LHUThacSi/synthetic_dropout_dataset_vietnam_100k_final_lhu

Student Dropout Prediction Dataset (Lac Hong University - Synthetic)

This dataset is a synthetically generated dataset representing student academic and behavioral data at Lac Hong University. It is intended for machine learning tasks that predict student dropout risks.

📊 Features

• —StudentID: Unique student identifier (format: 1YYxxxxxx)
• —LUC: Lack of University Commitment (Likert 1–5)
• —DCC: Degree Commitment Conflict (Likert 1–5)
• —ITM: Ineffective Time Management (Likert 1–5)
• —CD: Curriculum Design dissatisfaction (Likert 1–5)
• —IALE: Inability to Adapt to Learning Environment (Likert 1–5)
• —LCP: Low Class Participation (Likert 1–5)
• —PC: Personal Circumstances (Likert 1–5)
• —SDI: Student Dropout Intention (score 1–5)
• —Dropout: Target label (1 = high dropout risk, 0 = low risk)
• —GPA_10: GPA on a 10-point scale
• —Year: Current academic year (1 to 4)
• —RepeatCount: Number of failed courses
• —DebtCredits: Total credits currently failed
• —Major: Student's field of study
• —TotalCredits: Total credits required for the major

📁 Dataset Summary

• —Samples: 100,000
• —File Format: CSV
• —License: MIT
• —Use Case: Tabular classification - dropout risk prediction

🧪 Example Use Cases

• —Train classification models to predict dropout
• —Analyze correlation between GPA, failed credits, and dropout risk
• —Use in academic dashboards or student early-warning systems

🛡 Disclaimer

This dataset is synthetically generated for academic and research purposes. It does not contain any real or personally identifiable student data.