In 2024, just after the college entrance examination, some people took the language and physics questions of the college entrance examination to "challenge" domestic artificial intelligence (AI).From the results, most of the AI's language composition is written in the right way, but for relatively complex and logical problems such as math and physics, the accuracy of AI is uneven, and no AI model has achieved all the accuracy.
The reason for this is that the vast majority of AI today's capabilities depend on the training data and algorithms used by its development agencies.Because languages have relatively fixed structures and rules, these data-driven AIs perform well in understanding and generating natural languages.But for mathematics, physics and other disciplines, AI needs to have a deep understanding of mathematical concepts, formulas, reasoning and even the physical world, and involves the influence of various factors such as interference recognition.Reflecting on AI's problem-solving performance, they may perform well in terms of specific knowledge points, but have limited ability to solve problems that require some creativity and flexibility.For the application of AI in education, people should recognize the limitations of relying on AI, and developing human intelligence and creativity is still an important goal of the "AI+Education" stage.
At present, the application of AI in education has made some progress.Many domestic AI education applications or equipment can develop personalized learning plans and provide course content in stages according to students' learning conditions and needs.Some AI models can also provide real-time guidance and feedback, correct students' homework, and analyze students' learning data to understand their knowledge.At the same time, the prospects for AI applications in education are still broad, such as AI devices in the education scene still need to be "used" in the state, how to provide proactive educational assistance is worth studying.In addition, AI can only check the students' knowledge system according to the database, and lack support for the cultivation of students' creativity.It is still dependent on teachers and parents to make up for it.
To understand and build a comprehensive "AI+ education" for a more efficient, reliable, and human-machine collaborative education system, we must look at it from a more open perspective.The future of "AI+ education" should not simply use educational equipment with built-in AI, but should achieve AI coverage of educational scenarios by building "human-machine environmental ecosystem intelligence."Human-machine environmental ecosystem intelligence is the sum of humans, AI, devices, environments, and their interactions and relationships.Environmental elements generally refer to the physical environment, social environment and information environment. These environmental factors will create conditions for human-computer interaction and system performance and provide auxiliary information.Under this ecosystem, people, machines, and environments in the system form a complete and complex ecosystem through interdependence and interaction.
Human-machine environment ecosystem intelligence will bring more diversified, personalized and interactive learning experience to "AI+ education", promote the overall development of students, and is the future development direction of existing AI education applications.This does not mean that AI or teachers will be replaced, but will continue to be an important part of the entire education ecosystem, working with other actors such as students, parents, and others to build richer and more productive learning environments.In the mature human-machine environment ecosystem intelligence, teachers will play a key role in guiding interpersonal communication, emotional cultivation and personalized development.
Learn knowledge, build character, inspire, develop leadership…All aspects of quality training have their importance and should not be neglected.The core philosophy of human-machine environmental ecosystem education engineering is to give full play to the advantages of human and AI technologies to create an environment conducive to learning and system development from the perspective of the overall ecosystem.In the future, AI may no longer be the answer to the problem, but rather the task of developing students' creativity, critical thinking, and comprehensive skills.Such a complex process requires a combination of factors such as stimulation and awakening, knowledge transfer, individual autonomy and social environment.In such an educational environment, students can better find self-worth and become responsible, creative and contributing citizens.