Student Dropout and Academic Success Prediction Data

Student academic records from a higher education institution, hosted on the UCI Machine Learning Repository. The dataset is intended for predicting student dropout and academic success outcomes. Platform tags indicate a focus on Educational Data Mining.

Use Cases

• Predict dropout status using demographic and enrollment features like course enrollment and age.
• Classify academic success levels based on past academic performance metrics such as GPA or credits earned.
• Identify key risk factors for student attrition by analyzing features related to socioeconomic status and academic engagement.
• Build a binary classifier to flag at-risk students using features like attendance records and grade history.

Strengths

• Dataset is hosted on the UCI Machine Learning Repository, a recognized source for benchmark datasets.
• Platform tags provide clear domain context: Educational Data Mining, Tabular, Academic Success, Higher Education, Student Dropout.

Limitations

• Specific data volume (row count) and feature details (column names) are unknown.
• Geographic and temporal coverage of the student records is unspecified, limiting generalizability.

Provenance

Source

UCI Machine Learning Repository