ArticleJournal of microbiology & biology education2023
Classification of Features across Five CURE Networks Reveals Opportunities to Improve Course Design, Instruction, and Equity.
Article in Journal of microbiology & biology education, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
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Who cites it
3 citing papers in PubMed.
- Evaluating gains in student self-efficacy in scientific literacy associated with a brief curricular intervention.Journal of microbiology & biology education · 2025Article
- Unveiling Undergraduate Research: Employing Ecological Momentary Assessment to Characterize and Compare Undergraduate Research Experiences.CBE life sciences education · 2025Article
- Faculty perceptions of a professional development program for developing CUREs and promoting inclusive and equitable teaching.Journal of microbiology & biology education · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Course-based undergraduate research experiences (CUREs) are tools used to introduce students to authentic participation in science. Several specific CUREs have been shown to benefit students' interest and retention in the biological sciences. Nevertheless, CUREs vary greatly in terms of their context, methodology, and degree of research authenticity, so different types of CUREs may differently influence student outcomes. This programmatic diversity poses a challenge to educators who want to better understand which course components and features are reliably present in a CURE curriculum. To address these issues, we identified, catalogued, and classified 112 potential features of CUREs across the biosciences. To develop the list, we interviewed instructors experienced with teaching individual and large networked CUREs across a diversity of the biological disciplines, including: Squirrel-Net (field-based animal behavior), SEA-PHAGES (wet lab microbiology and computational microbiology), Tiny Earth (environmental and wet lab microbiology), PARE (environmental microbiology), and the Genomics Education Partnership (eukaryotic computational biology). Twenty-five interviewees contributed expert content in terms of CURE features and classification of those items into an organized list. The resulting list's categories encompasses student experiences with the following: (i) the scientific process; (ii) technical aspects of science; (iii) the professional development associated with research; and (iv) building scientific identity. The most striking insight was that CUREs vary widely in terms of which features they contain, since different CUREs will by necessity have different approaches to science and student involvement. We also identified several features commonly thought to be crucial to CUREs yet have ambiguous definitions. This ambiguity can potentially confound efforts to make CUREs research-authentic and aligned with the central goals of science. We disambiguate these terms and represent their varied meanings throughout the classification. We also provide instructor-friendly supplementary worksheets along with considerations for instructors interested in expanding their CURE course design, instruction, and equity.
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Registered trials
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.