⏱️ The Essentials in 3 Minutes |
🧠 Understand the Pedagogical Value of the Open Question
The open question moves the learner from a passive posture (identify the right answer) to an active one (define what a good answer looks like). It is a powerful lever for anchoring complex concepts and developing the ability to transfer knowledge. It is particularly effective:
at the start of a module, to deconstruct misconceptions and activate initial representations;
after several granules, to increase difficulty and test deep comprehension;
in sequence: several open questions in a row create an immersive, reflective experience.
It works particularly well for:
anchoring mastery of complex concepts: "restate in your own words the principle of...";
application questions where the learner must work through a concrete and complex situation.
📌 Example: in a management training course, an open question such as "How would you respond to a demotivated team member?" pushes the learner to mobilize their learning in a real context, far beyond what a multiple-choice question allows.
🔀 Choose the Right Mode
Mode | Use case |
Without expected answer | Free reflection, open-ended questioning |
With expected answer | Practice on a specific concept |
💡 In an AI project, the expected answer is generated automatically: the "with expected answer" mode always applies.
🛠️ Add an Open Question Manually
Open your project.
Add an exercise granule in the relevant module.
Choose the Open question type.
Edit the exercise via the ✏️ icon.
Select the mode:
With expected answer: enter the model answer, then enable AI if you want personalized feedback.
Without expected answer: enter only the question (and optionally a narrator comment).
⚠️ If you switch from "with expected answer" to "without expected answer", you may lose the content entered. A warning message is displayed before the change.
👀 Anticipate the Learner Experience
The learner enters their answer in a free text area. They have 2 attempts before seeing the expected answer (if one exists).
Without expected answer: the learner reflects and writes, with no feedback. Useful for sparking reflection or preparing a discussion.
With AI enabled: after their response, the learner receives personalized feedback that analyzes their answer against the model and indicates how to improve.
⚠️ AI mode requires the learner to be logged in to a Didask account. Distribution via a public link without registration is not compatible with this mode: remove open questions with AI before configuring this type of distribution.
📊 Track Statistics
The quality of learners' first responses automatically determines the difficulty level displayed for the exercise:
Quality of first responses | Level displayed |
Majority poor | Difficult |
Majority average | Moderate |
Majority good | Easy |
⚠️ Detailed statistics are available from 15/01. They are not retroactive: only responses submitted after that date are taken into account.
📌 Good to Know
This format is designed for practice, not evaluation: it is not possible to consult individual learner responses.
The open question cannot be added to a final evaluation or an evaluation module.
Keywords: open question, exercise granule, AI feedback, free response, formative exercise.