Using personal statements in college admissions: An investigation of gender bias and the effects of increased structure

Niessen, A. Susan M.; Neumann, Marvin

doi:10.1080/15305058.2021.2019749

Cited by 5 publications

(3 citation statements)

References 30 publications

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“…Additionally, the authors related this, together with cognitive strategies and self-regulation, to the problem of procrastination in higher-education students [145]. Other recent studies found differences in gender variables clearly related to dropout, such as previously acquired competencies or academic skills [7,42,146]. An interesting line of future research in this regard was considered in studies such as that of Vooren et al (2022) [6], where female university students, despite showing lower dropout rates in the first year (specifically in STEM programs, as was the case of the present study), were less likely to finally graduate in comparison with men.…”

Section: Discussionmentioning

confidence: 95%

Predictors of University Attrition: Looking for an Equitable and Sustainable Higher Education

et al. 2022

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The failure and dropout of university studies are issues that worry all nations due to the personal, social, and economic costs that this they entail. Because the dropout phenomenon is complex and involves numerous factors, to reverse it would involve a comprehensive approach through interventions aimed at the factors identified as key in the decision to drop out. Therefore, the main objective of this work is to determine the profile of students who enter the EPN (STEM higher-education institution) to analyze the characteristics that differentiate students who drop out early in their career and those who stay in school. A sample of 624 students who accessed the EPN leveling course (a compulsory course at the beginning of their studies) participated in the study. A total of 26.6% of the participants were women. A total of 50.7% of the participants passed the course. Data referring to social, economic, and academic variables were analyzed. Comparison techniques, as well as artificial neural networks, were used to compare characteristic profiles of students who passed the leveling course and those who dropped out. The results showed significant differences between the profiles of the students who passed and those who dropped out with regard to the variables related to previous academic performance and motivational and attributional aspects. The artificial neural networks corroborated the importance of these variables in predicting dropout. In this research, the key variables predicting whether a student continues or leaves higher education are revealed, allowing the identification of students at possible risk of dropping out and thus promoting initiatives to provide adequate academic support and improve student retention.

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Section: Discussionmentioning

confidence: 95%

Predictors of University Attrition: Looking for an Equitable and Sustainable Higher Education

et al. 2022

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“…Rather than unstructured statements, admissions committees could use structured statements focused on questions not covered elsewhere. Niessen & Neumann (2022) found higher inter-rater reliability in evaluations of structured personal statements than unstructured ones.…”

Section: Future Directionsmentioning

confidence: 86%

Worth the Weight: An Examination of Unstructured and Structured Data in Graduate Admissions

Adaryukov¹,

Biernat²,

Girard³

et al. 2023

Preprint

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In graduate admissions, as in many multiattribute decisions, evaluators must judge candidates from a flood of information, including recommendation letters, personal statements, grades, and standardized test scores. Some of this information is structured, while some is unstructured. This creates a challenge for those studying these decisions, as most theories of behavioral economics specifically focus on decisions made from highly structured information. The goal of this study was to evaluate how structured and unstructured information are used within graduate admissions decisions. We examined a uniquely comprehensive dataset of 2,231 graduate applications to the University of Kansas, containing full application packages, demographics, and final admissions decisions for each applicant. To make sense of our documents, we applied structural topic modeling, an extension of correlated topic modeling that allows topic content and prevalence to covary based on other metadata (e.g., department of study). This allowed us to examine not only what information the letters and statements contain, but also the effects of gender, race, and department on how that information was conveyed. We found that most topics in the unstructured data related to specific fields of study and were difficult to generalize outside of that field. Consequently, we found that admissions committees behaved as if they prioritized structured numeric metrics, using unstructured information to check for disqualifications if at all. Furthermore, we found that applicant race and gender influenced the prevalence of topics in their letters and statements.

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“…Patterson et al (2016b) reported that personal statements, references and unstructured interviews were inappropriate for values-based recruitment. Niessen and Neumann (2022) reported that the PS used to capture the motivation of 806 psychology students showed low inter-rater reliability and negligible predictive validity for first year GPA and dropout, with authors suggesting that time spent reading and rating the PS was wasted.…”

Section: Introductionmentioning

confidence: 99%

Evaluating shortlisting methods for admission into the social work degree: personal statement versus psychological test

Roulston

McNeill²,

Hayes³

et al. 2022

Social Work Education

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Oversubscribed social work (SW) courses and a workforce review in Northern Ireland prompted a review of admissions, to ensure recruitment of applicants with strong core values. Concerns regarding authorship, plagiarism and reliability of personal statements, and calls for values-based recruitment underpinned this research. This study evaluates psychometric properties of an SW specific personal statement (PS) and a values-based psychological screening tool, Social Work Match (SWM). Social Work students (n = 112), who commenced the 3-year undergraduate route (UGR) or the 2-year relevant graduate route (RGR) were invited to participate. Their PS scores and SWM scores permitted investigation of scoring outcomes and psychometric properties. Statistical analysis was conducted using Minitab 17. Forty-nine participants (5 male, 44 female) completed SWM on two occasions (October 2020 and January 2021). Findings provide practical, theoretical, statistical, and qualitative reasons for concluding that the PS has substantial limitations as a measure of suitability. It does not compare well with international test standards for psychometric tests. In contrast, SWM is a valid and reliable measure with good discriminatory power, standardized administration and consistent marking. SWM is a viable alternative to the PS for assessing suitability/shortlisting applicants for social work interviews.

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Using personal statements in college admissions: An investigation of gender bias and the effects of increased structure

Cited by 5 publications

References 30 publications

Predictors of University Attrition: Looking for an Equitable and Sustainable Higher Education

Predictors of University Attrition: Looking for an Equitable and Sustainable Higher Education

Worth the Weight: An Examination of Unstructured and Structured Data in Graduate Admissions

Evaluating shortlisting methods for admission into the social work degree: personal statement versus psychological test

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