Characterizing intercampus migration in a private university of Baja California, Mexico [version 2; peer review: 2 approved]
Given the socioeconomic and environmental differences between Mexico’s geographical regions, having a multi-campus system is common for private and public universities. Hence, students may choose to migrate from one campus to another. Although such a phenomenon is not properly students’ desertion, s...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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F1000 Research Ltd
2023-03-01
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| Series: | F1000Research |
| Subjects: | |
| Online Access: | https://f1000research.com/articles/11-678/v2 |
| _version_ | 1797866189323501568 |
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| author | Damián-Emilio Gibaja-Romero Lucia Beltrán Rosa-María Cantón-Croda |
| author_facet | Damián-Emilio Gibaja-Romero Lucia Beltrán Rosa-María Cantón-Croda |
| author_sort | Damián-Emilio Gibaja-Romero |
| collection | DOAJ |
| description | Given the socioeconomic and environmental differences between Mexico’s geographical regions, having a multi-campus system is common for private and public universities. Hence, students may choose to migrate from one campus to another. Although such a phenomenon is not properly students’ desertion, students’ migration impacts campus’ main indicators: enrollment growth goals, terminal efficiency, accreditation programs, and revenue. Thus, the campus of origin internalizes migration as students’ desertion. By considering a campus from a private multi-campus university in Baja California, Mexico, this study characterizes and predicts students’ migration and predicts by determining the socioeconomic and academic variables that impact the probability of moving to a different campus. Our database comprises quantitative and qualitative information of 356 dropout students from 2008 to 2018. Hence, we apply the logistic regression technique to build a predictive model; we found that the most significant predictive variables are the GPA results, age, financial support, and academic development. So, our main results characterize migrant students as having top grades, coming from the high school campus, and attending engineering programs. Surprisingly, economic variables are not significant in choosing to migrate from one campus to another. |
| first_indexed | 2024-04-09T23:20:02Z |
| format | Article |
| id | doaj.art-c5e3c629f2e543539bad1cc0c770546a |
| institution | Directory Open Access Journal |
| issn | 2046-1402 |
| language | English |
| last_indexed | 2024-04-09T23:20:02Z |
| publishDate | 2023-03-01 |
| publisher | F1000 Research Ltd |
| record_format | Article |
| series | F1000Research |
| spelling | doaj.art-c5e3c629f2e543539bad1cc0c770546a2023-03-22T01:00:00ZengF1000 Research LtdF1000Research2046-14022023-03-0111145672Characterizing intercampus migration in a private university of Baja California, Mexico [version 2; peer review: 2 approved]Damián-Emilio Gibaja-Romero0Lucia Beltrán1https://orcid.org/0000-0003-2230-2299Rosa-María Cantón-Croda2https://orcid.org/0000-0002-5469-8964Area de Matematicas, UPAEP-University, Puebla, Puebla, 72410, MexicoCETYS Universidad, Ensenada, Baja California, 22000, MexicoDecanato de Ingenierias, UPAEP-University, Puebla, Puebla, 72410, MexicoGiven the socioeconomic and environmental differences between Mexico’s geographical regions, having a multi-campus system is common for private and public universities. Hence, students may choose to migrate from one campus to another. Although such a phenomenon is not properly students’ desertion, students’ migration impacts campus’ main indicators: enrollment growth goals, terminal efficiency, accreditation programs, and revenue. Thus, the campus of origin internalizes migration as students’ desertion. By considering a campus from a private multi-campus university in Baja California, Mexico, this study characterizes and predicts students’ migration and predicts by determining the socioeconomic and academic variables that impact the probability of moving to a different campus. Our database comprises quantitative and qualitative information of 356 dropout students from 2008 to 2018. Hence, we apply the logistic regression technique to build a predictive model; we found that the most significant predictive variables are the GPA results, age, financial support, and academic development. So, our main results characterize migrant students as having top grades, coming from the high school campus, and attending engineering programs. Surprisingly, economic variables are not significant in choosing to migrate from one campus to another.https://f1000research.com/articles/11-678/v2University dropout predictive modeling data mining intercampus migrationeng |
| spellingShingle | Damián-Emilio Gibaja-Romero Lucia Beltrán Rosa-María Cantón-Croda Characterizing intercampus migration in a private university of Baja California, Mexico [version 2; peer review: 2 approved] F1000Research University dropout predictive modeling data mining intercampus migration eng |
| title | Characterizing intercampus migration in a private university of Baja California, Mexico [version 2; peer review: 2 approved] |
| title_full | Characterizing intercampus migration in a private university of Baja California, Mexico [version 2; peer review: 2 approved] |
| title_fullStr | Characterizing intercampus migration in a private university of Baja California, Mexico [version 2; peer review: 2 approved] |
| title_full_unstemmed | Characterizing intercampus migration in a private university of Baja California, Mexico [version 2; peer review: 2 approved] |
| title_short | Characterizing intercampus migration in a private university of Baja California, Mexico [version 2; peer review: 2 approved] |
| title_sort | characterizing intercampus migration in a private university of baja california mexico version 2 peer review 2 approved |
| topic | University dropout predictive modeling data mining intercampus migration eng |
| url | https://f1000research.com/articles/11-678/v2 |
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