Interactive learning material

Generating Interactive Learning Content with AI

Learning goals, activities and meaningful feedback

Author: Zsolt LengyeliTStudy Hungary Training and Research Centre
Reviewer: Mária HartyányiiTStudy Hungary Training and Research Centre

Symbols representing flashcards, matching, simulation, dialogue and a self-check list. — Choose the interaction format to match the learning goal.

Learning objective

Learners learn more when they do something with the content: answer, decide, sort, try, get feedback and try again.

This material introduces ways in which AI can help teachers design quizzes, branching scenarios, interactive worksheets, self-check exercises, dialogue-based tasks, simulations and practice activities.

By the end of this material, you will be able to

Match interaction types to learning goals.
Use AI to generate interactive content with meaningful feedback.
Test and revise content for correctness, usability, accessibility and data protection.

Introduction

Designing meaningful interaction

Interactive materials used to take a long time to produce: teachers had to write good questions, plausible distractors, answer keys and helpful feedback. Creating a digital activity often also required programming skills.

Generative AI changes both parts. A language model can draft dozens of questions with feedback in minutes, and an AI tool that writes code can turn the content into a working web page or an import file for a learning platform.

01

Learning objective

What should learners know or be able to do by the end?

02

Activity

What do they need to decide, sort, try or explain?

03

Feedback

How will they understand the result and the next step?

Types of interactive learning activities

Which interaction fits the learning goal?

Choose the interaction type according to what you expect learners to be able to do.

01

Recall and understanding

Quizzes, flashcards, matching or fill-in-the-gap worksheets.

Learners recognise and explain the basic concepts.

02

Procedures

Ordering or drag-and-drop tasks.

Example: put the steps of a brake check in the correct order.

03

Decisions and problem solving

A branching scenario or a fault-diagnosis case.

Learners weigh up options and their consequences.

04

Communication

A dialogue-based task in which AI plays a customer, colleague or supervisor.

Learners practise expressing themselves in a professional situation.

05

Understanding relationships

A simple simulation with one adjustable parameter.

Learners observe, for example, the relationship between voltage, resistance and current.

06

Reflection and self-assessment

A self-check list and short reflective questions with model answers.

Learners review their own work and identify ways to move forward.

The thinking behind questions and answers

Quizzes with meaningful feedback

Quizzes are the easiest interactive element to generate, and they are easy to generate badly. Feedback supports learning when it explains why an answer is right or wrong and what to do next.

Ask explicitly for distractors based on typical misconceptions, and explanatory feedback for every option. A distractor is a plausible but incorrect answer that can reveal what the learner misunderstands.

A quiz showing correct and incorrect answers, explanatory feedback and a score indicator. — Explanatory feedback and a final score support formative self-assessment.

Example prompt for a quiz with feedback

“Create 8 multiple-choice questions for first-year electrician apprentices on protective earthing, based only on the attached textbook chapter. Each question has 4 options. The wrong options should reflect typical learner misconceptions. For every option, write one sentence of feedback explaining why it is correct or incorrect. Mark the difficulty (easy/medium/hard). Output in Moodle GIFT format.”

The output format

From draft questions to working learning content

Content can be imported into a learning platform or turned into a stand-alone web page by an AI tool that writes code. Choose the format according to the target platform and the feedback you need.

01

Moodle import

GIFT can include feedback for individual answers to multiple-choice questions. Aiken can be used for simpler multiple-choice questions.

GIFT documentation · Aiken documentation

02

Quiz tools

Some quiz tools import questions from CSV files. Always match the columns and format to the import template of the tool you use.

03

Stand-alone web page

An AI tool that writes code can turn text into a working quiz, with question-by-question evaluation, explanations and a final score.

Professional decisions and consequences

Branching scenarios

A branching scenario presents a realistic situation and asks the learner to choose. Each choice leads to a different consequence and to further decisions.

It is well suited to situations that require professional judgement: handling a customer complaint, diagnosing a fault or responding to a safety incident.

Teacher review: the “best” path must be professionally correct, and the consequences must be realistic.

A branching decision tree with good, acceptable and problematic outcomes along different paths. — Each decision leads to a different consequence and a new decision point.

Example prompt for a decision tree

“Write a branching scenario with three decision points for a hairdressing apprentice whose client is unhappy with a colour result. Give three options per decision, the consequence of each, and feedback that refers to professional communication and customer service standards.”

AI as a practice partner

Dialogue-based tasks

With a well-written instruction, a chatbot can act as a practice partner: a customer who asks questions, a supervisor who expects a report or a patient who describes symptoms.

Some platforms allow the instruction to be saved as a custom assistant, for example a custom GPT. Learners can then practise repeatedly under the school’s rules.

Role
Who should AI play: a customer, colleague or supervisor?
Situation
What has happened, and what does the learner need to achieve?
Difficulty
How complex should the situation be for the learner’s level?
Ending
When should the dialogue end?
Feedback
Which criteria should AI use to evaluate the learner’s responses?
Repetition
How can the activity be reused under the school’s rules?

Understanding relationships

Simulations: change and observe!

A slider that changes a value, a calculator for a workshop formula or a virtual control panel can all become learning activities. The teacher describes the desired behaviour in plain language, then tests the result.

Try this example

How does the current change?

We are exploring a simple resistance model, with 12 V applied throughout. Change the resistance and observe the current.

Resistance (Ω)

You can also use the left and right arrow keys to move the slider.

20 Ω → 0.60 A

Ohm’s law in this model: I = U / R. As resistance increases at a constant voltage, current decreases.

What does the interaction add?

Learners change one parameter and immediately observe its effect. The task could ask: “What happens to the current if we double the resistance?”

AI tools that write and run code can create this behaviour. The source material gives ChatGPT, Claude Artifacts and agents such as Codex as examples.

Test the model: the formula, units, boundary values and displayed results must all be correct.

Before it reaches the classroom

Build, test, revise

AI-generated interactive content must be tested before classroom use. A working button and an attractive interface do not, on their own, prove that the learning content is correct.

The process: build with AI → test with learners → observe → revise. To support revision, describe precisely where and why difficulties occurred.

A teacher and AI create an activity, learners try it, then observation and revision follow. — Build with AI, test with learners, observe and revise.

Five review criteria

Knowledge check

Check what you have learnt!

Answer all five questions. The evaluation gives an explanation and a suggested next step for each answer you select.

1Which interaction is best suited to practising the steps of a procedure? Flashcards presenting random concepts. Putting the steps in the correct order. A purely decorative animation.

2Which feedback best supports learning? Only: “Incorrect.” Only the final score. It explains why an answer is right or wrong and suggests a next step.

3What should a teacher check in a branching scenario? That the best path is professionally correct and the consequences are realistic. Only that there are as many branches as possible. Only that the colours and images look attractive.

4A tool requires learner logins and stores results. What should you do? Use it immediately, because every learning tool is automatically suitable. Check its data handling and compliance with the GDPR and the school’s rules. Check only how quickly it calculates scores.

5Which approach supports accessibility? Activities that can only be operated with a mouse. Very short time limits for every task. Readable text, sufficient contrast, image descriptions and keyboard operation.

Takeaways

Takeaways for teachers

Start from the learning goal and choose an interaction type that fits it.
Ask for misconception-based distractors and explanatory feedback for every option.
Use branching scenarios and dialogue-based tasks to practise professional decisions and communication.
Thoroughly test any quiz or simulation created with an AI tool that writes code.
Check correctness, usability, accessibility and data protection; pilot with learners and revise.

References and further sources

Learning and feedback

Hattie, J. & Timperley, H. (2007): The Power of Feedback. Review of Educational Research, 77(1), 81–112.
Clark, R. C. & Mayer, R. E. (2016): e-Learning and the Science of Instruction. 4th ed., Wiley.

Tools and formats

Moodle Docs: GIFT format.
H5P documentation and interactive content.
VITA project: interactive learning modules.

Training background material

Lengyel, Zs. (2026): Concrete applications for content generation. VITA training presentation.

On the next page, you can download PDF versions of the complete English source material and the practical task.

Contributors and attachments

Credits and copyright

Author: Zsolt LengyeliTStudy Hungary Training and Research Centre
Reviewer: Mária HartyányiiTStudy Hungary Training and Research Centre
Project: 2025-1-LT01-KA220-VET-000362456

Attachments

Download the English source materialM4-T1-MLC4-TEXT-EN.pdf Download the practical taskM4-T1-MLC4-EXC-EN.pdf

This work may be reused and adapted under the terms of the Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0).

Funded by the European Union. Views and opinions expressed are those of the author(s) only and do not necessarily reflect those of the European Union or the National Agency.

By the end of this material, you will be able to

Learning objective

Activity

Feedback

Recall and understanding

Procedures

Decisions and problem solving

Communication

Understanding relationships

Reflection and self-assessment

Moodle import

Quiz tools

Stand-alone web page

Role

Situation

Difficulty

Ending

Feedback

Repetition

How does the current change?

What does the interaction add?

Five review criteria

Learning and feedback

Tools and formats

Training background material

Attachments