The advancement of human society has always been closely tied to the interactions of social production transformation and the evolution of knowledge medium. To ensure that social development continues to progress, it is essential that education gets ahead of technological advancements. In today’s rapidly evolving society, which is being driven by Artificial Intelligence (AI), determining the direction that education should take is a critical issue that must be addressed.

Capability-oriented education

The digitalization of education is a vital part of the Digital China initiative. With years of continuous efforts, China’s educational informatization has achieved leapfrogged progress. Campus network access across the nation has reached 100%, which has provided a significant boost to the development of education in China.

The digital and intelligence revolutions have raised higher requirements for workers’ qualities in various fields. Capabilities for innovation, communication and cooperation, addressing complex issues, and human-machine cooperation will become essential for the future. Changes in demand for talent will force the comprehensive, thorough transformation and upgrading of education, with shaping capabilities at its core.

Features of future education

Initially, education will transition from a fixed paradigm to a ubiquitous existence. This shift includes two aspects. First, the subject of education will become ubiquitous, and second, education settings will become ubiquitous.

Secondly, the focus of education will shift from emphasizing the “efficiency of teaching” toward the “essence of cultivation.” “Learning how to learn effectively” is far more important than “acquiring a skill.” The use of AI technologies will allow for a more personalized approach to education, as each individual’s cognitive structure can be accurately described and their intellectual strengths leveraged. This will lead to a more active, learner-centered learning mechanism that encourages creativity and a passion for learning.

Thirdly, the future of education will see a shift from knowledge inheritance toward knowledge creation, with the “joint human-machine creation” becoming the major knowledge production mode, while traditional education theories view humans as the only active factor. Building upon the foundation of knowledge inheritance, the challenge for future education lies in facilitating learners to update and create knowledge through human-machine interactions.

Fourthly, there is a shift from a single knowledge scenario toward a virtual simulation ecosystem. The cross-border integration of “Internet+AI+education” has disrupted the traditional method of knowledge transfer. With the help of virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies, it is now possible to reconstruct traditional knowledge presentation methods, promote the interaction and integration between real and virtual spaces, and ultimately create a new educational environment, via creating digital twins of humans, objects, and environments.

Technological application

The future of education cannot be reduced to a simple superposition or combination of traditional education, digitalization, and intelligentization. Rather it will be a self-driven education model that prioritizes the holistic development of individuals and integrates technology to enhance their capabilities. This approach is necessary to meet the demands of future society for workers’ innovative abilities.

First, it is suggested to use technologies to promote a return to the essence of education. The learning environment should be improved through the application of AI technologies. It is advised to accelerate the construction of a comprehensive disciplinary knowledge atlas, phased capability atlas, and industrial skill atlas, to improve the adaptive learning system that drives the “long board” abilities of learners. With the help of artificial neural networks, big data mining, and other technologies, we can identify the path of multi-dimensional comprehensive quality training, value shaping and learning behavior optimization for learners in different educational scenarios and age stages. This will help education return to the essence that “everyone can develop in an all-round way and become a talent.”

Second, it is suggested to solidify the technological foundation of future education. At present, the national education digitalization strategic action has been fully launched, and the comprehensive digital transformation of education is becoming an inevitable trend. We must use the national intelligent education public service platform as a driving force to speed up the integration of high-quality education digital resources. This will help to build a ubiquitous intelligent education knowledge base, tool base, and material base. By doing so, we can promote education equity by making education resources dynamically accessible, improve education efficiency through quick access to education tools, and enable educators and learners to access education resources anytime and anywhere, and explore new disciplinary fields. We need to adapt to the paradigm shift of data-intensive scientific discoveries, strengthen the promotion and application of cutting-edge technologies in future education, and promote the leap from quantitative to qualitative accumulation.

Third, it is recommended to establish ubiquitous and interconnected educational application scenarios. To enhance the development and utilization of technologies such as VR, we should create an educational application environment that has pervasive awareness and connectivity among “humans, machines, objects, and environments.” This will result in the formation of a “digital twin world” that can be utilized for future education. We need to build a future education scenario set that adapts to different cognitive stages, skill training and socialization processes, focusing on different educated groups in the fields of basic education, vocational education, higher education, and social education. We will construct a comprehensive simulated training field for vocational education, as well as a simulation space for advanced exploration of future higher education science. The goal is to showcase the entire dynamic process of converting knowledge into tangible productivity for learners in the “digital twin world” of future education. This will create a closed-loop system of knowledge, starting with interactive input and culminating in creative output.

Fourth, it is necessary to firmly uphold the ethical bottom line of intelligent technologies. This involves identifying and recognizing potential risks. We should also leverage the “emotional” advantages of educators, with the goal of promoting students’ growth. By understanding the emotional needs of learners during the learning process, we can uphold and continue the humanistic sentiments in education, and encourage emotional integration in educational practices.

Fifth, it is suggested to prioritize the cultivation of high-end AI talent by accelerating the construction of a national strategic sci-tech force in the field of AI, with a focus on intelligent computing and intelligent perception, and accelerate the construction of major sci-tech infrastructure such as digital reactors. We will first explore reforms such as talent mobility, diversified investment, and achievement evaluation and transformation. Collaborative innovation among national laboratories, universities, research institutes, and enterprises should be promoted, the cultivation of urgently needed professional and technical AI talent accelerated, to deepen integration and mutual support between AI and education.

Zhu Shiqiang is deputy secretary of the Party committee at Zhejiang University.