Authors:
Kathy Lea Malone
1
and
Anita Schuchardt
2
Affiliations:
1
Graduate School of Education, Nazarbayev University, Kabanbay Batyr 53, Astana, 01000 and Kazakhstan
;
2
Department of Biology Education, University of Minnesota, Minneapolis, MN, 53455 and U.S.A.
Keyword(s):
Modelling Instruction, Science Modelling, Simulations, Population Growth, Scientific Reasoning.
Related
Ontology
Subjects/Areas/Topics:
Active Learning
;
Computer-Supported Education
;
e-Learning
;
Game-Based and Simulation-Based Learning
;
Learning/Teaching Methodologies and Assessment
;
Pattern Recognition
;
Theory and Methods
Abstract:
Internationally, students have difficulty interpreting and drawing conclusions from data. These skills are essential components of scientific reasoning, an ability that has been shown to correlate with conceptual change. Providing greater opportunities for students to engage in scientific practices such as modelling in order to collect and reason with data has the potential to improve scientific reasoning skills. However, in some subdisciplines of biology, such as population growth, data collection needs to occur over time scales that are unfeasible in a classroom setting. Computer-based simulations of biological phenomena are one way to overcome this limitation, but their effect on scientific reasoning has been under investigated. This study researched the effect on scientific reasoning of computer-based simulations in a context that employed a specific type of model-based reasoning (Modelling Instruction). Students who used computer-based simulations in a Modelling Instruction cont
ext showed increased scientific reasoning post-instruction compared to a comparison group. Moreover, shifts were observed in the intervention group towards more formal reasoning whereas no such change was observed with the comparison group. This result suggests that computer-based simulations should be further explored as a way to improve student scientific reasoning, particularly in contexts where laboratory investigations are not feasible.
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