Show simple item record

dc.contributor.authorCasadiego-Alzate R
dc.contributor.authorSánchez-Torres J.A
dc.contributor.authorArroyo-Cañada F.J
dc.contributor.authorArgila-Irurita A.
dc.date.accessioned2022-09-14T14:33:41Z
dc.date.available2022-09-14T14:33:41Z
dc.date.created2022
dc.identifier.issn1750385X
dc.identifier.urihttp://hdl.handle.net/11407/7430
dc.descriptionThe aim of the paper sought to identify the factors that influence the dropout risk of university students. We worked with data from a sample of 476 students, including academic, institutional and socio-economic information. Logistic regression was applied to identify the variables with the greatest impact on the dropout risk and thus propose actions that could help mitigate this phenomenon. The model correctly predicted 84% of cases. Among the most important results of this study was that the youngest students taking classes during the day were those who tended to abandon their studies during the first four semesters. Additionally, the effect exerted by age of entry, number of semesters completed, accumulated average, total number of credits approved, financing and obtaining educational aid with the institution was greater when compared with other factors analysed in the present study. Copyright © 2022 Inderscience Enterprises Ltd.eng
dc.language.isoeng
dc.publisherInderscience Publishers
dc.relation.isversionofhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85130135357&doi=10.1504%2fIJMIE.2022.122622&partnerID=40&md5=331b810aab1ccdc882513ce1afdafff2
dc.sourceInternational Journal of Management in Education
dc.titleDeterminants of university student dropout: the case of the Politécnico Grancolombiano
dc.typeArticle
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.publisher.programMercadeo
dc.type.spaArtículo
dc.identifier.doi10.1504/IJMIE.2022.122622
dc.subject.keywordColombiaeng
dc.subject.keywordDropouteng
dc.subject.keywordEnrolmenteng
dc.subject.keywordStrategieseng
dc.subject.keywordUniversityeng
dc.relation.citationvolume16
dc.relation.citationissue3
dc.relation.citationstartpage211
dc.relation.citationendpage234
dc.publisher.facultyFacultad de Ciencias Económicas y Administrativas
dc.affiliationCasadiego-Alzate, R., Department of Marketing, Institución Universitaria Politécnico Grancolombiano, Medellín, Colombia
dc.affiliationSánchez-Torres, J.A., Department of Marketing, University of Medellin, Medellín, Colombia
dc.affiliationArroyo-Cañada, F.J., Department of Business, University of Barcelona, Barcelona, Spain
dc.affiliationArgila-Irurita, A., Department of Business, University of Barcelona, Barcelona, Spain
dc.relation.referencesAhuja, R., Kankane, Y., Predicting the probability of student's degree completion by using different data mining techniques (2018) 2017 4th International Conference on Image Information Processing, ICIIP 2017
dc.relation.referencesAparicio-Chueca, P., Domínguez-Amorós, M., Maestro-Yarza, I., Beyond university dropout. An approach to university transfer (2019) Studies in Higher Education
dc.relation.referencesArulampalam, W., Naylor, R.A., Smith, J.P., Dropping out of medical school in the UK: Explaining the changes over ten years (2007) Medical Education
dc.relation.referencesAtal, D., Hernández, L., Factores de permanencia o abandono de los estudiantes de primer año de la universidad central de chile cohorte (2017) Tercera Conferencia Lationamericana sobre el Abandono en la Educación Superior CLABES, , https://revistas.utp.ac.pa/index.php/clabes/article/view/1687/2423, at
dc.relation.referencesBean, J.P., Dropouts and turnover: The synthesis and test of a causal model of student attrition (1980) Research in Higher Education
dc.relation.referencesBerria, J., Minatto, G., Lima, L.R.A., Martins, C.R., Petroski, E.L., Predictors of dropout in the school-based multi-component intervention, “Mexa-se (2018) Health Education Research, 33 (4), pp. 280-281
dc.relation.referencesBlanchField, W.C., College dropout identification: A case study (1971) Journal of Experimental Education, 40 (2), pp. 1-4
dc.relation.referencesBorkotoky, K., Unisa, S., Female education and its association with changes in sociodemographic behaviour: evidence from India (2015) Journal of Biosocial Science, 47 (5), pp. 1-20
dc.relation.referencesCarvajal, C.M., González, J.A., Sarzoza, S.J., Variables Sociodemográficas y Académicas Explicativas de la Deserción de Estudiantes en la Facultad de Ciencias Naturales de la Universidad de Playa Ancha (Chile) (2018) Formación universitaria, 11 (2), pp. 3-12
dc.relation.referencesCarvajal, R.A., Cervantes, C.T., Aproximaciones a la deserción universitaria en Chile (2017) Educação e Pesquisa, 44 (1), pp. 1-20
dc.relation.referencesCasanova, J.R., Gomes, C.M.A., Bernardo, A.B., Núñez, J.C., Almeida, L.S., Dimensionality and reliability of a screening instrument for students at-risk of dropping out from Higher Education (2021) Studies in Educational Evaluation, 68
dc.relation.referencesCastelló, M., Pardo, M., Sala-Bubaré, A., Suñé-Soler, N., Why do students consider dropping out of doctoral degrees? Institutional and personal factors (2017) Higher Education, 74 (6), pp. 1053-1068
dc.relation.referencesCastro-Montoya, B.A., Lopera-Gómez, C.M., Manrique-Hernández, R.D., Gonzalez-Gómez, D., A competing dropout and graduation risk survival analysis of undergraduate students at a private university in Medellín (Colombia) (2021) Formacion Universitaria, 14 (1), pp. 81-98
dc.relation.referencesCobre, J., Tortorelli, F.A.C., de Oliveira, S.C., Modelling two types of heterogeneity in the analysis of student success (2019) Journal of Applied Statistics, 46 (14), pp. 2527-2539
dc.relation.referencesDharmawan, T., Ginardi, H., Munif, A., Dropout Detection Using Non-Academic Data (2018) Proceedings - 2018 4th International Conference on Science and Technology, ICST 2018, pp. 1-10
dc.relation.referencesDorta-Guerra, R., Marrero, I., Abdul-Jalbar, B., Trujillo-González, R., Torres, N.V., A new academic performance indicator for the first term of first-year science degrees students at La Laguna University: a predictive model (2019) FEBS Open Bio, 9 (9), pp. 1493-1502
dc.relation.referencesEspinosa, J., Hernández, J., Mariño, L., Estrategias de permanencia universitaria (2020) Avft, 39 (1), pp. 88-97. , http://www.revistaavft.com/images/revistas/2020/avft_1_2020/16_estrategias.pdf, at
dc.relation.referencesFernández-martín, T., Solís-Salazar, M., Hernández-Jiménez, M.T., Moreira-Mora, T.E., (2019) Un análisis multinomial y predictivo de los factores asociados a la deserción universitaria, 23 (1), pp. 1-25
dc.relation.referencesFortin, A., Sauvé, L., Viger, C., Landry, F., Nontraditional student withdrawal from undergraduate accounting programmes: a holistic perspective (2016) Accounting Education, 25 (5), pp. 437-478
dc.relation.referencesGarcía, A.M., Acceso, abandono y graduación en la educación superior argentina (2006) Sistema de Información de Tendencias Educativas en América Latina, 5 (1), pp. 1-17
dc.relation.referencesGilardi, S., Guglielmetti, C., University life of non-traditional students: Engagement styles and impact on attrition (2011) Journal of Higher Education, 82 (1), pp. 33-53
dc.relation.referencesHenríquez, N., Escobar, D., Construcción de un modelo de alerta temprana para la detección de estudiantes en riesgo de deserción de la universidad metropolitana de ciencias de la educación (2016) Revista Mexicana de Investigacion Educativa, 21 (71), pp. 1221-1248
dc.relation.referencesHernandez Gonzalez, A.G., Armenta, R.A.M., Rosales, L.A.M., Barrientos, A.G., Xihuitl, J.L.T., Algredo, I., Comparative Study of Algorithms to Predict the Desertion in the Students at the ITSM-Mexico (2016) IEEE Latin America Transactions
dc.relation.referencesvan Herpen, S.G.A., Meeuwisse, M., Hofman, W.A., Severiens, S.E., Arends, L.R., Early predictors of first-year academic success at university: pre-university effort, pre-university self-efficacy, and pre-university reasons for attending university (2017) Educational Research and Evaluation, 3611 (5)
dc.relation.referencesJindal, R., Borah, M.D., A Survey on Educational Data Mining and Research Trends (2013) International Journal of Database Management Systems
dc.relation.referencesJung, J., Kim, Y., Exploring regional and institutional factors of international students' dropout: The South Korea case (2018) Higher Education Quarterly, 72 (2), pp. 141-159
dc.relation.referencesKostopoulos, G., Kotsiantis, S., Pierrakeas, C., Koutsonikos, G., Gravvanis, G.A., Forecasting students' success in an open university (2018) International Journal of Learning Technology, 13 (1), pp. 26-43
dc.relation.referencesKostopoulos, G., Kotsiantis, S., Pierrakeas, C., Koutsonikos, G., Gravvanis, G.A., Forecasting students' success in an open university (2018) International Journal of Learning Technology, 13 (1), pp. 26-43
dc.relation.referencesKotsiantis, S.B., Use of machine learning techniques for educational proposes: a decision support system for forecasting students' grades (2012) Artificial Intelligence Review, 37 (1), pp. 331-344
dc.relation.referencesKuhns, L.M., Vazquez, R., Ramirez-Valles, J., Researching special populations: Retention of Latino gay and bisexual men and transgender persons in longitudinal health research (2008) Health Education Research, 23 (5), pp. 814-825
dc.relation.referencesLehr, S., Use educational data mining to predict undergraduate retention (2016) Proceedings - IEEE 16th International Conference on Advanced Learning Technologies, ICALT 2016
dc.relation.referencesMa, Y., Cragg, K., So close, yet so far away: Early vs. Late dropouts (2012) Journal of College Student Retention: Research, Theory and Practice, 14 (4), pp. 533-548
dc.relation.referencesMarí, G., Muestras Equilibradas En Poblaciones Finitas: Un Estudio (2007) undécimas jornadas 'Investigaciones en la Facultad' de Ciencias Económicas y Estadística
dc.relation.referencesMartín, T.F., Salazar, M.S., Jiménez, M.T.H., Mora, T.E.M., Un análisis multinomial y predictivo de los factores asociados a la deserción universitaria (2015) Revista Electrónica Educare, 23 (1), pp. 1-25
dc.relation.referencesMartin Calvo, J.F., Calidad educativa en la educación superior colombiana: una aproximación teórica (2018) Sophia
dc.relation.referencesMelguizo, T., Torres, F.S., Jaime, H., The association between financial aid availability and the college dropout rates in Colombia (2011) Higher Education, 62 (1), pp. 231-247
dc.relation.referencesMeyer, M., Marx, S., Engineering dropouts: A qualitative examination of why undergraduates leave engineering (2014) Journal of Engineering Education, 103 (4), pp. 525-548
dc.relation.referencesMurray, M., Factors affecting graduation and student dropout rates at the University of KwaZulu-Natal (2014) South African Journal of Science, 110, pp. 39-45. , Nos. 11/12
dc.relation.referenceshttps://observatorio.tec.mx/, at: (accessed on 21 September 2019)
dc.relation.referencesO'Neill, L., Medical school dropout - testing at admission versus selection by highest grades as predictors (2011) Medical Education, 45 (11), pp. 1111-1120
dc.relation.referencesO'Neill, L.D., Residents in difficulty-just slower learners? a case-control study (2014) BMC Medical Education, 14, p. 1047
dc.relation.referencesOloriz, M.G., Fernández, J.M., Relación entre las características del estudiante al momento de iniciar estudios superiores y el abandono en la universidad nacional de luján durante el período 2000-2010 (2010) Tercera Conferencia Lationamericana sobre el Abandono en la Educación Superior CLABES
dc.relation.referencesOu, D., Education for all: Quasi-experimental estimates of the impacts of compulsory primary education in Hong Kong (2013) Asia Pacific Education Review, 14 (1), pp. 267-283
dc.relation.referencesParamo, G.J., Correa Maya, C.A., Deserción estudiantil universitaria. Conceptualización (2012) Revista U, 35 (114), pp. 65-78
dc.relation.referencesPeralta, C.D., Conceptual model for dropout chilean university student (2008) Estudios Pedagogicos, 34 (2), pp. 65-86
dc.relation.referencesRodríguez Urrego, M., La investigación sobre deserción universitaria en Colombia 2006-2016. Tendencias y resultados (2019) Pedagogía y Saberes, 51 (1), pp. 49-66
dc.relation.referencesvan Rooij, E., Fokkens-Bruinsma, M., Jansen, E., Factors that influence PhD candidates' success: the importance of PhD project characteristics (2019) Studies in Continuing Education, pp. 1-20
dc.relation.referencesRooij, E. Van, Jansen, E., Factors that influence PhD candidates' success: the importance of PhD project characteristics (2019) Studies in Continuing Education, pp. 1-20. , Taylor & Francis
dc.relation.referencesSandoval-Palis, I., Naranjo, D., Vidal, J., Gilar-Corbi, R., Early dropout prediction model: A case study of university leveling course students (2020) Sustainability (Switzerland), 12 (22), pp. 1-17
dc.relation.referencesSchripsema, N.R., van Trigt, A.M., Borleffs, J.C., Cohen-Schotanus, J., Selection and study performance: Comparing three admission processes within one medical school (2014) Medical Education, 48 (12), pp. 1201-1210
dc.relation.referencesSlanger, W.D., Berg, E.A., Fisk, P.S., Hanson, M.G., A longitudinal cohort study of student motivational factors related to academic success and retention using the College Student Inventory (2015) Journal of College Student Retention: Research, Theory and Practice, pp. 1-25
dc.relation.referencesSpady, W.G., (1967) Peer Integration and Academic Success: The Dropout Process Among Chicago Freshman, , University of Chicago, USA
dc.relation.referencesSpady, W.G., Dropouts from higher education: Toward an empirical model (1971) Interchange, 2 (1), pp. 38-62
dc.relation.referencesStanczyk, N.E., Bolman, C., Smit, E.S., Candel, M.J.J.M., Muris, J.W.M., De Vries, H., How to encourage smokers to participate in web-based computer-tailored smoking cessation programs: A comparison of different recruitment strategies (2014) Health Education Research, 29 (1), pp. 23-40
dc.relation.referencesStoessel, K., Ihme, T.A., Barbarino, M.L., Fisseler, B., Stürmer, S., Sociodemographic Diversity and Distance Education: Who Drops Out from Academic Programs and Why? (2015) Research in Higher Education, 56, pp. 228-246
dc.relation.referencesSuárez Brieva, E., Suárez Brieva, E.S., Pérez Lara, E.C., Análisis de los factores asociados al rendimiento académico de los estudiantes de un curso de informática (2019) Journal of Chemical Information and Modeling, 53 (9), pp. 1689-1699
dc.relation.referencesTieben, N., Brückenkursteilnahme und Studienabbruch in Ingenieurwissenschaftlichen Studiengängen (2019) Zeitschrift fur Erziehungswissenschaft, 22 (1), pp. 1175-1202
dc.relation.referencesVanegas-Pissa, J.C., Sancho-Ugalde, H., Análisis de cohorte: Deserción, rezago y eficiencia terminal, en la carrera de Licenciatura en Medicina y Cirugía de la Universidad de Ciencias Médicas (2019) Revista Electrónica Educare, 23 (1), pp. 1-22
dc.relation.referencesVenegas-Muggli, J.I., Muñoz-Gajardo, K.A., González-Clares, M.J., The impact of counseling and mathematics remedial programs on the academic achievement of higher education students in Chile (2019) Journal of College Student Development, 60 (4), pp. 472-488
dc.relation.referencesVila, D., Cisneros, S., Granda, P., Ortega, C., Posso-Yépez, M., García-Santillán, I., Detection of desertion patterns in university students using data mining techniques: A case study (2019) Technology Trends. CITT 2018. Communications in Computer and Information Science, , Botto-Tobar M., Pizarro G., Zúñiga-Prieto M., D'Armas M., Zúñiga Sánchez M. (eds)
dc.relation.referencesViloria, A., Padilla, J.G., Vargas-Mercado, C., Hernández-Palma, H., Llinas, N.O., David, M.A., Integration of data technology for analyzing university dropout (2019) Procedia Computer Science, 155 (1), pp. 569-574
dc.relation.referencesde Visser, M., Fluit, C., Cohen-Schotanus, J., Laan, R., The effects of a non-cognitive versus cognitive admission procedure within cohorts in one medical school (2018) Advances in Health Sciences Education, 23 (1), pp. 187-200
dc.relation.referencesVos, C.M., Wouters, A., Jonker, M., de Haan, M., Westerhof, M.A., Croiset, G., Kusurkar, R.A., Bachelor completion and dropout rates of selected, rejected and lottery-admitted medical students in the Netherlands (2019) BMC Medical Education, 80 (1), pp. 1-9
dc.relation.referencesWray, J., Aspland, J., Barrett, D., Gardiner, E., Factors affecting the programme completion of pre-registration nursing students through a three year course: A retrospective cohort study (2017) Nurse Education in Practice, 24 (1), pp. 14-20
dc.relation.referencesYair, G., Rotem, N., Shustak, E., The riddle of the existential dropout: lessons from an institutional study of student attrition (2020) European Journal of Higher Education
dc.relation.referencesZelterman, D., (2015) Applied Multivariate Statistics with R, Applied Multivariate Statistics with R, , Switzerland: Springer International Publishing
dc.type.coarhttp://purl.org/coar/resource_type/c_6501
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dc.type.driverinfo:eu-repo/semantics/article
dc.identifier.reponamereponame:Repositorio Institucional Universidad de Medellín
dc.identifier.repourlrepourl:https://repository.udem.edu.co/
dc.identifier.instnameinstname:Universidad de Medellín


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record