Answer: Chain-of-Thought Prompting

Chain-of-Thought (CoT) prompting is specifically designed to make AI models explain their reasoning step-by-step. This technique encourages the model to break down complex problems into intermediate steps, making the thought process transparent and easier to understand. **Why other options are not correct:** - **A) Zero-shot Prompting**: This involves giving the model a task without any examples. While it can work for simple tasks, it doesn't inherently encourage step-by-step explanations. - **B) Negative Prompting**: This technique is used to specify what the model should NOT do, often in image generation or to avoid certain outputs. It doesn't promote step-by-step reasoning. - **D) Few-shot Prompting**: This provides examples to guide the model's response, but the examples themselves need to demonstrate step-by-step reasoning for the model to learn this behavior. Chain-of-Thought prompting is the most appropriate choice because it explicitly instructs the model to show its work, which is essential for an AI tutor that needs to be transparent about its reasoning process.

Author: Jin H