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Building mental models by dissecting physical models
Author(s) -
Srivastava Anveshna
Publication year - 2015
Publication title -
biochemistry and molecular biology education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.34
H-Index - 39
eISSN - 1539-3429
pISSN - 1470-8175
DOI - 10.1002/bmb.20921
Subject(s) - conceptual model , mental model , psychological intervention , computer science , test (biology) , measure (data warehouse) , structural equation modeling , mathematics education , psychology , machine learning , ecology , cognitive science , biology , data mining , database , psychiatry
When students build physical models from prefabricated components to learn about model systems, there is an implicit trade‐off between the physical degrees of freedom in building the model and the intensity of instructor supervision needed. Models that are too flexible, permitting multiple possible constructions require greater supervision to ensure focused learning; models that are too constrained require less supervision, but can be constructed mechanically, with little to no conceptual engagement. We propose “model‐dissection” as an alternative to “model‐building,” whereby instructors could make efficient use of supervisory resources, while simultaneously promoting focused learning. We report empirical results from a study conducted with biology undergraduate students, where we demonstrate that asking them to “dissect” out specific conceptual structures from an already built 3D physical model leads to a significant improvement in performance than asking them to build the 3D model from simpler components. Using questionnaires to measure understanding both before and after model‐based interventions for two cohorts of students, we find that both the “builders” and the “dissectors” improve in the post‐test, but it is the latter group who show statistically significant improvement. These results, in addition to the intrinsic time‐efficiency of “model dissection,” suggest that it could be a valuable pedagogical tool. © 2015 by The International Union of Biochemistry and Molecular Biology, 44:7–11, 2016.