Using AI to Create Post-Course Feedback Forms

Edit Content

Using AI to Create Post-Course Feedback Forms

Introduction

After each course, most educators and training providers do collect feedback from learners.

However, not everyone is able to actually make effective use of that feedback.

Feedback forms are often too long, so learners respond superficially.

Questions are too general, making the results difficult to analyze.

In the end, the collected data is often used only as “reference material,” rather than as a basis for real improvement.

In recent years, many organizations have started using AI to design and process feedback forms.

This is not about “following trends” or “appearing modern,” but about solving a long-standing problem:

👉 How can we ask the right questions, understand feedback faster, and improve courses more effectively?

This article takes a neutral and practical look at how AI is being used to create post-course feedback forms, including its advantages, limitations, and real-world applications for online courses—especially on platforms like Ourdemy.

1. Why post-course feedback is essential

Post-course feedback is not only about finding out whether learners are “satisfied” or not.

It plays a much more important role for educators and training providers, such as:

Identifying lessons that are too difficult, too long, or likely to discourage learners
Understanding where learners stop and why they drop out
Improving course content for future versions
Enhancing the overall learning experience on online learning platforms like Ourdemy

In online courses, instructors cannot directly observe learners’ reactions, so feedback becomes the “eyes” that help you understand what is actually happening in your course.

2. Common challenges when creating feedback forms manually

Many educators experience the following problems:

Not knowing what to ask → asking questions just for formality
Questions being too vague → learners give shallow answers
Too many questions → learners abandon the form midway
Feedback data that is difficult to summarize and hard to turn into concrete actions

For example:

“How do you feel about the course?”

→ Learner response: “It’s okay.” (almost unusable)

AI helps shift feedback collection from emotional, unfocused questions to purpose-driven questions.

3. How AI is used in feedback forms today

AI does not replace humans in evaluating educational quality.

However, AI is highly effective in supporting three key areas:

question design, personalization, and data aggregation.

3.1. Creating course-specific questions

Instead of using the same feedback form for every course, AI can generate more relevant questions based on:

The course objectives
The content of each module
The target learner profile

This results in feedback questions that are more closely aligned with each specific course.

3.2. Shortening forms while retaining useful information

AI can help:

Remove overlapping or redundant questions
Prioritize questions that are more likely to generate insights
Combine quantitative questions with short open-ended questions

The typical results are:

Shorter forms
Higher completion rates
More meaningful and actionable responses

3.3. Aggregating and analyzing open-ended feedback

One of AI’s strongest advantages lies in handling open-text feedback:

Collecting open responses
Grouping them by themes (content, instructor, pacing, assignments, etc.)
Identifying recurring patterns instead of reviewing each comment individually

This is especially useful when:

Courses have a large number of learners
There are multiple courses or repeated course runs
Feedback needs to be compared over time

4. Key question categories for post-course feedback forms

An effective feedback form does not need many questions, but it does need the right categories.

4.1. Course content

This helps identify:

Whether lessons were too difficult or too easy
Whether the content met learners’ expectations

Example questions:

“How easy was the course content to understand?”
“Which lesson did you find the most difficult to follow?”

4.2. Format and presentation

This helps improve:

Videos, slides, and text materials
Lesson length and pacing

Example questions:

“Was the length of each lesson appropriate?”
“Which format helped you learn most effectively?”

4.3. Learning experience on the platform (Ourdemy)

This helps uncover issues unrelated to the course content itself.

Example questions:

“Was it easy to find lessons and materials?”
“Did you encounter any technical difficulties?”

4.4. Practical application after the course

This evaluates the real-world value of the course.

Example questions:

“Which parts of the course have you already applied?”
“What content helped you change your current approach or workflow?”

4.5. Suggestions for improvement (open-ended)

Limit this to one or two questions, and keep the tone gentle.

Example:

“If you could change one thing about the course, what would it be?”

5. Step-by-step guide to using AI to create post-course feedback forms

Step 1: Define the primary goal of the feedback form

Before using AI, clearly answer these questions:

What do you most want to improve?
Course content, teaching approach, or learning experience?

Clear example goals include:

Identifying the most difficult lesson
Evaluating the suitability of lesson formats
Collecting ideas for the next version of the course

👉 Each feedback form should focus on one main goal, rather than trying to cover everything.

Step 2: Prepare information to provide to AI

You can summarize the following:

Course name
Target learners (beginners / working professionals / application-focused learners)
Course duration
Main lesson format (video / slide / text)
Learning platform: Ourdemy
Timing of feedback collection: end of course

This information helps AI:

Choose appropriate language and tone
Avoid questions that are too advanced or too basic

Step 3: Ask AI to generate a structured feedback form

Example prompt:

Createa post-course feedbackform for an online course for beginners on Ourdemy.
Theform should havea maximum of10 questions, divided into three sections:
(1) Course content
(2) Learning format and experience
(3) Suggestions for improvement
Questions should be short and easy to answer.

AI will return a grouped list of questions that can be easily refined.

Step 4: Combine different question types

To keep the form easy to answer while collecting useful data, include:

Rating scale (1–5)

Use for:

Clarity
Satisfaction
Practical usefulness

Example:

“How would you rate the clarity of the course content?”

Multiple choice (single or multiple selection)

Use for:

Comparisons
Decision-making

Example:

“Which lesson format helped you learn most effectively?”

Short open-ended questions

Use for:

Deeper insights
Identifying real issues

Example:

“Which lesson took you the most time to complete, and why?”

👉 One or two open-ended questions are usually sufficient.

Step 5: Refine language for Ourdemy learners

After generating the form, you should:

Remove duplicate or overlapping questions
Keep the total number of questions between 5 and 10
Use language that is:
- Gentle
- Non-judgmental
- Encouraging honest feedback

Example revision:

❌ “What is wrong with the course?”
✅ “What do you think could be improved to make the course easier to learn?”

6. How to implement feedback forms on Ourdemy

Method 1: Attach the form to the final lesson

Add the form link to the last lesson
Encourage learners to respond before completing the course

👉 Suitable for short courses

Method 2: Send the form after course completion

Send via email or platform notification
Often results in higher response rates

Method 3: Collect feedback by module

Short forms with 3–4 questions
Helps identify issues early
Suitable for longer courses on Ourdemy

👉 Detailed guides

Ourdemy provides built-in tools for creating forms and embedding them directly into pages or lessons. You can refer to the following guides:

How to create a form on Ourdemy: https://ourdemy.com/where-can-i-create-a-form/
How to add a form to a page or lesson: https://ourdemy.com/how-do-i-add-a-form/

By following these steps, you can easily implement feedback forms tailored to each course without relying on external tools.

Conclusion:

AI helps ask the right questions; educators make the right improvements

Using AI to create post-course feedback forms is not about chasing trends or “modernizing for the sake of it.”

The real goal is to help educators collect feedback in a structured, focused, and actionable way.

When applied correctly, AI helps you:

Ask questions that address real learner issues
Understand the actual learning experience more quickly
Clearly identify areas for improvement

AI helps you ask better and more precise questions.

However, the quality of courses on Ourdemy ultimately depends on the decisions and proactive efforts of educators.