

### Taxonomy Levels

- **Level 0: Remember** - Recall facts and basic concepts
- **Level 1: Understand** - Explain ideas or concepts
- **Level 2: Apply** - Use information in new situations
- **Level 3: Analyze** - Draw connections among ideas
- **Level 4: Evaluate** - Justify decisions or positions
- **Level 5: Create** - Produce new or original work

## Model Details

- **Model Type**: BERT-based sequence classification
- **Base Model**: `bert-base-uncased`
- **Fine-tuned on**: Custom dataset of educational learning objectives
- **Language**: English
- **License**: Apache 2.0

## Training Data

- **Dataset Size**: Educational learning objectives across multiple domains
- **Domains**: STEM, Humanities, Social Sciences, Professional Skills
- **Balance**: Stratified across all six taxonomy levels

## Usage