AI-driven Educational Evaluation Innovation: Construction and Practice of Big Data Analysis and Intelligent Evaluation System

This study offers an intelligent education assessment model incorporating Big Data and AI technology, and built a complete technical framework including data collection, optimization of algorithms and dynamic feedback. According to the empirical test of 12 schools, the system response speed is increased by 40% and the precision rate is increased to 92.3% compared to the traditional evaluation method. The Core algorithm module performs real -time analysis of the learning behavior trajectory and forms a personalized evaluation card. Experimental data show that the system can effectively capture 78% of unconventional learning characteristics and improve the accuracy of educational interventions by 2.1 times. Look for and develop the visual analysis platform at the same time, and operating efficiency on the teacher side is improved by 60% compared to the old system. These technological breakthroughs offer a way achievable for the digital transformation of education assessment, in particular in the formulation of differentiated teaching strategies. The search for follow-up will focus on the elimination of the strangulation neck of the merger of multi-round data and the exploration of the potential for applying advanced computer science in real-time feedback.