| Title |
Wilson, Jacob_MCS_2020 |
| Alternative Title |
Applying Machine Learning to Improve Curriculum Design Across a Variety of Disciplines |
| Creator |
Wilson, Jacob |
| Collection Name |
Master of Computer Science |
| Description |
A study of the graduation and retention rates among college student data using features gathered from academic records and demographic information. Machine Learning techniques are employed on university student data to predict graduation and retention rates from several different learning disciplines. Analyses made from result sets showing how the features relate to graduation and retention outcomes. |
| Subject |
Computer science |
| Keywords |
Machine learning techniques; Graduation and retention rates |
| Digital Publisher |
Stewart Library, Weber State University |
| Date |
2020 |
| Language |
eng |
| Rights |
The author has granted Weber State University Archives a limited, non-exclusive, royalty-free license to reproduce their theses, in whole or in part, in electronic or paper form and to make it available to the general public at no charge. The author retains all other rights. |
| Source |
University Archives Electronic Records; Master of Computer Science. Stewart Library, Weber State University |
| Format |
application/pdf |
| ARK |
ark:/87278/s6m5ptvm |
| Setname |
wsu_smt |
| ID |
96829 |
| Reference URL |
https://digital.weber.edu/ark:/87278/s6m5ptvm |
