Docs / Instructional Philosophies / Competency-Based

Competency-Based Instruction

Skills-focused learning through measurable competencies. Learners progress by demonstrating mastery at each proficiency level.

Definition

Competency-Based Instruction (CBI) organizes learning around measurable skills and abilities. Learners progress by demonstrating mastery of specific competencies, regardless of time spent. The focus is on what learners can do, not what they have covered.

Central Question "What can the learner do?"

Core Principles

🎯

Mastery-Focused

Learners advance by demonstrating skill proficiency. No moving on until mastery is achieved.

⏱️

Learner-Paced

Time is variable, mastery is constant. Some learn faster, others take more time.

🏆

Performance-Based Assessment

Real-world application of skills. Demonstrate ability, don't just recall facts.

📋

Explicit Outcomes

Clear, measurable competency definitions. Everyone knows what success looks like.

Structure in UALS

Competency-based content is organized in a three-level hierarchy with proficiency levels:

Competency Category (e.g., AI Literacy)
├── Domain-Specific Competency 1
│ ├── Level 1: Acquire (Foundational)
│ ├── Level 2: Deepen (Intermediate)
│ └── Level 3: Create (Advanced)
└── Domain-Specific Competency 2
├── Level 1: Acquire
├── Level 2: Deepen
└── Level 3: Create

Example: AI Literacy DSC

AI Literacy
├── AI Capabilities in Language Learning
│ ├── Acquire: Recognizes what AI does well and poorly
│ ├── Deepen: Evaluates AI performance across language tasks
│ └── Create: Develops guidelines for optimal AI tool selection
└── Ethical AI Use
├── Acquire: Identifies basic ethical concerns
├── Deepen: Analyzes ethical implications in scenarios
└── Create: Designs ethical frameworks for AI deployment

Proficiency Levels Explained

The three proficiency levels align with Bloom's Taxonomy, progressing from lower-order to higher-order thinking skills:

1/3
Acquire
Foundational knowledge and recognition
Remember, Understand
2/3
Deepen
Analysis, application, and evaluation
Apply, Analyze
3/3
Create
Synthesis, innovation, and creation
Evaluate, Create
Bloom's Taxonomy Alignment These levels map to cognitive domains: Acquire covers Remember and Understand; Deepen covers Apply and Analyze; Create covers Evaluate and Create.

Data Format

When making API requests for competency-based content, use this format:

JSON 
{
  "module": "KE",                              // KE, SPL, or SBCAT
  "competency_category": "AI Literacy",
  "domain_specific_competency": "AI Capabilities in Language Learning",
  "proficiency_level": "2/3",                  // 1/3, 2/3, or 3/3
  "meta_category": "STEM",
  "field_of_study": "Education Technology"
}

DSC File Structure

Teacher's personal DSC files are stored in GCS with this format:

JSON 
{
  "framework": {
    "title": "AI Literacy",
    "competencies": [
      {
        "id": 1,
        "name": "AI Capabilities in Language Learning",
        "description": "Understanding what AI can and cannot do",
        "levels": {
          "acquire": "Recognizes what AI does well and poorly",
          "deepen": "Evaluates AI performance across language tasks",
          "create": "Develops guidelines for optimal AI tool selection"
        },
        "aiNotes": {
          "acquire": "Focus on practical, everyday examples",
          "deepen": "Include comparison scenarios between AI tools",
          "create": "Emphasize ethical considerations"
        }
      }
    ]
  }
}

Key Characteristics

Aspect Competency-Based Approach
Learning Path Flexible, mastery-driven
Progress Measure Demonstrated proficiency
Terminology Competencies, Skills, Proficiency Levels
Success Criteria Mastery of defined competencies
Pacing Individual, self-paced
Assessment Performance demonstrations
Framework ID Pattern dsc-comp-{name}

Learning Systems in Competency Mode

All three learning systems adapt their content for competency-based instruction:

🗺️

Knowledge Explorer (KE)

Purpose: Deep exploration of competencies

Example: Exploring "AI Capabilities" with skill maps showing what AI can do well vs. poorly across different domains.

💬

Socratic Playground (SPL)

Purpose: Interactive skill practice

Example: Guided practice applying AI evaluation skills through Socratic questioning and scenarios.

📝

Scenario-Based CAT (SBCAT)

Purpose: Adaptive competency assessment

Example: Assessing proficiency across AI literacy competencies with real-world scenario questions.

Per-Competency Tracking SBCAT tracks performance for each competency separately, allowing targeted remediation and granular progress reporting. See the Continuous Assessment documentation.

When to Use Competency-Based

💼 Professional development focused on skill acquisition
🏢 Workforce training with specific job competencies
🎯 Personalized learning allowing self-paced progression
🔧 Skill-gap remediation targeting specific weaknesses
🏅 Micro-credentials and digital badges for verified skills
🛠️ Project-based learning emphasizing real-world application

Practical Examples

  • AI Literacy professional development for educators
  • Software development bootcamp skills
  • Healthcare practitioner clinical skills training
  • Leadership and management competency development
  • Technical certification programs (AWS, Google Cloud, etc.)

Adoption & Customization

There are multiple ways to adopt competency-based instruction in UALS:

📋

Use Existing DSC

Browse the DSC catalog and copy an existing competency framework to your personal collection. Ideal for standard competency domains.

Quick Start
✏️

Customize a Template

Copy an existing DSC, then modify competencies, proficiency levels, and AI notes to match your specific needs.

Recommended
🆕

Create from Scratch

Build a completely new competency framework with your own competencies and levels. Full control over all content.

Create Framework

Customization Options

Option Description When to Use
AI Notes (Per Level) Custom instructions for each proficiency level (acquire, deepen, create) Differentiate content difficulty and focus by level
Competency Description Detailed description of what the competency covers Clarify scope and expectations for learners
Scenario Context Class-level context applied to all assessments Ground scenarios in specific professional context
Proficiency Definitions Custom text for acquire/deepen/create levels Tailor mastery criteria to your domain

AI Notes (Per Proficiency Level)

Add custom instructions for each level to differentiate content generation:

JSON 
{
  "name": "AI Capabilities in Language Learning",
  "aiNotes": {
    "acquire": "Use simple, everyday examples. Focus on recognition and identification.",
    "deepen": "Include comparison scenarios between AI tools. Require analysis and evaluation.",
    "create": "Challenge with novel, open-ended situations. Require synthesis and design."
  }
}

Scenario Context (Class-Level)

Ground all competency assessments in relevant real-world situations:

JSON 
{
  "classId": "ai-literacy-teachers-2024",
  "scenarioContext": "K-12 language arts teachers exploring AI tools for classroom use"
}

Complete DSC Example

Here's a complete competency framework structure:

JSON 
{
  "framework": {
    "id": "dsc-comp-ai-literacy",
    "title": "AI Literacy for Educators",
    "description": "Essential competencies for educators using AI in teaching",
    "competencies": [
      {
        "id": 1,
        "name": "AI Capabilities in Language Learning",
        "description": "Understanding what AI can and cannot do effectively",
        "levels": {
          "acquire": "Recognizes basic AI capabilities and limitations",
          "deepen": "Evaluates AI performance across different tasks",
          "create": "Develops guidelines for optimal AI tool selection"
        },
        "aiNotes": {
          "acquire": "Focus on practical, everyday examples",
          "deepen": "Include comparison scenarios",
          "create": "Emphasize ethical considerations"
        }
      },
      {
        "id": 2,
        "name": "Ethical AI Use",
        "description": "Applying ethical principles when using AI tools",
        "levels": {
          "acquire": "Identifies basic ethical concerns with AI",
          "deepen": "Analyzes ethical implications in scenarios",
          "create": "Designs ethical frameworks for AI deployment"
        }
      }
    ]
  }
}
Want to create your own competency framework? See the Create Your Own Framework guide for step-by-step instructions.

UALS Competency-Based Instruction Documentation

For additional help, visit the Teacher Dashboard