As an important scientific and technological force for social development, artificial intelligence technology will serve as a new driving force for national economic development and international competition. Innovative talents are the cornerstone to promote the orderly development of artificial intelligence. In the era of artificial intelligence, how to combine artificial intelligence technology with education and cultivate more innovative talents for artificial intelligence development has become a major and far-reaching task faced by countries around the world. The plan to serve education based on artificial intelligence technology has attracted great attention from countries all over the world. Among them, maker education, as a new type of education model, its core goal of talent training is highly consistent with artificial intelligence, which is based on training people who are good at using technology innovative talents.

Maker education for the era of artificial intelligence is mainly to cultivate makers who are engaged in artificial intelligence development and innovation. They not only have the ability to innovate and create, solve problems and have a keen scientific and technological foresight, but also have good teamwork and communication skills. . At the same time, the core technology of artificial intelligence has injected new vitality into maker education. Maker education has important theoretical and practical significance for the cultivation of innovative talents in the intelligent era.

First of all, curriculum design should emphasize the mastery of basic concepts and basic principles, instead of bringing a large number of the latest so-called artificial intelligence achievements that are still in the exploratory stage into the classroom, falling into the misunderstanding of blindly "seeking novelty". The current artificial intelligence discipline is still in the process of rapid evolution. Compared with traditional disciplines such as mathematics and physics, many of the latest achievements have not been fully tested by theory and practice, and lack classicity and stability. For example, machine learning-related courses can focus on the basic ideas and methods of supervised and unsupervised learning, avoiding the complex deep learning models that are rapidly evolving.

Secondly, according to the cognitive ability and characteristics of students in different grades, the corresponding teaching content and classroom activities should be designed, and there should be obvious differences between different grades. For example, in elementary school, experiential activities and classroom discussions can be the main focus; in junior high school, more emphasis is placed on the understanding of basic principles and simple practice; in high school, we can appropriately deepen the understanding of important concepts and methods and organize comprehensive practice . For the same core content, the curriculum settings of different grades need to be designed and planned from the shallower to the deeper. For the explanation of more complex concepts and methods, the method of horizontal analogy should be used as much as possible to present it to students intuitively.

Thirdly, the curriculum design should adopt more project-based or inquiry-based learning, without emphasizing complete knowledge and theoretical systems, so that students can be easily accepted and interested in in-depth exploration. Students can choose common situations and themes in their daily life, design reasonable driving problems and teaching scaffolds, and guide students to use artificial intelligence technology to solve practical problems or make project works. For example, the topic of "garbage classification" can be selected, with "how to build a smarter trash can" as the driving question, and guide students to complete the learning of relevant core content in the process of completing the design and production of smart trash cans.

Artificial intelligence education in primary and secondary schools in my country needs to follow the knowledge system and thinking methods of the artificial intelligence discipline itself, so that students can understand what problems artificial intelligence can be used to solve in the experience, master the basic concepts and thinking methods of artificial intelligence in learning, and practice in practice. Think about what new problems and impacts artificial intelligence will bring. At the same time, it is necessary to encourage the participation of multiple social entities such as experts in the field, industry associations, and artificial intelligence enterprises, jointly build and share high-quality curriculum design plans, tools and cases, and collaboratively solve bottleneck problems such as the lack of high-quality teachers. Scale and high-quality landing are guaranteed.

To sum up, with the strong support of relevant national policies, artificial intelligence education in primary and secondary schools in my country has grown from nothing and is gradually entering a period of rapid development. To carry out high-quality AI education in primary and secondary schools, we need to first pay attention to some of the current challenges. On this basis, it is necessary to standardize and clarify the core content and scope of the curriculum, and design the curriculum according to the characteristics of the artificial intelligence discipline itself, so as to help the majority of primary and secondary school teachers understand and master "what to teach" and "how to teach".

Reviewing Editor Huang Haoyu

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