Strategies, methods and policy support to improve students' academic achievement and career development across academic periods

Abstract

This study explores the strategies, methods and impacts of personalized education implemented at different school stages (from kindergarten to high school). Aiming to solve the problem that the traditional education model ignores individual differences among students and based on empirical analysis, this study explores the effect of personalized education on students' academic achievement, career planning and personal development through cross-stage long-term tracking methods. Using cross-stage long-term tracking methods and experimental grouping of the entire K12 school, combined with artificial intelligence and big data tools, quantitative and qualitative data are analyzed to develop new assessment tools and scales. Data analysis will cover descriptive statistics, multivariate analysis, content analysis, and case studies to evaluate the impact of personalized education on students and test multiple hypotheses. The study also highlights the importance of ethical standards to ensure informed consent and privacy protection of participants.