Evidence map›Paper›PMID 34970383›Full record

ArticleJournal of microbiology & biology education2021

The Conceptualization of Quantitative Reasoning among Introductory Biology Faculty.

Ann Cleveland, Asli Sezen-Barrie, Gili Marbach-Ad

Open access · goldAbstract read
In one paragraph

Article in Journal of microbiology & biology education, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.2field-weighted citation impact, top 46% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

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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 3 institutions in 1 country.

Ann ClevelandCorning School of Ocean Studies, Maine Maritime Academy, Castine, Maine, USA.ORCID https://orcid.org/0000-0001-6270-2030
Asli Sezen-BarrieSchool of Learning and Teaching, Research in STEM Education (RISE) Center, University of Maine, Orono, Maine, USA.
Gili Marbach-AdCollege of Computer, Mathematical and Natural Sciences, University of Maryland, College Park, Maryland, USA.
Corning (United States) · USUniversity of Maine · USUniversity of Maryland, College Park · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantitative reasoning (QR) skills have become a critical competency for undergraduate biology students, and recommendations for curricular reform urge QR training throughout undergraduate biology programs. Much research has been directed at course design, pedagogy, and student challenges in QR, but less research has been directed toward understanding how biology faculty conceptualize the QR skills they are called upon to teach. We conducted in-depth, semistructured interviews with 15 participants teaching introductory biology courses to learn how faculty conceptualize QR at the introductory level. Using phenomenology, responses were coded to establish inductive codes. We found that two themes emerged from the coded conceptualizations: sophisticated, cognitively complex QR skills and basic QR skills. Participants placed emphasis on the more complex QR skills as being important in the undergraduate curriculum, beginning at the introductory level. Participants' conceptualizations of QR aligned with skills called for in curriculum reform, but the perceived notion of "basic" for some skills may not align with the literature. This suggests that more is needed in aligning faculty conceptualization of QR with curriculum, pedagogy, and assessment.

Indexed as

BioSkills guidefaculty perspectiveintroductory biologyquantitative reasoningVision and Change

Identifiers

PMID34970383
PMCPMC8672876
OpenAlexW4206318170

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.