The Conceptualization of Quantitative Reasoning among Introductory Biology Faculty.

BioSkills guide Vision and Change faculty perspective introductory biology quantitative reasoning

Journal

Journal of microbiology & biology education
ISSN: 1935-7877
Titre abrégé: J Microbiol Biol Educ
Pays: United States
ID NLM: 101543341

Informations de publication

Date de publication:
Dec 2021
Historique:
received: 19 07 2021
accepted: 10 11 2021
entrez: 31 12 2021
pubmed: 1 1 2022
medline: 1 1 2022
Statut: epublish

Résumé

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.

Identifiants

pubmed: 34970383
doi: 10.1128/jmbe.00203-21
pii: jmbe00203-21
pmc: PMC8672876
pii:
doi:

Types de publication

Journal Article

Langues

eng

Informations de copyright

Copyright © 2021 Cleveland et al.

Déclaration de conflit d'intérêts

The authors declare no conflict of interest.

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Auteurs

Ann Cleveland (A)

Corning School of Ocean Studies, Maine Maritime Academy, Castine, Maine, USA.

Asli Sezen-Barrie (A)

School of Learning and Teaching, Research in STEM Education (RISE) Center, University of Maine, Orono, Maine, USA.

Gili Marbach-Ad (G)

College of Computer, Mathematical and Natural Sciences, University of Maryland, College Park, Maryland, USA.

Classifications MeSH