ARTIFICIAL INTELLIGENCE (AI) EMPOWERS EDUCATIONAL DECISION-MAKING: RESEARCH ON PATHWAYS AND CHALLENGES OF GAOKAO APPLICATION

Abstract

With the deepening of the new GaoKao reform and the digital transformation of education, GAOKAO application planning faces challenges such as information overload, over-reliance on experience and regional disparities. Traditional models struggle to meet dynamic and personalized demands. This study systematically examines the pathways and challenges of Artificial Intelligence (AI) technologies in GaoKao application planning, constructing a "perception-analysis-response"technical closed-loop framework. Through multimodal data fusion, dynamic decision optimization and service chain design, AI technologies can address the limitations of traditional planning models: integrating of academic performance, psychological assessments and policy data at front-end; generating a five-dimensional decision-making system and risk-alert models based on intelligent algorithms at middle-end; and delivering personalized reports and real-time tracking services at back-end. Case analyses reveal that 3 application models, including commercialization, public-benefit and technology-integration, achieve cost efficiency, equity orientation and technological breakthroughs respectively, while facing challenges such as algorithmic transparency, sustainable operations and ethical risks at the same time. The study further uncovers multidimensional paradoxes in technological empowerment, including conflicts between algorithmic authority and educational subjectivity, and class solidification exacerbated by digital divides. To address these issues, an education-oriented ethical framework must be established, together with dynamic adaptation mechanisms and equity compensation arrangement, to foster a collaborative governance system driven by "technology + humanistic"synergy. This research provides theoretical and practical insights for optimizing educational resource allocation and advancing scientific decision-making, offering significant implications for modernizing educational governance.