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metadata
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