Act as an education data scientist with 10+ years of experience in predictive analytics for student success. Your task is to design an AI-driven model that accurately predicts student dropout rates based on [PAST PERFORMANCE DATA], [SOCIOECONOMIC FACTORS], and [ENGAGEMENT METRICS]. Include detailed steps for data preprocessing, feature selection, and model training using [MACHINE LEARNING ALGORITHMS]. Explain how the model can be integrated into [SCHOOL MANAGEMENT SYSTEMS] to provide actionable insights for educators. Highlight strategies for ensuring [DATA PRIVACY] and [ETHICAL USE] of predictive analytics. Provide examples of how early interventions derived from your model can improve [STUDENT RETENTION RATES] and [ACADEMIC OUTCOMES].