Explanatory Factors of University Dropout Explored Through Artificial Intelligence
This paper identifies key research on the factors that help to explain university dropout and how these factors are being explored by means of artificial intelligence (AI). The study describes the methodology employed to select 31 papers from a repository of 2,745 reported in the literature. The ana...
| Authors: | , , |
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| Format: | article |
| Status: | Published version |
| Publication Date: | 2023 |
| Country: | México |
| Institution: | UNIVERSIDAD AUTÓNOMA DE BAJA CALIFORNIA |
| Repository: | Revista Electrónica de Investigacion Educativa |
| Language: | Spanish |
| OAI Identifier: | oai:ojs.redie.uabc.mx:article/4455 |
| Online Access: | https://redie.uabc.mx/redie/article/view/4455 |
| Access Level: | Open access |
| Keyword: | deserción escolar tasa de deserción escolar estudiante universitario inteligencia artificial dropping out dropout rate college students artificial intelligence evasão escolar taxa de evasão estudante universitário inteligência artificial |
| Summary: | This paper identifies key research on the factors that help to explain university dropout and how these factors are being explored by means of artificial intelligence (AI). The study describes the methodology employed to select 31 papers from a repository of 2,745 reported in the literature. The analysis centered on the main AI methods used and four categories of explanatory factors of university dropout: academic factors; factors associated with motivation and study habits; institutional factors; and economic and sociodemographic factors. The conclusion drawn from this literature review is that AI is most commonly used for decision tree-based classification, and most studies focus on predicting university dropout on the basis of explanatory factors. |
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