Evidence map›Paper›PMID 35119948›Full record

ArticleCBE life sciences education2022

Improving Students' Understanding of Biological Variation in Experimental Design and Analysis through a Short Model-Based Curricular Intervention.

Jessica Dewey, Jenna Hicks, Anita Schuchardt

Open access · diamondAbstract read
In one paragraph

Article in CBE life sciences education, 2022. 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
0.7field-weighted citation impact, top 30% of its field
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, 3 citations in OpenAlex.

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 at 2 institutions in 1 country.

Jessica DeweyBiology Department, Syracuse University, Syracuse, NY 13244.
Jenna HicksOffice of Professional Development, University of Minnesota, Minneapolis, MN 55455.
Anita SchuchardtDepartment of Biology Teaching and Learning, University of Minnesota, Minneapolis, MN 55455.
University of Minnesota · USSyracuse University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

When conducting biological investigations, experts constantly integrate their conceptual and quantitative understanding of variation with the design and analysis of the investigation. This process is difficult for students, because curricula often treat these concepts as separate components. This study describes the effect of a curricular intervention aimed at improving students' conceptual and quantitative understanding of variation in the context of experimental design and analysis. A model-based intervention curriculum consisting of five short modules was implemented in an introductory biology laboratory course. All students received the regular laboratory curriculum, and half of the students also received the Intervention curriculum. Students' understanding of variation was assessed using a published 16-question multiple-choice instrument designed and validated by the research team. Students were assessed before and after the intervention was implemented, and normalized gain scores were calculated. Students who received the intervention showed significantly higher normalized gains than students who did not receive the intervention. This effect was not influenced by students' gender or exposure to prior statistics courses and persisted into and through the following semester's laboratory course. These results provide support for the use of model-based approaches to improve students' understanding of biological variation in experimental design and analysis.

Indexed as

Research DesignStudentsCurriculumHumans

Identifiers

PMID35119948
PMCPMC9250365
OpenAlexW4210285264

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.