The DOI matches its Crossref record.
Modeling theory applied: Modeling Instruction in introductory physics
Abstract
Modeling Instruction is a pedagogical approach which has been widely and successfully employed in high school physics instruction but is not commonly used at the university level. The goal of this paper is to describe the nature of Modeling Instruction at the university level and to clarify the role of models in physics instruction. A university physics class is described as it progresses through a typical modeling cycle, Introduction and Representation, Coordination of Representations, Abstraction and Generalization, and Application and Refinement. The benefits of modeling instruction are discussed.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Singer, S., & Smith, K. A. (2013) · Journal of Engineering Education · doi:10.1002/jee.20030 · Cited by 835
Synthesis of discipline-based education research in physics
Docktor, J. L., & Mestre, J. P. (2014) · Physical Review Special Topics - Physics Education Research · doi:10.1103/physrevstper.10.020119 · Cited by 549
Henderson, C., Dancy, M., & Niewiadomska-Bugaj, M. (2012) · Physical Review Special Topics - Physics Education Research · doi:10.1103/physrevstper.8.020104 · Cited by 322
Price, E., Lau, A. C., Goldberg, F., Turpen, C., Smith, P. S., Dancy, M., & Robinson, S. (2021) · International Journal of STEM Education · doi:10.1186/s40594-020-00268-7 · Cited by 60
Improving performance in quantum mechanics with explicit incentives to correct mistakes
Brown, B. R., Mason, A., & Singh, C. (2016) · Physical Review Physics Education Research · doi:10.1103/physrevphyseducres.12.010121 · Cited by 59
Metadata
- Authors
- Brewe, E.
- Venue
- American Journal of Physics
- Published
- 2008-12-01
- Volume
- 76
- Issue
- 12
- Pages
- 1155-1160
- ISSN
- 0002-9505 (ISSN-L)
- 1943-2909
- OpenAlex
- W1974170782
- Cited by
- 210
- References
- 0
- FWCI
- 18.60
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Modeling theory applied: Modeling Instruction in introductory physics. https://app.cochat.ai/papers/10.1119/1.2983148
- The paper
- Brewe, E. (2008). Modeling theory applied: Modeling Instruction in introductory physics. American Journal of Physics. https://doi.org/10.1119/1.2983148
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
