Student Academic Performance & Dropout Prediction with Explainable AI
Predict which students are at risk of failing or dropping out early in the semester, and explain why with SHAP.
Representative screens. Your project is built to the listed features after you order.
Need your guide to approve it first?
Download the two-page synopsis and abstract, free.
Compiled for you, not resold
Every codebase is compiled to order, configured with its own database migrations and bundled with a report written to your university’s format, so your submission never matches anyone else’s. Deliverables reach your vault within 10 to 12 working days, depending on demand and how much customisation you ask for.
Problem Statement & Abstract
Colleges usually discover struggling students only after exams. This project predicts risk early, using attendance, internal marks, assignment submissions and background factors, so mentors can step in while it still matters.
Using the public UCI Student Performance dataset plus a synthetic college dataset, the project cleans the data, handles class imbalance with SMOTE and compares Logistic Regression, Random Forest and XGBoost. The best model classifies students as low, medium or high risk and predicts the expected final grade.
Because teachers must trust the predictions, every prediction is explained with SHAP values: for example "risk is high mainly because attendance is 58% and two assignments are missing". A Streamlit dashboard lets mentors upload a class list, see risk levels, filter by subject and download a list of students to counsel. The report discusses fairness, so that factors such as gender do not unfairly drive predictions.
Key Features
- Data cleaning, encoding and feature engineering
- Class imbalance handled with SMOTE
- Comparison of Logistic Regression, Random Forest and XGBoost
- Low / medium / high risk classification
- Per-student explanations with SHAP
- Streamlit dashboard with class upload and filters
- Downloadable counselling list
- Fairness check across student groups
Suitable For
Everything included
+ GST • about $96 USD
Added to your cart
- Delivered in 10 to 12 working days
- Free revisions for 30 days while your guide reviews
- Report written to your university’s format