SISTC integrated student dataset of 1,027 cleaned records with 14 features for dropout prediction¶
Product or Programme · All products and programmes
Evidence · no claims cited
Description¶
A de-identified dataset created by SISTC researchers by integrating enrollment, academic performance, demographic, and enrollment-history records to support modeling of student withdrawal and cancellation risk.
Components¶
Claims¶
Related Products and Programmes¶
Key Sources¶
- Gheisari, S., & Salarian, H. (2024). Analysis and Prediction of At-Risk Students using Machine Learning Algorithms. https://scholar.google.com/scholar?q=Analysis+and+Prediction+of+At-Risk+Students+using+Machine+Learning+Algorithms
Page metadata
| Field | Value |
|---|---|
type |
product |
id |
sistc-integrated-student-dataset-of-1027-cleaned-records-with-14-features-for-dropout-pred |
title |
SISTC integrated student dataset of 1,027 cleaned records with 14 features for dropout prediction |
description |
A de-identified dataset created by SISTC researchers by integrating enrollment, academic performance, demographic, and enrollment-history records to support modeling of student withdrawal and cancellation risk. |
status |
review |
product_kind |
dataset |
generated |
by process:settle-candidates on 2026-10-10 |
trust |
unverified — no one has confirmed this page's content |
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