Physical Review Physics Education Research

A description of the ontological assumptions, epistemological commitments, and methodological implications for three basic genres of quantitative research.

Using focus group and interview data from quantitative PER experts to identify areas of improvement, the authors examine to what extent these issues exist in published PER work.

The process of encoding data plays an essential role in the subsequent analysis, yet many authors provide little information about how their data were encoded.

The importance of publishing null results in physics education research.

Students with greater numbers of outgoing interactions express less anxiety about physics and certain grouping strategies might support decreased anxiety.

Comparisons between analyses using complete cases and multiple imputation show that researchers can make qualitatively different conclusions in quantitative research studies.

Modeled responses to the Conceptual Survey in Electricity and Magnetism demonstrate that a wider variety of conceptual ideas are present than discussed in the original design.

Hierarchal linear modeling is argued to often be a better analytic technique than single-level models.

Long-term implications from quantitative education data can be inferred using short-term data through regression-corrected grouping.

Education research data often do not meet the assumptions for linear regression models; other analysis models must be used.

Rasch modeling may facilitate better quantitative physics education instrument development and use.

Two cluster analysis methods applied to highlight researcher choices in how each method impacts results.