Evidence map›Paper›PMID 30631678›Full record

ArticleInternational journal of STEM education2017

How personal, behavioral, and environmental factors predict working in STEMM vs non-STEMM middle-skill careers.

Matthew A Cannady, Debra Moore, Elizabeth Votruba-Drzal, Eric Greenwald, Regie Stites, Christian D Schunn

Abstract read
In one paragraph

Article in International journal of STEM education, 2017. 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. Socioeconomic gaps in science achievement.International journal of STEM education · 2018
    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

6 authors.

Matthew A Cannady1Lawrence Hall of Science, University of California Berkeley, Berkeley, CA 94709 USA.ORCID 0000-0002-7256-3131
Debra Moore2University of Pittsburgh, Pittsburgh, PA USA.
Elizabeth Votruba-Drzal2University of Pittsburgh, Pittsburgh, PA USA.
Eric Greenwald1Lawrence Hall of Science, University of California Berkeley, Berkeley, CA 94709 USA.
Regie Stites3SRI International, Palo Alto, CA USA.
Christian D Schunn2University of Pittsburgh, Pittsburgh, PA USA.ORCID 0000-0003-3589-297X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMuch of science, technology, engineering, mathematics, and medical (STEMM) education policy and research centers around developing the upper levels of the STEMM workforce sector. However, there are many positions in this workforce, "middle-skill careers," that are largely responsible for executing the innovations and are largely ignored in STEMM education research.

resultsUsing data from the National Educational Longitudinal Study of 1988, we found differences in what predicts STEMM-related vs. non-STEMM careers across skill-level. For instance, underrepresented minorities and those exhibiting school transgressions are more likely to be working in middle-skill STEMM fields than in middle-skill non-STEMM fields as adults; the same is not true of the high-skill workforce.

conclusionsOne-size-fits-all policies for broadening participation in the STEMM workforce across skill-level are unlikely to be successful. Further, programs that are designed to generate wonder and fascination with STEMM content may be successful in attracting more girls. However, to promote greater participation of individuals from traditionally underrepresented ethnic minority groups in STEMM, programs that support choices toward higher educational attainment, specifically four-year college degree attainment, are more likely to be successful.

Indexed as

Middle-skillSTEMM careerSTEMM educationSTEMM workforce

Identifiers

PMID30631678
PMCPMC6310473

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.