Intelligent Tutoring System (ITS) Agents
UALS includes a comprehensive Intelligent Tutoring System with 100 specialized AI agents that adapt to each student's learning style and progress. This page explains how to configure ITS agents for your class.
🧠 What Are ITS Agents?
ITS Agents are AI-powered tutoring assistants that work behind the scenes to personalize the learning experience for each student. They analyze student behavior, performance, and preferences to make intelligent recommendations.
When a student uses UALS, the ITS agents analyze their interactions and generate personalized recommendations. These recommendations influence content generation, hint timing, difficulty adjustment, and more.
Agent Categories
UALS includes 100 agents organized into categories:
| Category | Agents | Purpose |
|---|---|---|
| Knowledge Representation | 3 | Domain model, curriculum alignment, misconception detection |
| Learner Modeling | 4 | Student profiles, knowledge tracing, mastery estimation |
| Pedagogical Decision-Making | 9 | Teaching strategies, content sequencing, intervention timing |
| Tutoring Interaction | 5 | Dialogue, hints, scaffolding, feedback |
| Content Generation | 4 | Problems, examples, explanations, metacognitive support |
| Assessment & Analytics | 2 | Performance evaluation, learning data analysis |
| Extended Capabilities | 27 | Advanced learner support, social learning, multimodal |
| Micro-Behavior Monitoring | 43 | Detailed activity monitoring, pattern detection |
| Coordinator | 1 | Orchestrates all other agents |
📊 Analysis Levels
The ITS Analysis Level setting controls how many agents are involved in analyzing each student. Higher levels provide deeper personalization but require more processing time.
| Level | Name | Agents | Time | Use Case |
|---|---|---|---|---|
| 1 | Lightning | 4 | 1-2s | Large classes, basic personalization |
| 2 | Quick | 11 | 2-4s | Recommended for most classes |
| 3 | Standard | 20 | 4-8s | Content generation focus |
| 4 | Enhanced | 35 | 8-15s | Advanced pedagogical strategies |
| 5 | Professional | 50 | 12-18s | Multimodal & social intelligence |
| 6 | Research | 65 | 15-22s | Learning sciences research |
| 7 | Advanced | 80 | 18-28s | Domain-specific expertise |
| 8 | Enterprise | 90 | 22-32s | Longitudinal learning & AI ethics |
| 9 | Stakeholder | 95 | 24-35s | Multi-stakeholder intelligence |
| 10 | Complete | 100 | 25-40s | Full adaptive learning ecosystem |
Level 2 (Quick) is recommended for most classes. It provides good personalization with minimal wait time. Use higher levels for smaller classes or research contexts.
🎛️ ITS Agent Customizer
The ITS Agent Customizer allows you to fine-tune which agents are active and their behavior settings for your class.
Accessing the Customizer
- Open Class Management for your class
- Navigate to "ITS Agents" in the sidebar
- Click "Customize ITS Agents"
Available Settings
Analysis Level
Set the default analysis depth (1-10). Higher levels engage more agents for deeper personalization.
Agent Activation
Enable or disable specific agent categories based on your teaching needs and class size.
Behavior Tuning
Adjust individual agent parameters like hint frequency, intervention thresholds, and feedback styles.
AI Thinking Display
Control whether students can see the "Show AI Thinking" button that displays agent reasoning.
🔑 Key Agents Explained
Learner Model Agent
Builds and maintains a comprehensive profile of each student including:
- Prior knowledge and skill levels
- Learning pace and patterns
- Preferred content types
- Emotional and motivational states
Pedagogical Model Agent
Makes high-level teaching strategy decisions:
- When to introduce new concepts vs. reinforce existing ones
- Which teaching method suits the current learner state
- Optimal sequence of topics
- When to provide breaks or changes of pace
Socratic Tutoring Agent
Implements inquiry-based learning in the Socratic Playground:
- Generates probing questions
- Guides without giving direct answers
- Challenges assumptions
- Encourages self-discovery
Hint Generation Agent
Provides progressive hints during assessments:
- Determines when a hint is needed
- Chooses appropriate hint level (subtle to explicit)
- Tracks hint usage for analytics
- Adjusts based on student frustration level
Misconception Detection Agent
Identifies common student errors:
- Recognizes patterns in wrong answers
- Maps errors to known misconceptions
- Triggers targeted remediation
- Updates learner model with gap information
🔍 Explainable AI Feature
UALS includes a "Show AI Thinking" feature that provides transparency into how the ITS makes decisions.
How It Works
- Student completes the learner onboarding
- ITS agents analyze the student and generate recommendations
- "🧠 Show AI Thinking" button appears on results screen
- Clicking reveals a timeline of agent invocations and reasoning
Benefits
- Transparency: Students understand why content is personalized
- Trust: Seeing the reasoning builds confidence in the system
- Learning: Students gain metacognitive awareness
- Debugging: Teachers can verify recommendations make sense
📈 Impact on Learning Systems
The ITS recommendations directly influence all three learning systems:
Knowledge Explorer (KE)
- Novice learners get simpler concept maps
- Advanced learners get dense, interconnected networks
- Gaps trigger targeted expansion nodes
Socratic Playground (SPL)
- Socratic mode uses questioning techniques
- Novices get more detailed hints
- Frustration triggers encouragement and easier questions
SBCAT Assessments
- Diagnostic focus on knowledge gaps
- Difficulty calibrated to mastery level
- Sophisticated distractors for advanced students
⚡ Performance Considerations
| Operation | Time |
|---|---|
| Single agent invocation | 50-150ms |
| Parallel agent group (3 agents) | 150-250ms |
| Sequential workflow (5 steps) | 500-800ms |
| Complex workflow (10 steps) | 1000-1800ms |
For large classes (100+ students), consider using lower analysis levels (1-3) to minimize processing time. The system can handle 100+ concurrent learners per server with level 2 analysis.
Best Practices
- Start with Level 2 and adjust based on class feedback
- Enable the "Show AI Thinking" feature for transparency
- Monitor analytics to see if personalization improves outcomes
- Consider higher levels for struggling students who need more support
- Don't use Level 10 for large classes (processing time issues)
- Don't disable all agents (some personalization is always beneficial)
- Remember that agent recommendations are suggestions, not guarantees