Understanding Variables & Analytics

Variables are the building blocks of tracking and measuring learning in CoursePipelines. Think of them as containers that store important information about your learners' progress and experiences.

What Are Variables?

Variables capture and store different types of information in your courses and chatbots. Examples include:

• Quiz scores
• Course completion status
• Time spent learning
• Correct answers on questions
• Chatbot interaction data

Where Do Variables Come From?

Variables can be collected from two main sources:

Course Variables

These track what happens within your courses, such as:

• Quiz scores
• Completion rates
• Time spent on pages
• Question responses
• Module progress

Agent Variables

These track interactions with your Custom AI Agents, such as:

• Conversation State: last_intent, current_topic
• Learner Input: feedback_rating, confidence_score
• Agent Actions: resources_suggested, escalation_needed

Agent variables allow you to personalize the agent's behavior and track the effectiveness of AI interactions.

System Variables

Types of Variables

Variables come in different formats to store different kinds of information:

Numbers

Perfect for scores, percentages, and counts.

• Examples: quiz_score = 85, completion_rate = 70, module_progress = 4
• Important for AI Evaluation: When using AI Evaluation actions with dual outputs, connect the score output to number-type variables

Text (Strings)

Good for categories, names, or responses.

• Examples: learning_status = "completed", favorite_topic = "JavaScript", feedback = "Need more examples"
• Important for AI Evaluation: When using AI Evaluation actions with dual outputs, connect the feedback output to string-type variables

Yes/No (Boolean)

Simple true/false information.

• Examples: module_passed = true, certification_earned = false, prerequisite_met = true

Time

Measures durations in seconds.

• Examples: video_watched = 320 (seconds), course_time = 4500 (seconds)

Type Safety in Pipelines

When connecting action outputs to course variables in pipelines:

• Score outputs from AI Evaluation actions must connect to number variables
• Feedback outputs from AI Evaluation actions must connect to string variables
• The pipeline editor will help ensure you make the correct connections

Viewing and Analyzing Variables

Once your variables are collecting data, you have several ways to understand what they're telling you:

1. Detailed Reports

Variable reports show you:

• Basic statistics (average, highest, lowest scores)
• Individual learner values
• Visual comparisons
• Export options for further analysis

To view reports:

1. Go to the Variables section
2. Click on a variable name
3. Select "View Report"

2. Charts and Graphs

For visual learners, charts make data easier to understand:

• Bar charts for numerical data (like scores)
• Pie charts for categories (like responses)
• Interactive tooltips show details when you hover

To view charts:

1. Go to the Variables section
2. Click on a variable
3. Select "View Chart"

3. Leaderboards

For numerical variables, leaderboards show:

• Top performers with medal icons (🥇, 🥈, 🥉)
• Rankings for all learners
• Score formats based on the variable type

For text variables, they show:

• Most common responses
• How many learners gave each response
• Percentage breakdowns

To view leaderboards:

1. Go to the Variables section
2. Click on a variable
3. Select "View Leaderboard"

Sharing Variable Data

You can easily share variable information with others:

Embedding in Other Systems

Add any variable view to your own website or learning platform:

<iframe
  src="https://coursepipelines.com/variables/your-variable-id/chart"
  width="100%"
  height="600px"
  frameborder="0"
></iframe>

Just replace "your-variable-id" with your actual variable ID.

Tips for Using Variables Effectively

1. Clear Naming

• Use descriptive names that explain what the variable tracks
• For example, use "quiz1_score" instead of just "score"
• Be consistent in your naming style across all variables

2. Organization

• Group related variables together
• Use the same type of variable for similar information
• Archive old variables instead of deleting them to keep your history

3. Regular Review

• Check your variable data often to spot trends
• Use different visualization types for different insights
• Export data for deeper analysis when needed

Getting Started with Variables

1. Go to the Variables section of your dashboard
2. Click "Create Variable"
3. Fill in:
   • Display Name (what humans see)
   • Technical Name (for the system)
   • Variable Type (Number, Text, Yes/No, Time)
   • Description (what it measures)
4. Click "Save"
5. Connect your variable to courses or chatbots through Pipelines

Ready to start tracking learning progress? Create your first variable now