Evidence map›Paper›PMID 38516055›Full record

ArticlePolicy insights from the behavioral and brain sciences2024

Catalyzing Equity in STEM Teams: Harnessing Generative AI for Inclusion and Diversity.

Nia Nixon, Yiwen Lin, Lauren Snow

Abstract read
In one paragraph

Article in Policy insights from the behavioral and brain sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Nia NixonUniversity of California, Irvine, California, USA.ORCID https://orcid.org/0000-0002-9839-8947
Yiwen LinUniversity of California, Irvine, California, USA.ORCID https://orcid.org/0000-0003-3602-8454
Lauren SnowUniversity of California, Irvine, California, USA.

Funding

Grassroots Rigor: making rigorous research practices accessible, meaningful, and building a community around themUC2NS128361 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI Konrad P. Kording · 2022 to 2026
$13.8M
NINDS NIH HHS UC2 NS128361
6 · The paper itself

Abstract

Collaboration is key to STEM, where multidisciplinary team research can solve complex problems. However, inequality in STEM fields hinders their full potential, due to persistent psychological barriers in underrepresented students' experience. This paper documents teamwork in STEM and explores the transformative potential of computational modeling and generative AI in promoting STEM-team diversity and inclusion. Leveraging generative AI, this paper outlines two primary areas for advancing diversity, equity, and inclusion. First, formalizing collaboration assessment with inclusive analytics can capture fine-grained learner behavior. Second, adaptive, personalized AI systems can support diversity and inclusion in STEM teams. Four policy recommendations highlight AI's capacity: formalized collaborative skill assessment, inclusive analytics, funding for socio-cognitive research, human-AI teaming for inclusion training. Researchers, educators, and policymakers can build an equitable STEM ecosystem. This roadmap advances AI-enhanced collaboration, offering a vision for the future of STEM where diverse voices are actively encouraged and heard within collaborative scientific endeavors.

Indexed as

collaborative problem-solvingdiversity in STEMgenerative artificial intelligencenatural language processingSTEM inclusion

Identifiers

PMID38516055
PMCPMC10950550

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.