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Predicting time to graduation at a large enrollment American university.

ABSTRACT: The time it takes a student to graduate with a university degree is mitigated by a variety of factors such as their background, the academic performance at university, and their integration into the social communities of the university they attend. Different universities have different populations, student services, instruction styles, and degree programs, however, they all collect institutional data. This study presents data for 160,933 students attending a large American research university. The data includes performance, enrollment, demographics, and preparation features. Discrete time hazard models for the time-to-graduation are presented in the context of Tinto's Theory of Drop Out. Additionally, a novel machine learning method: gradient boosted trees, is applied and compared to the typical maximum likelihood method. We demonstrate that enrollment factors (such as changing a major) lead to greater increases in model predictive performance of when a student graduates than performance factors (such as grades) or preparation (such as high school GPA).

SUBMITTER: Aiken JM

PROVIDER: S-EPMC7665823 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Predicting time to graduation at a large enrollment American university.

Aiken John M JM De Bin Riccardo R Hjorth-Jensen Morten M Caballero Marcos D MD

PloS one 20201113 11

The time it takes a student to graduate with a university degree is mitigated by a variety of factors such as their background, the academic performance at university, and their integration into the social communities of the university they attend. Different universities have different populations, student services, instruction styles, and degree programs, however, they all collect institutional data. This study presents data for 160,933 students attending a large American research university. T ...[more]

PMID: 33186404

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Project description:ObjectiveTo evaluate the association between health and study-related factors measured by an Electronic Health Questionnaire (eHQ), participation in a health examination process and graduation in a university student population.DesignNationwide, retrospective, register-based cohort study with a 6-year follow-up.SettingStudent health care in Finland. Finnish Student Health Service (FSHS) provides statutory student health services to university students in Finland. The health examination process of FSHS includes the eHQ provided annually to university entrants and a subsequent health check when necessary based on students' eHQ response.ParticipantsA national cohort of university entrants from the 2011-2012 academic year (n=14 329, n (female)=8075, n (male)=6254).Outcome measuresThe primary outcome measure was graduation, measured based on whether a student had completed a bachelor's, licentiate or master's degree during the 6-year follow-up.ResultsSome 72% of the women and 60% of the men had graduated during the follow-up. The predictors in the eHQ associated with non-graduation differed by sex. Among the women's low enthusiasm about studies (OR 2.6, 95% CI 1.9 to 3.6), low engagement with studies (OR 2.5, 95% CI 1.8 to 3.4) and daily smoking (OR 1.9, 95% CI 1.4 to 2.6) were the strongest predictors to non-graduation. Among the men, low engagement with studies (OR 3.7, 95% CI 2.5 to 5.5) and obesity (body mass index≥35) (OR 4.0, 95% CI 1.9 to 8.8) were the strongest predictors to non-graduation. Not attending the health check when referred was associated with non-graduation in both sexes: the OR for not graduating was 1.6 (95% CI 1.3 to 1.9) in women and 1.3 (95% CI 1.0 to 1.6) in men.ConclusionsEngagement and enthusiasm about studying in the first year are important predictors of graduation and therefore a potential intervention target. Health promotion initiatives conducted early in the studies may have a positive effect on students' academic achievement.

Dataset Information

Predicting time to graduation at a large enrollment American university.

Publications

Predicting time to graduation at a large enrollment American university.

Similar Datasets

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