Evidence map›Paper›PMID 39418171›Full record

ArticleCBE life sciences education2024

A Multi-institutional Cluster Analysis to Identify Groups of Courses with Exemplary Opportunity Gaps for Undergraduate Students in the Biological Sciences.

Kameryn Denaro, Marco Molinaro, Stefano Fiorini, Rebecca L Matz, Chris Mead, Meryl Motika, Nita Tarchinski, Montserrat Valdivia Medinaceli, W Carson Byrd, Benjamin Koester and 3 more

Abstract read
In one paragraph

Article in CBE life sciences education, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Kameryn DenaroDivision of Teaching Excellence and Innovation, University of California, Irvine, CA 92697.
Marco MolinaroTeaching and Learning Transformation Center - Educational Effectiveness, University of Maryland, College Park, MD 20742.
Stefano FioriniResearch And Analytics, Institutional Analytics, UITS, Indiana University, Bloomington, IN 47401.
Rebecca L MatzCenter for Academic Innovation, University of Michigan, Ann Arbor, MI 48104.
Chris MeadSchool of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287.
Meryl MotikaOffice of the Vice Chancellor for Student Affairs, University of California, Berkeley, CA 94720.
Nita TarchinskiUndergraduate Education, College of Literature, Science, and the Arts, University of Michigan, Ann Arbor, MI 48109.
Montserrat Valdivia MedinaceliNeurobiology, Physiology and Behavior, University of California, Davis, CA 95616.
W Carson ByrdCenter for the Study of Higher and Postsecondary Education, University of Michigan, Ann Arbor, MI 48109.
Benjamin KoesterCenter for the Study of Higher and Postsecondary Education, University of Michigan, Ann Arbor, MI 48109.
Hye Rin LeeCollege of Education and Human Development, University of Delaware, Newark, DE 19716.
Timothy McKayDepartments of Physics and Astronomy, College of Literature, Science, and the Arts, and School of Education, University of Michigan, Ann Arbor, MI 48109.
Brian K SatoDepartment of Molecular Biology and Biochemistry and Division of Teaching Excellence and Innovation, University of California, Irvine, CA 92697.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Examining institutional data from seven cohorts of students intending to major in biology across five research-intensive institutions, this work analyzes opportunity gaps-defined as the difference between the grade received by students from the dominant and nondominant sociodemographic groups in institutions of higher education-at the course-section level across mathematics, physics, biology, and chemistry disciplines. From this analysis, we find that the majority of course sections have large opportunity gaps between female and male students, students who are Black, Latino/a/e/x, or indigenous to the United States and its territories and students who are White or Asian, first-generation and non-first-generation students, and low-income and non-low-income students. This work provides a framework to analyze equity across institutions using robust methodology, including: using multiple approaches to measure grades, quantile regression rankscores which adjust for previous academic performance, and cluster analysis. Recommendations are provided for institutions to identify faculty who have equitable course sections, automate equity analyses, and compare results to other institutions to make a change toward more equitable outcomes.

Indexed as

StudentsBiological Science DisciplinesCluster AnalysisCurriculumEducational MeasurementFemaleHumansMaleUniversities

Identifiers

PMID39418171
PMCPMC11659849

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.