Individualized Education Path Planning and Intelligent Recommendation System Based on Big Data

This article aims to explore the application of big data technology in the field of education and study how to use big data technology to provide individualized instructional resources for preschool education. In this article, an intelligent recommendation algorithm (EDR) which combines emotion and dynamic adjustment is proposed. The algorithm combines a variety of recommendation strategies and affective analysis techniques, aiming at dynamically adjusting the recommendation content while considering children's learning progress and emotional state. The effectiveness of EDR algorithm is verified by simulation analysis. The results show that EDR algorithm is superior to the traditional recommendation algorithm in recommendation accuracy, diversity and user satisfaction. In the preschool education scene, EDR algorithm can understand children's learning needs more accurately and provide them with more individualized learning resources recommendation. Individualized education path planning and intelligent recommendation system based on big data has obvious advantages and practical application value, which provides more accurate and individualized learning support for preschool education.