Abstract
In 21 century the education become more important like the health and the economic sector. In Oman, the students join the higher educational institutes after they complete twelve years in school. During their studies the students affected by many factors that can lead them to incomplete their studies and get the higher certificate. This study investigate the factors that affect the students in withdraw from colleges of technology in the first year using data mining techniques. This study target the students in colleges of technology in foundation level. Using decision tree list of the rules extracted that may affect the students in withdrawing from the college. It found that most of students leave the college with reason undesired to study, which affected the college preformance.
References
- Al-Radaideh, Q. A., Al-Shawakfa, E. M., & Al-Najjar, M. I. (2006, December). Mining student data using decision trees. In International Arab Conference on Information Technology (ACIT'2006), Yarmouk University, Jordan
- Raju, D., & Schumacker, R. (2015). Exploring student characteristics of retention that lead to graduation in higher education using data mining models. Journal of College Student Retention: Research, Theory & Practice, 16(4), 563-591.
Abstract
References
- Al-Radaideh, Q. A., Al-Shawakfa, E. M., & Al-Najjar, M. I. (2006, December). Mining student data using decision trees. In International Arab Conference on Information Technology (ACIT'2006), Yarmouk University, Jordan
- Raju, D., & Schumacker, R. (2015). Exploring student characteristics of retention that lead to graduation in higher education using data mining models. Journal of College Student Retention: Research, Theory & Practice, 16(4), 563-591.
Details
| Primary Language | English |
|---|---|
| Subjects | Other Fields of Education |
| Journal Section | Articles |
| Authors | |
| Publication Date | September 10, 2020 |
| Submission Date | February 3, 2020 |
| Published in Issue | Year 2020Volume: 6 Issue: 16 |
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