Preventing student drop out at CWU
Document Type
Oral Presentation
Campus where you would like to present
SURC 140
Start Date
16-5-2013
End Date
16-5-2013
Abstract
This data-mining project aims to assess the risk of CWU undergraduate students’ attrition. We choose a moment at the end of a student’s first year of study to predict the risk of evasion and decide if counseling should recommended. Once the at-risk students are detected, many actions may be taken (such as psychological and educational support, registering orientation, shift change, etc.) to reduce drop-out risk. As input data, we use the student's profile, extracted from the university’s database, including the student's academic results. We use the Google Prediction API, which is Google's collection of cloud-based machine learning tools for prediction.
Recommended Citation
Arakh, Suvarna, "Preventing student drop out at CWU" (2013). Symposium Of University Research and Creative Expression (SOURCE). 5.
https://digitalcommons.cwu.edu/source/2013/oralpresentations/5
Additional Mentoring Department
Computer Science
Preventing student drop out at CWU
SURC 140
This data-mining project aims to assess the risk of CWU undergraduate students’ attrition. We choose a moment at the end of a student’s first year of study to predict the risk of evasion and decide if counseling should recommended. Once the at-risk students are detected, many actions may be taken (such as psychological and educational support, registering orientation, shift change, etc.) to reduce drop-out risk. As input data, we use the student's profile, extracted from the university’s database, including the student's academic results. We use the Google Prediction API, which is Google's collection of cloud-based machine learning tools for prediction.
Faculty Mentor(s)
Razvan Andonie