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Science Education
Article . 2023 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Rolling balls or trapping ions? How students relate models to real‐world phenomena in the physics laboratory

Authors: Sebastian Kilde Löfgren; Jonathan Weidow; Jonas Enger;

Rolling balls or trapping ions? How students relate models to real‐world phenomena in the physics laboratory

Abstract

AbstractThe creation and use of models in science is of great importance for knowledge production and communication. For example, toy models are often used as idealized explanatory models in physics education. Models can be a powerful tool for exploring phenomena in ways that facilitate learning. However, careful consideration of instruction and explanations needs to be considered to guide how students relate models to real‐world phenomena in subject‐correct ways. A design experiment was conducted to investigate how upper secondary school students can use models for learning in the physics laboratory. The intervention used in the study was a laboratory exercise developed over three phases where students worked with a mechanical Paul trap and a simulation to understand the principle behind a real Paul trap. Each phase of the study consisted of three to five laboratory sessions. The data were analyzed using thematic analysis and the learning process was understood using the theoretical framework of variation theory. From the results, it was possible to identify patterns of variation for successful lab groups and critical aspects and features students need to discern to effectively modelize the mechanical Paul trap. The findings also indicate that having students work with models can be a meaningful clarificatory process to develop a deeper understanding of the use and limitations of models in science.

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    6
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Top 10%
hybrid
Beta
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