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Article summary:

1. This paper presents an AI education system and related AI curricula specifically designed for primary and secondary students at different cognitive levels.

2. The system is designed to be scalable and knowledge continuous, with simple graphical interfaces to enable primary school students to understand the application of AI in their daily lives.

3. Typical teaching cases such as speech recognition, text recognition, image recognition, intelligent transportation, smart home, and intelligent robots are discussed to enhance comprehension of AI concepts and applications.

Article analysis:

The article provides a comprehensive overview of the design of an AI education system for primary and secondary school students. It outlines the features of the system, including scalability and knowledge continuity, as well as the typical teaching cases that are used to enhance comprehension of AI concepts and applications. The article also discusses the application of parallel intelligence theory and ACP framework in this system.

The article appears to be reliable in terms of its content; however, there are some potential biases that should be noted. For example, the article does not discuss any potential risks associated with using AI in education systems or any possible counterarguments against its use. Additionally, it does not present both sides equally; instead it focuses on promoting the use of AI in educational systems without exploring any potential drawbacks or negative implications that could arise from its implementation. Furthermore, there is no evidence provided for some of the claims made in the article such as “AI curricula are developed based on constructivism” or “typical teaching cases…are used to enhance comprehension of AI concepts and applications” which could make it difficult for readers to assess their accuracy or trustworthiness.

In conclusion, while this article provides a comprehensive overview of an AI education system for primary and secondary school students, there are some potential biases that should be noted when assessing its trustworthiness and reliability.