EDUCATIONAL MANAGEMENT OF PERSONALIZED LEARNING PATHS BASED ON BIG DATA IN YUNNAN

Abstract

This paper examines the use of big data in managing personal learning paths in Yunnan. The study is set in a region with many ethnic groups and uneven development. Global research shows that real time data and adaptive systems can make learning more personalized for each student. Local practice in Yunnan still faces many challenges. The study identifies four key problems in universities: weak digital infrastructure, centralized governance, low teacher data skills, and limited culturally responsive design. Most systems do not reflect local culture. The findings suggest that effective management requires more than technology. It needs flexible governance, clear teacher training, basic rules for data use, and tools that match local needs. Insights from other countries offer useful guidance. Using these lessons, universities in Yunnan should develop a data plan that aligns with the local social and educational context.