Abstract
The dropout at the universities has become a concern in several countries around the world, its high rates generate negative consequences for students and organizations. Based on the analysis of the educative, organizational theories, and the logic reasoning were established 11 factors that influenced in the dropout. This research as an objective to design a model to determine new factors to predict the dropout in which the dimension of analysis were the students, the institutions, the academic context and the social and economic environment. Additionally, trying through the use of Logistical Regression, Decision Tree and Support Vector Machine if the proposed factors are related and or may contribute predicting the dropout at the universities of Ecuador.
Original language | English |
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Title of host publication | Proceedings of 2018 IEEE Global Engineering Education Conference |
Subtitle of host publication | Emerging Trends and Challenges of Engineering Education, EDUCON 2018 |
Publisher | IEEE Computer Society |
Pages | 1238-1242 |
Number of pages | 5 |
ISBN (Electronic) | 9781538629574 |
DOIs | |
State | Published - 23 May 2018 |
Externally published | Yes |
Event | 2018 IEEE Global Engineering Education Conference - Emerging Trends and Challenges of Engineering Education, EDUCON 2018 - Santa Cruz de Tenerife, Canary Islands, Spain Duration: 17 Apr 2018 → 20 Apr 2018 |
Publication series
Name | IEEE Global Engineering Education Conference, EDUCON |
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Volume | 2018-April |
ISSN (Print) | 2165-9559 |
ISSN (Electronic) | 2165-9567 |
Conference
Conference | 2018 IEEE Global Engineering Education Conference - Emerging Trends and Challenges of Engineering Education, EDUCON 2018 |
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Country/Territory | Spain |
City | Santa Cruz de Tenerife, Canary Islands |
Period | 17/04/18 → 20/04/18 |
Bibliographical note
Publisher Copyright:© 2018 IEEE.
Keywords
- data mining
- factor
- university student desertion