Skip to Content
📧 Join the Teacharium waitlist to get access. 
User DocumentationSee It BuiltLearning Inventory Part One

Create a Learning Inventory with Teacharium AI

Build a learning inventory — a survey-style lesson that assesses how learners prefer to learn, then visualizes their results. This walkthrough shows how to use AI to generate the questions, manage variables, and create a results screen.

Try the lesson

This lesson is best viewed on a desktop or tablet computer.

Try it full screen →

How this lesson is built

The inventory presents a series of “This or That” questions across several learning style categories. Each answer increments a category variable. At the end, a radar chart displays how the learner’s responses distribute across categories.

Lesson abstract and variables

The lesson abstract describes the inventory’s categories (visual, auditory, reading/writing, kinesthetic) and explains that each question maps to one of them. The AI uses this context to generate questions that are well-distributed across categories and to define the category variables.

Variables are created upfront — one per category — each starting at zero. Every question answer increments the matching category variable.

Generating questions with AI

The AI generates the full set of This or That questions based on the abstract. Each question presents two options representing different learning preferences. The AI assigns each option to a category and wires up the variable increment action automatically.

After generation, questions can be reordered, duplicated, or edited individually. AI commands like “duplicate the last 5 steps” make it easy to add more questions without rebuilding them.

This or That component

The This or That component presents two choices side by side. Each choice can trigger an action when selected — in this lesson, selecting a choice increments the corresponding category variable. The component supports auto-advance, so selecting an answer immediately moves to the next step without requiring a button click.

Results visualization

The final screen uses a radar chart widget (built in the companion video) that reads the category variables and renders a polygon showing the learner’s profile. The learner sees how their responses distribute across all categories at a glance.

For the results widget build, see Build a Custom Results Widget.