AI助力费曼技术中英文学习法

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      费曼学习法的核心就是：当你能给人解释清楚一个概念时，才算完全理解。而你能用英文解释清楚时，代表你能用母语人的思维方式去解释一个复杂概念，这个过程中你需要对你的英语表达方式进行整合，并且用口语输出，这个过程很慢，但对你英语有巨大提升。既能快速学习知识，又能提高英语水平的学习方法， 即费曼学习+英文解释+刻意练习

步骤：

1.将你要学习的PDF文件上传到ChatGPT或者Claude,Kimi 等大模型

2.告诉AI你用费曼学习+英文解释的方法帮助你理解这篇材料。

提示词：你是学习专家，我上传一个PDF给您，对您提问，帮助我解答。请用费曼学习帮助我学习与理解，根据我的指示用中文或英文回答。

3.向AI提问，让它用英文出问题考你。届时还可以使用TTS把对应英语文字转为语音MP3，练习英文听力，可以反复听到明白为止。

AI提出的英文问题完整内容：

Question: How does the integration of data elements enhance the efficiency and effectiveness of emergency management as outlined in the "Data Elements ×" three-year action plan?

To answer this question, let's break it down step by step:

1. Understanding Data Elements: Data elements refer to the various types of data that can be collected, analyzed, and utilized to inform decisions and actions. These can include data on disaster incidents, resource allocation, personnel, and operational permits.

2. Emergency Management Context: In the context of emergency management, the goal is to respond quickly and effectively to crises, disasters, or emergencies. This involves coordinating resources, personnel, and actions to mitigate risks and impacts.

3. Integration of Data Elements: The action plan suggests that by integrating data elements across different regions and departments, the efficiency of regulatory enforcement and emergency response can be improved. This integration allows for better sharing and utilization of information, which is crucial during emergencies.

4. Enhancing Safety Management: The plan also mentions the use of public data, such as power and communication data, combined with safety and natural disaster data to improve precision in monitoring and regulation of high-risk activities.

5. Improving Disaster Warning Capabilities: By analyzing data related to seismic activities and environmental changes, the plan aims to enhance the predictive capabilities for earthquakes, including the timing, location, and magnitude.

6. Leveraging Data for Risk Assessment: Insurance companies are encouraged to develop models for assessing safety risks in high-risk industries, which can lead to more accurate and scientific risk evaluations.

7. Outcome: The integration of data elements into emergency management is expected to lead to more efficient and effective responses to emergencies, better safety management, and improved disaster warning systems, all of which contribute to a higher level of preparedness and resilience.

4.关键：自己用英文默念回答一遍，如果回答不上来，再去学习相关概念，直到用英文能把概念解释得很清楚。 

默念完成时，自我解答时英语读出来，可以使用通义千问实时语音识别，检测口语发音标准性：

5. 让AI纠正你的问题。这是《刻意练习》的核心概念：通过正确答案的反馈，有目的的纠正自己的理解，语法，表达，词汇，从而让你大脑走出舒适区。建立新的心理表征。这个过程很痛苦，但是同时学习知识和英文效率很高的方式。

                                                           AI纠正

社区中还发现一个prompt, 让这个过程变成我所说的“从认知门槛到认知斜坡”。
Prompt如下，叫他生成Chain of Thoughts问题，难度：你定；Coverage范围：你定。
好好用retrieval的方式把所有的小问题回答了，然后再用：
Grade all my answers and provide constructive suggestions. 叫他给你改个分。在学习科学里面，打分也是重要技法。

感觉差不多了，还可以叫他针对你没有答对的知识点再去生成一套Chain of Thoughts Questions.