An AI model provides specific help when a user makes a mistake. The help should relate directly to the user's last action. The help should not be a general suggestion.
By Pawan Nayar · from the LLOS AI Learning record
An AI model provides specific help when a user makes a mistake.
The help should relate directly to the user's last action. The help should not be a general suggestion.
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. The hint should not be a general message like 'think carefully.' The hint should guide the user to the next correct step.
A student is learning about nouns and verbs. The student tries to identify 'happy' as a noun. The AI model shows a small message. The message says, 'Try pointing. You can point to an apple. You cannot point to 'happy' – you feel it. 'Happy' describes something.' This specific hint helps the student understand the difference.
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A developer creates wrong answer choices for a question. Each wrong choice needs a matching explanation.
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.
If an AI model lacks specific feedback, it uses general responses. These general responses are not helpful for a student.
An AI model provides specific help when a user makes a mistake. The help should relate directly to the user's last action. The help should not be a general suggestion.