Every wrong answer choice must have specific feedback. If a user selects a wrong option, the system must provide a reason why it is wrong. Without feedback, the user does not learn from the mistake.
By Pawan Nayar · from the LLOS AI Learning record
Every wrong answer choice must have specific feedback.
If a user selects a wrong option, the system must provide a reason why it is wrong. Without feedback, the user does not learn from the mistake.
A developer creates wrong answer choices for a question. Each wrong choice needs a matching explanation. This explanation tells the user why their answer is incorrect. If there is no feedback, the user gets no help. The system will not show a hint. The user will not understand their mistake.
A student answers a multiple-choice question. The student picks an incorrect option. If the developer did not write specific feedback for that option, the student sees nothing. The student does not learn why the answer was wrong. The student cannot improve their understanding.
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When a user fails a task, the AI model should offer a hint. The hint must be specific to the sub-task where the user failed.
A system must have a clear signal for every failure. This signal can be a specific time, a tap pattern, or a wrong input.
A quiz is a chance for a person to learn. It helps a person understand new ideas.
After a third wrong attempt, the AI model should show a large explanation. Correct parts of the user's answer should turn green.
Every wrong answer choice must have specific feedback. If a user selects a wrong option, the system must provide a reason why it is wrong. Without feedback, the user does not learn from the mistake.