Examining the Effects of Institutional and Cohort Characteristics on Retention Rates

Pike, Gary R.; Graunke, Steven S.

doi:10.1007/s11162-014-9360-9

Cited by 28 publications

(18 citation statements)

References 18 publications

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“…According to the results presented by the author, the institutional influence on the student's propensity for dropping out is therefore modest. In the same sense, the results of the research presented by Pike and Graunke (2015) emphasize student variables in particular vocational and career issues. Tinto and Cullen (1973) report that evidence-based studies of dropout in only one institution have serious limitations.…”

Section: Introductionmentioning

confidence: 79%

Multilevel modeling of persistence in higher education

Ferrão

Almeida

2018

Ensaio: aval.pol.públ.Educ.

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The dropout or evasion rates in higher education are now a social and institutional concern, justifying the implementation of public policies to prevent this phenomenon. These policies need studies on the most determinant variables of the risk of dropout. The main objective of this study is to analyze the student's persistence in undergraduate courses, and the relationship with the student's previous school trajectory and with the conditions of entrance into higher education, controlling for students' sociodemographic characteristics, such as gender and age. We applied multilevel logistic regression models to data of 2.697 freshmen enrolled in a Portuguese public university in the academic year 2015/16. The results suggest that failure in basic education (ISCED 2) has a long-term effect. According to the estimates obtained, students who declare not having failed in basic education have odds ratio of persistence 2.7 times higher than students who declare having failed in basic education. The conditions of student's admission to the course he/she attends are relevant variables to persistence in Higher Education, for example, whether s/he was admitted to her/his first option course and the student's university entrance score. The results also show that older and male students have lower probability of persistence.

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Section: Introductionmentioning

confidence: 79%

Multilevel modeling of persistence in higher education

Ferrão

Almeida

2018

Ensaio: aval.pol.públ.Educ.

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“…Our principal interest is to understand how meso (university level) and macro (national level) contexts interact with micro phenomena such as students' careers (Pike & Graunke, 2015). In order to achieve this aim, the paper shows a secondary analysis of longitudinal administrative data by means of SA and EH.…”

Section: Methodsmentioning

confidence: 99%

The interaction of meso and macro contexts with students’ careers. Three applied analysis

Decataldo

Amico

D'Alessandro³

2019

CEJER

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This paper presents three applied analysis. Our principal interest is to understand how meso (university level) and macro (national level) contexts interact with micro phenomena such as students’ careers. To achieve this aim, the paper shows a secondary analysis of longitudinal administrative data by means of Sequence Analysis and Event History Models. Furthermore, it shows the results of an additional analysis using a quasi-experimental research on longitudinal data. The paper examines typical pathways of Italian students, by means of administrative information’s on student enrollment from Sapienza University of Rome. The aim of this paper is triple: 1. describe students’ careers in higher education by building a typology of pathways using Sequence Analysis. 2. Identify how socio-economic and macro level characteristics affect students’ careers by multinomial logistic regression model where clusters are used as dependent variables and focus on the study of the “event” by using Event History analysis. 3. Evaluate the Italian Higher Education reform policies and their main outcomes throughout a quasi-experimental research. Mainly, the outcomes show the importance of the warming-up period, the individual choice and the exogenous events after enrolment in determining the success/failure of each career. Our outcomes suggest that Italian universities should rethink the mechanisms available to manage failure and guide student choices.

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“…More generally, student characteristics that affect 4-year degree completion include race, gender, age, socioeconomic status (SES), and enrollment intensity (part-time vs. full-time) (Gayles & Ampaw, 2014; Pike, 2013; Pike & Graunke, 2015; Titus, 2006, 2009). Variables were collected from the IPEDS Fall Enrollment survey to capture the percent of total fall enrollment of students from each of the following racial groups: Asian, Native Hawaiian, or Pacific Islander; Black/African American; Hispanic/Latino; and American Indian/Alaska Native with White students as the omitted category.…”

Section: Methodsmentioning

confidence: 99%

Performance Funding Policy Impacts on STEM Degree Attainment

2018

Educational Policy

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Performance funding policies for higher education allocate appropriations to public institutions based on student outcomes such as degree completions. This study investigates whether a special science, technology, engineering, and mathematics (STEM) incentive in 13 state performance funding policies leads to greater undergraduate degree completions in STEM fields. This study applies a conceptual framework of principal–agent theory and anticipatory policy effects. Incorporating a panel data set on 551 public 4-year institutions from 2003-2004 to 2014-2015, results from difference-in-differences analyses suggest that the STEM incentive increases total STEM bachelor’s degrees completed as well as STEM bachelor’s degrees completed as a proportion of all bachelor’s degrees. Findings are robust to alternative specifications, suggesting that institutions are responding to the performance funding STEM incentive by graduating more students in these high-demand fields.

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Examining the Effects of Institutional and Cohort Characteristics on Retention Rates

Cited by 28 publications

References 18 publications

Multilevel modeling of persistence in higher education

Multilevel modeling of persistence in higher education

The interaction of meso and macro contexts with students’ careers. Three applied analysis

Performance Funding Policy Impacts on STEM Degree Attainment

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