{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T14:29:23Z","timestamp":1776522563643,"version":"3.51.2"},"reference-count":37,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2022,8,25]],"date-time":"2022-08-25T00:00:00Z","timestamp":1661385600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Institute for the Future of Education"},{"name":"the Tecnologico de Monterrey"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Data"],"abstract":"<jats:p>High dropout rates and delayed completion in higher education are associated with considerable personal and social costs. In Latin America, 50% of students drop out, and only 50% of the remaining ones graduate on time. Therefore, there is an urgent need to identify students at risk and understand the main factors of dropping out. Together with the emergence of efficient computational methods, the rich data accumulated in educational administrative systems have opened novel approaches to promote student persistence. In order to support research related to preventing student dropout, a dataset has been gathered and curated from Tecnologico de Monterrey students, consisting of 50 variables and 143,326 records. The dataset contains non-identifiable information of 121,584 High School and Undergraduate students belonging to the seven admission cohorts from August\u2013December 2014 to 2020, covering two educational models. The variables included in this dataset consider factors mentioned in the literature, such as sociodemographic and academic information related to the student, as well as institution-specific variables, such as student life. This dataset provides researchers with the opportunity to test different types of models for dropout prediction, so as to inform timely interventions to support at-risk students.<\/jats:p>","DOI":"10.3390\/data7090119","type":"journal-article","created":{"date-parts":[[2022,8,25]],"date-time":"2022-08-25T21:28:12Z","timestamp":1661462892000},"page":"119","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Student Dataset from Tecnologico de Monterrey in Mexico to Predict Dropout in Higher Education"],"prefix":"10.3390","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5348-6479","authenticated-orcid":false,"given":"Joanna","family":"Alvarado-Uribe","sequence":"first","affiliation":[{"name":"Institute for the Future of Education, Tecnologico de Monterrey, Monterrey 64849, Mexico"},{"name":"School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey 64849, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0935-2139","authenticated-orcid":false,"given":"Paola","family":"Mej\u00eda-Almada","sequence":"additional","affiliation":[{"name":"Institute for the Future of Education, Tecnologico de Monterrey, Monterrey 64849, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7468-188X","authenticated-orcid":false,"given":"Ana Luisa","family":"Masetto Herrera","sequence":"additional","affiliation":[{"name":"Analytics and Business Intelligence Department, Tecnologico de Monterrey, Monterrey 64849, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0666-5279","authenticated-orcid":false,"given":"Roland","family":"Molontay","sequence":"additional","affiliation":[{"name":"Department of Stochastics, Institute of Mathematics, Budapest University of Technology and Economics, 1111 Budapest, Hungary"},{"name":"ELKH-BME Stochastics Research Group, 1111 Budapest, Hungary"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5270-7655","authenticated-orcid":false,"given":"Isabel","family":"Hilliger","sequence":"additional","affiliation":[{"name":"School of Engineering, Pontificia Universidad Cat\u00f3lica de Chile, Santiago 7820436, Chile"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5415-7041","authenticated-orcid":false,"given":"Vinayak","family":"Hegde","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Mysuru Campus, Amrita Vishwa Vidyapeetham, Mysore 570026, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1905-0764","authenticated-orcid":false,"given":"Jos\u00e9 Enrique","family":"Montemayor Gallegos","sequence":"additional","affiliation":[{"name":"Analytics and Business Intelligence Department, Tecnologico de Monterrey, Monterrey 64849, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6894-0125","authenticated-orcid":false,"given":"Renato Armando","family":"Ram\u00edrez D\u00edaz","sequence":"additional","affiliation":[{"name":"Analytics and Business Intelligence Department, Tecnologico de Monterrey, Monterrey 64849, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2460-3442","authenticated-orcid":false,"given":"Hector G.","family":"Ceballos","sequence":"additional","affiliation":[{"name":"Institute for the Future of Education, Tecnologico de Monterrey, Monterrey 64849, Mexico"},{"name":"School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey 64849, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,25]]},"reference":[{"key":"ref_1","first-page":"137","article-title":"Economic Effects of Student Dropouts: A Comparative Study","volume":"3","author":"Latif","year":"2015","journal-title":"J. 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