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Undergraduate biology students view scientific models as easy‐to‐learn simple explanations
Author(s) -
Trujillo Caleb,
Bennett Steve,
Long Tammy
Publication year - 2018
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.2018.32.1_supplement.535.36
Subject(s) - mathematics education , inclusion (mineral) , scientific modelling , perception , exploratory research , simple (philosophy) , scientific writing , psychology , computer science , epistemology , sociology , social psychology , philosophy , art , literature , neuroscience , anthropology
The inclusion of modeling in undergraduate science classrooms is warranted so that students engage in authentic scientific practices to understand the world. This study investigates students' perceptions of modeling by asking: what attributes do introductory biology students associate with scientific models? We conducted an exploratory mixed methods study with participants recruited from model‐based introductory biology courses across two interviews. During the first interview, students provided attributes of models including definitions, purposes, and qualities. An inductive analysis revealed that most students viewed models as explanatory visual representations that aid learning. During the second interview one year later, the same students assigned identified attributes to different representations in a sorting task. A correspondence analysis revealed that learners closely associate scientific models to simplistic easy‐to‐learn explanations, but not to data or predictions. The results suggest that students associate scientific models with explanations that aid learning by making complex content simple and comprehensible. Conversely, students perceive the attributes of empirical support and predictive power as distinct from scientific models. This study furthers an understanding of students' perspectives of models in a biology classroom and informs potential changes to model‐based instruction. Support or Funding Information This material is based upon work supported by the National Science Foundation under Grant No. DRL 1420492. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .