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The connotation and characteristics of "artificial intelligence + education"In today's digital age, the emergence of cutting-edge technologies such as natural language processing models represented by ChatGPT and the latest video generation model Sora are profoundly revealing the unlimited potential and broad prospects of artificial intelligence (AI) in the field of education. The emergence of these advanced technologies not only heralds a revolutionary change driven by artificial intelligence in the field of education, but also provides strong technical support for achieving higher quality and more personalized education. In this context, it is particularly important and urgent to study and apply the new model of "artificial intelligence + education".The so-called "artificial intelligence + education" is a comprehensive concept. It refers to a new education model that deeply integrates artificial intelligence technology into the field of education, optimizes the education environment through intelligent means, and promotes fundamental changes in traditional education models, teaching methods and learning experiences. In a narrow sense, "artificial intelligence + education" means using artificial intelligence technology to assist in teaching, management, evaluation and feedback, etc., to achieve more efficient and personalized education services. In a broader sense, "artificial intelligence + education" is not only limited to technical applications, but also represents an innovation in educational concepts and educational models. It emphasizes student-centeredness, making full use of artificial intelligence technology to meet students' personalized needs, and continuously improving students' learning outcomes. At the same time, "artificial intelligence + education" also requires educators to constantly update their educational concepts and improve their own information literacy to adapt to the needs of educational development in the new era."AI + Education" has the following main features: New scenario education: extending the depth and breadth of education. With the deep integration of "AI + Education", the traditional education model is being redefined and the boundaries of education are constantly being broadened. "AI + Education" has greatly extended the depth and breadth of education by building new educational scenarios, breaking the time and space limitations of education. With the help of AI technology, learners can study anytime and anywhere through online learning platforms, get instant learning feedback and answers to questions through intelligent tutoring systems, and gain a deeper understanding of knowledge through simulation learning systems, greatly improving learning depth and learning efficiency.Personalized learning: Achieve precise matching of educational resources. Personalized learning is one of the basic characteristics of "AI + Education" and also its advantage. With the help of artificial intelligence technology, learners' learning trajectories can be collected comprehensively, accurately and timely, and learners' learning preferences can be mastered. Through precise calculations, customized learning services can be provided to learners, and learners' interests, abilities, learning resources and learning methods can be accurately matched, thus improving learning efficiency and effectiveness.Adaptive adjustment: enabling dynamic adaptation of the learning process. Adaptability is an important feature of "AI + Education". The adaptive adjustment capability of "AI + Education" can dynamically adjust the content and difficulty of learning according to the learner's learning progress and feedback, so that learners always learn in the learning method and learning difficulty area that best suits them. In addition, adaptive adjustment can also help learners discover their own learning blind spots and weak links, and fill in the gaps in time to further improve learning effects.Immersive experience: continuously generating innovative momentum for education. Under the new scenario education model of "artificial intelligence + education", immersive experience is gradually becoming an important engine for educational innovation. "Artificial intelligence + education" creates an immersive learning environment by combining advanced virtual reality (VR) and augmented reality (AR) technologies, visualizes abstract knowledge, provides learners with an immersive learning experience, and makes the educational process more vivid and vivid. In this environment, learners can not only understand and master knowledge more intuitively, but also explore and experience the knowledge they have learned more deeply, thereby effectively stimulating learners' creativity and providing a continuous source of innovative momentum for educational innovation. By continuously generating innovative momentum, "artificial intelligence + education" will also continue to promote the transformation and innovation of the education model to dynamically adapt to the transformative needs of educational development in the new era.

Globally, the continuous development of artificial intelligence technology has become an important force in promoting educational reform. The deep integration of artificial intelligence technology and education has not only had a profound impact on teaching and learning methods, but also touched the core of educational concepts, and will inevitably promote fundamental changes in educational paradigms. However, like a double-edged sword, the widespread application of artificial intelligence technology in the field of education has also brought a series of problems and challenges to educational development and reform.● Technical challenges. Challenges of technical applicability. Although current artificial intelligence technology has made significant progress, it still seems powerless when faced with complex scenarios in education. The essence of artificial intelligence is to simulate human intelligence. It relies on algorithms and data to perform tasks, providing education with a new way of personalized learning and teaching, and improving the efficiency and experience of education. However, this technology has not yet reached a fully mature stage and still faces challenges brought about by the sparsity of learning data, which may lead to a lack of accuracy in personalized solutions. At the same time, when data resources are limited, the model also tends to generalize. These problems not only affect the in-depth application of artificial intelligence in education, but also cause many educational artificial intelligence products on the market to appear not "intelligent" enough in actual applications, and it is difficult to meet the changing and complex needs in educational scenarios.Risk of technology dependence. The widespread application of artificial intelligence technology in the field of education also brings a potential risk, that is, educators and managers may over-rely on these technologies to solve teaching and management problems, and learners may over-rely on artificial intelligence technology to obtain knowledge and information. This dependence may lead to "technology dependence" in teaching and learning, while ignoring the importance of reflection in the teaching process and independent thinking in the learning process. Therefore, although the application of artificial intelligence in the field of education presents an irreversible trend, we should still stick to the original intention of education, continue to focus on the core value of education and the all-round development of people, and avoid excessive dominance of technology and weakening the educational function of education.●Challenges of data security and privacy protectionThe "2024 Artificial Intelligence Index Report" released by Stanford University pointed out that the continuous advancement and widespread use of technology have significantly improved productivity, but the current promotion and application of artificial intelligence technology may also be limited by the limitations of the technology itself, and may cause problems such as privacy, the spread of false information and intellectual property risks.Data security challenges. It is extremely important to ensure data security during the collection, storage and transmission of data. In the field of education, the accumulated data not only covers students' basic personal information, but also involves important records of their learning process, such as learning progress, academic performance, behavioral patterns and other sensitive data. This type of information is highly private and sensitive. If it is accidentally leaked or maliciously used, it will pose a serious threat to the safety of individual students and may have an adverse impact on the stability and healthy operation of the overall education system. Therefore, how to establish a complete data security mechanism to ensure the security of data throughout its life cycle has become an urgent and vital task in the field of artificial intelligence technology applications.The challenge of privacy protection. In the "AI + Education" scenario, a large amount of student data is collected and analyzed in order to provide each student with a personalized learning plan. Students' personal information, learning behaviors, and grades all fall into the category of personal privacy. The collection and use of these data must be based on full respect for students' privacy. However, in practice, due to the influence of multiple factors such as concepts, technology, and management, the protection of student privacy may face uncertainty. In the integrated development of "AI + Education", the protection of student privacy also needs to be given high attention to ensure the safety and reliability of the educational environment.●Value-based challengesIn the field of education, values ​​and ethical concepts are an indispensable part. How to ensure that the application of artificial intelligence technology in the field of education meets the expectations and requirements of society is a challenge that "artificial intelligence + education" needs to face at the value level.The value function of technology products is missing. At present, most AI education products are mainly concentrated in the field of adaptive learning. They provide students with customized learning content and feedback through intelligent algorithms. However, the goal of education is far more than imparting knowledge. It also includes the comprehensive development of students, such as the cultivation of social skills, psychological quality, and moral qualities. However, the existing AI education products are insufficient in cultivating these qualities. The functional defects of AI education products at the value level have, to a certain extent, limited the comprehensive application and far-reaching impact of AI technology in the field of education.The difficulty of coordinating different values. In the context of the deepening development of globalization and informatization, social thoughts and ideas are becoming increasingly diverse. In the process of promoting the integration of "artificial intelligence + education", ensuring that the application of artificial intelligence technology can adapt to this diverse development trend, especially in line with the core values ​​and ethical values ​​of society, has become an urgent and challenging task. Specifically, there are significant differences in the understanding and practice of culture in different scenarios. For example, in some companies, collectivism and team spirit are regarded as important value orientations; while in other companies, individual struggle may be respected. Therefore, the design and application of artificial intelligence technology products should fully consider these cultural differences to avoid misleading.●Challenges in the way knowledge is produced and disseminated. The continuous deepening of the application of artificial intelligence technology has not only changed the way knowledge is produced and disseminated, but also posed new challenges to the talent training model. The challenge of the change in the way knowledge is produced to students' independent thinking. The progress of artificial intelligence technology has changed the way humans acquire, create and apply knowledge. The automation and intelligence of knowledge production methods have lowered the threshold for knowledge acquisition, but over-reliance on content generated by artificial intelligence may form students' inertia in learning, causing students to gradually lose the ability to independently find, screen and integrate information. This change has brought new challenges to students' independent thinking ability.The paradigm revolution in the way knowledge is disseminated challenges the function of schools. The application of artificial intelligence technology has brought about significant changes in the way knowledge is disseminated. The traditional "teacher-student" binary teaching model is gradually changing to a "teacher-machine-student" ternary structure. In this new model, teachers, machines and students promote and influence each other and jointly promote the development of intelligent education. However, this change also means that people's concept of schools will change with the times, that is, the knowledge imparting function of schools will be weakened, which also poses a challenge to the functional positioning of schools in knowledge dissemination.●The challenge of adapting the roles of teachers and students. In the "AI + Education" scenario, the roles of teachers and students have changed, and both need to keep learning to better adapt to the changes in the education scenario. The challenge of teacher role adaptation. In the "AI + Education" scenario, teachers are no longer just knowledge transmitters, but must gradually evolve into guides and assistants in the students' learning process. This requires not only teachers to have solid professional knowledge, but also to master a series of new teaching tools and methods. This transformation undoubtedly places higher demands on teachers. The challenge of student role adaptation. In the "AI + Education" scenario, students must not only have good autonomous learning ability, but also have the ability to interact effectively with AI technology. For some students who are passive recipients in the traditional learning model, autonomous learning will face unprecedented challenges and difficulties, which may further widen the academic performance gap.●Challenges in resource sharingAlthough artificial intelligence technology has brought many opportunities to education, it has also posed challenges to fairness. How to enable all students to enjoy the benefits of artificial intelligence technology has become a crucial issue.Transparency concerns caused by "algorithm black box". "Algorithm black box" means that the internal logic and decision-making process of the algorithm are opaque and difficult to understand for users, so it is difficult to detect and correct errors. Decisions made based on these errors may have a negative impact on fairness. "Algorithm black box" is usually highlighted through problems such as algorithm bias and lack of transparency. Technological potential differences affect application costs. Specifically, some developed regions and schools have relatively good technical infrastructure due to their rich educational resources and financial support. These regions and schools can use artificial intelligence technology to assist teaching earlier and more comprehensively, thereby providing students with a richer and more efficient learning experience. On the contrary, schools in remote areas or with poor economic conditions may not be able to afford the high technical costs, and thus face different situations in the allocation of artificial intelligence education resources.

At the level of technology application: adhere to the combination of technology demystification and technology reification. In the development process of "artificial intelligence + education", we must adhere to the principle of combining technology demystification with technology reification to ensure that advanced technology can truly serve the essence of education. Technology demystification means that we need to break the excessive mystification and blind worship of artificial intelligence technology and face up to its essence as a tool. By deeply understanding the principles, capabilities and limitations of artificial intelligence, we can look at its role in education more rationally and avoid blindly pursuing the novelty of technology while ignoring its fit with educational goals. Before implementing new artificial intelligence educational technologies, a review mechanism should be established to evaluate their applicability, effectiveness and potential risks to ensure that only technologies that have been verified and meet educational goals are introduced.The emphasis of technological transformation is to properly integrate artificial intelligence technology into the educational process, making it a powerful tool to improve teaching effectiveness, assist teachers' work, and promote student learning, rather than to completely replace the role of teachers or traditional teaching methods. Therefore, the boundaries of technology application should be clarified, and the scope of application of artificial intelligence in education should be clarified. Educational institutions need to work with technical experts and education experts to formulate application standards and guidelines for artificial intelligence in the field of education. These standards and guidelines should clarify which artificial intelligence technologies are applicable, which may not be suitable for the educational environment, and how to reasonably integrate artificial intelligence into teaching activities. By clearly defining the reasonable scope of application of artificial intelligence in education, we can avoid excessive use of technology and excessive reliance on technology by teachers and students in the teaching process, which will affect independent thinking and innovation in the teaching process.Data security and privacy protection: Focus on the coordination of data operation and standardized management to eliminate the security risks of "AI + Education". In the development of "AI + Education", to ensure data security, compliance and personal privacy protection, it is necessary to build a complete data protection and privacy management mechanism from multiple levels such as legislation, management and technology to ensure that technology serves education without harming the legitimate rights and interests of teachers and students.First, strengthen data security legislation. Strict laws and regulations related to data security should be introduced to clearly define the responsibilities and obligations of educational institutions in various aspects such as data collection, storage and use. Secondly, establish a data life cycle management system. Thirdly, improve the privacy protection mechanism. The transparency of the privacy policy is the key. By formulating and making public a clear privacy policy, users should fully understand how data is collected, used and shared, and know their rights. At the same time, anonymize or desensitize sensitive data to reduce the risk of personal privacy leakage. Use advanced encryption and security technologies to provide solid technical support for data. Finally, strengthen standardized management and personnel training. Regularly train relevant personnel on data security and privacy protection, and ensure that they have the necessary knowledge and skills through assessment.Value level: ensure that technology serves the educational process, rather than dominates or replaces the educational process. "First, clarify the auxiliary position of artificial intelligence in education. The essence of education is to cultivate the all-round development of people, including knowledge, skills, emotional attitudes and values. Artificial intelligence should be regarded as an auxiliary teaching tool rather than the main body of education. By using artificial intelligence technology to provide students with personalized learning resources and using intelligent algorithms to track students' learning progress and learning effects, the purpose is to promote students' understanding of knowledge and mastery of skills, but artificial intelligence technology cannot replace schools and teachers as the main body of education. The emotional communication and interaction between teachers and students and classmates is difficult to achieve with the current application of artificial intelligence technology. Therefore, artificial intelligence can only play an auxiliary role in education.Secondly, pay attention to the all-round development of students. Educational goals are the yardstick for the application of artificial intelligence technology. When using artificial intelligence technology to design teaching activities, educational goals must be fully embedded in the application scenarios of artificial intelligence technology to ensure that technology serves the realization of educational goals, rather than simply using technical means to improve the efficiency of knowledge transfer. For example, artificial intelligence technology can be used to simulate teaching scenarios of different teaching design scenarios. For example, when introducing the occurrence of a historical event in a history class, virtual reality technology can be used to allow students to "travel" to ancient times and witness the occurrence of historical events in person, thus realizing the integration of historical knowledge education with emotional attitudes and values ​​education and other multi-faceted educational goals.Finally, enhance the inclusiveness of AI education products for different cultural scenarios. The design concept of AI education products should be to help students understand the double-edged sword effect of AI technology and cultivate students' correct views on technology and values. Through the application of AI education products, such as simulating communication scenarios under different cultural backgrounds through virtual reality or augmented reality technology, integrating value education into communication scenarios, and enhancing students' cross-cultural communication capabilities. In addition, when developing AI education products, the differences in different cultural backgrounds should be fully considered. For example, multiple language options and cultural background settings can be provided in the functional design of AI products to meet the personalized needs of different users.Knowledge production and dissemination level: Explore diversified talent training models. The application of artificial intelligence technology in the field of education is profoundly changing the way knowledge is produced and disseminated, and "artificial intelligence + education" provides unlimited possibilities for the innovation of talent training models.First, from the perspective of changes in the way knowledge is produced, the introduction of artificial intelligence technology has provided students with unprecedented convenience, but it has also brought challenges to the cultivation of independent thinking ability. Effective measures must be taken to overcome students' excessive dependence on artificial intelligence. First, balance the use of artificial intelligence with traditional teaching methods, combine virtual reality and augmented reality technology, provide students with an immersive learning experience, and allow them to practice in a simulated environment to deepen their understanding of knowledge. Second, implement problem-oriented learning, design real problem scenarios, take actual problems as the starting point, guide students to use artificial intelligence tools to explore and solve problems, and cultivate their ability to think independently and solve problems when facing problems.Secondly, from the perspective of the transformation of the way knowledge is disseminated, artificial intelligence technology has changed the way knowledge is disseminated, from the two-way interaction between teachers and students to the multi-dimensional interaction between "teachers, machines and students". In the "artificial intelligence + education" scenario, the ternary structure of "teachers, machines and students" emphasizes the close interaction between the three. The use of artificial intelligence technology to achieve a high degree of integration of education and learning resources has become a key link in improving teachers' teaching effectiveness and meeting students' personalized learning needs. Through artificial intelligence technology, existing teaching resources in various forms such as video, audio, and animation can be effectively integrated. It can also create suitable graphic and audio-visual teaching resources at any time according to different teaching scenarios. It can not only provide teachers with more vivid and vivid teaching content, but also enhance students' experience and help stimulate students' interest in learning.Teacher-student role adaptation level: Improvement of teaching ability and cultivation of autonomous learning ability. In the "artificial intelligence + education" scenario, the transformation and adaptation of the roles of teachers and students is particularly critical. This is not only an innovation of the traditional education model, but also an active exploration of the future development of education.First, strengthen the training of teachers' AI application skills. In the "teacher-machine-student" ternary structure, teachers can use AI technology to more accurately understand the learning needs and progress of each student, thereby providing personalized educational services. As a guide, teachers need to help students understand machine-generated knowledge and guide students on how to use AI resources more effectively. Therefore, in order to adapt to the needs of AI + teaching, teachers should be provided with systematic AI application skills education and training to help them adapt to new roles and improve their ability to use AI technology for teaching.Secondly, strengthen the cultivation of students' autonomous learning ability. Under the new education model, students should be helped to improve their autonomous learning ability and combine the advantages of traditional learning methods with artificial intelligence technology-assisted learning. Continue to carry forward the advantages of traditional learning methods in focusing on students' deep thinking and emotional communication between teachers and students, such as discussions, case analysis, group cooperation and other forms of activities in traditional classrooms; at the same time, students also need to learn to flexibly use artificial intelligence technology to enhance learning effects, such as using intelligent teaching systems to design personalized learning paths, and using virtual reality and augmented reality technologies for immersive learning. When evaluating students' learning outcomes, a more diverse evaluation method should be adopted, not only paying attention to students' mastery of subject knowledge, but also comprehensively considering the development of their creativity, communication skills, teamwork skills and other aspects.Achievement sharing: Optimize the allocation of educational resources and break the technological gap and algorithm black box. The rapid development of artificial intelligence technology has brought unprecedented changes and opportunities to the field of education. However, the technological gap between different regions, schools and educators has also highlighted the differences in the application level of artificial intelligence. In order to ensure the sharing of the achievements of the development of "artificial intelligence + education", it is necessary to optimize resource allocation and break the technological gap through policy guidance.First, optimizing the allocation of educational resources through policy guidance is the key to overcoming the technological gap. The government should play a policy-leading role, not only paying attention to the total amount of educational resources invested, but also paying attention to the reasonable allocation of resources among different regions and schools. By optimizing the fiscal budget, setting up special funds and other measures, we can guide educational resources to remote areas, schools with poor economic conditions and special education, and continuously improve their technical infrastructure conditions, so as to effectively narrow the educational gap between regions and schools, avoid the technological gap caused by uneven resource allocation, and provide a better educational environment for all students.Secondly, popularizing AI education is also an important way to overcome the "technological gap". Popularizing AI education through various means such as offering AI-related courses, holding popular science lectures, and providing practical platforms can provide all students with a common technical starting point, thereby narrowing the technical gap between different student groups and eliminating the resource sharing differences caused by technical differences.In addition, promoting transparency in algorithmic decision-making is another important measure to promote resource sharing. In the "AI + Education" scenario, breaking the "algorithm black box", correcting algorithmic bias, and promoting transparency in algorithmic decision-making will help promote fairness. The fairness and transparency of algorithmic decision-making can be ensured by introducing independent third-party institutions to conduct regular audits of algorithms, thereby eliminating information asymmetry and enhancing the trust of all parties in the education system.

The above text has been slightly abridgedSelected from | "National Governance" magazine, Issue 13, 2024Original title | "Artificial Intelligence + Education": Current Situation, Challenges and Approaches

Author: Si Linbo, Professor of School of Public Administration, Northwestern University

New Media Editor | Chang Chang

Original editor | Feng Yifan