Abstract：The rapid development of artificial intelligence (AI) technology is profoundly reshaping the education ecosystem, bringing many new opportunities and challenges for the promotion of educational equity. Based on the perspective of educational equity, this study systematically analyzes the connotation, path and value orientation of AI-enabled educational equity through the multiple dimensions of theoretical tracing, reality mapping, conceptual reshaping and future vision.
The study found has that artificial intelligence is driving education informatization from quantitative change to qualitative change, providing unprecedented technological support for tailored teaching and personalized learning. In terms of educational opportunities, AI technology helps build online education platforms, effectively bridging the digital divide between urban and rural education; supports the construction of intelligent learning systems, providing students with personalized and adaptive learning experiences; and promotes the ubiquitous supply of educational resources, improving the flexibility of educational opportunities. In the education process, intelligent technology supports the realization of tailor-made teaching, so that the unique needs of each student can be fully satisfied; provides strong support for differentiated teaching, and strives to narrow the education quality gap between different students; drives the development of intelligent learning companions, and greatly expands the spatial and temporal scope of personalized teaching services available to learners. In terms of education results, AI can comprehensively assess students’ comprehensive quality based on multiple data, support precise and developmental evaluation of students’ personality growth, and promote the continuity and ecology of education evaluation.
However, new types of risks, such as algorithmic bias and data privacy, should not be ignored, and it is necessary to strengthen the construction of technical ethics. The homogenization tendency of intelligent recommendation systems may aggravate the Matthew effect in the distribution of quality education resources; the improper use of education data may infringe on students’ privacy and produce group labeling effects; and the black-box algorithmic design may deprive the education process of the humanistic care it deserves.
In the future, we should uphold the concept of science and technology for the good, and promote collaborative innovation in educational theory and practice. In terms of human-machine collaboration, we should promote the deep involvement of artificial intelligence systems in the whole process of teaching and learning, and provide intelligent support for personalized learning. In the reconstruction of teachers’ roles, it is necessary to promote the transformation of teachers from “teaching craftsmen” to “guides”, dedicated to fostering holistic student development and value-based guidance. In terms of education governance reform, we need to utilize knowledge map, big model and other technologies to drive education decision-making from experience-driven to data-driven transformation. In the area of digital literacy enhancement, it should be used as a strategic tool to promote educational equity, narrow the digital divide and realize equal opportunities for development.
In short, we should give full play to the advantages of artificial intelligence while not ignoring the humanistic care adhere to the people-oriented, student development as the center, in order to make artificial intelligence truly become a tool to empower teachers, service education, and contribute wisdom and strength to the construction of a strong educational country. This requires the coordinated advancement of education theory and practice, policy innovation and system supply, technological progress and humanistic care.
