Characterizing active learning environments in physics using latent profile analysis

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

Characterizing active learning environments in physics using latent profile analysis. / Commeford, Kelley; Brewe, Eric; Traxler, Adrienne.

In: Physical Review Physics Education Research, Vol. 18, No. 1, 010113, 2022.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Commeford, K, Brewe, E & Traxler, A 2022, 'Characterizing active learning environments in physics using latent profile analysis', Physical Review Physics Education Research, vol. 18, no. 1, 010113. https://doi.org/10.1103/PhysRevPhysEducRes.18.010113

APA

Commeford, K., Brewe, E., & Traxler, A. (2022). Characterizing active learning environments in physics using latent profile analysis. Physical Review Physics Education Research, 18(1), [010113]. https://doi.org/10.1103/PhysRevPhysEducRes.18.010113

Vancouver

Commeford K, Brewe E, Traxler A. Characterizing active learning environments in physics using latent profile analysis. Physical Review Physics Education Research. 2022;18(1). 010113. https://doi.org/10.1103/PhysRevPhysEducRes.18.010113

Author

Commeford, Kelley ; Brewe, Eric ; Traxler, Adrienne. / Characterizing active learning environments in physics using latent profile analysis. In: Physical Review Physics Education Research. 2022 ; Vol. 18, No. 1.

Bibtex

@article{ea4aff00d2b341d39cccbf537c8fee4a,
title = "Characterizing active learning environments in physics using latent profile analysis",
abstract = "The vast majority of research involving active learning pedagogies uses passive lecture methods as a baseline. We propose to move beyond such comparisons to understand the mechanisms that make different active learning styles unique. Here, we use COPUS observations to record student and instructor activities in six known styles of active learning in physics, and use latent profile analysis to classify these observations. Latent profile analysis using two profiles successfully groups COPUS profiles into interactive lecturelike and other. Five latent profiles successfully sorts observations into interactive lecturelike, Modeling Instruction, ISLE labs, context-rich problems labs, and recitationlike or discussionlike. This analysis serves as a proof of concept, and suggests instructional differences across pedagogies that can be further investigated using this method.",
author = "Kelley Commeford and Eric Brewe and Adrienne Traxler",
year = "2022",
doi = "10.1103/PhysRevPhysEducRes.18.010113",
language = "English",
volume = "18",
journal = "Physical Review Physics Education Research",
issn = "2469-9896",
publisher = "American Physical Society",
number = "1",

}

RIS

TY - JOUR

T1 - Characterizing active learning environments in physics using latent profile analysis

AU - Commeford, Kelley

AU - Brewe, Eric

AU - Traxler, Adrienne

PY - 2022

Y1 - 2022

N2 - The vast majority of research involving active learning pedagogies uses passive lecture methods as a baseline. We propose to move beyond such comparisons to understand the mechanisms that make different active learning styles unique. Here, we use COPUS observations to record student and instructor activities in six known styles of active learning in physics, and use latent profile analysis to classify these observations. Latent profile analysis using two profiles successfully groups COPUS profiles into interactive lecturelike and other. Five latent profiles successfully sorts observations into interactive lecturelike, Modeling Instruction, ISLE labs, context-rich problems labs, and recitationlike or discussionlike. This analysis serves as a proof of concept, and suggests instructional differences across pedagogies that can be further investigated using this method.

AB - The vast majority of research involving active learning pedagogies uses passive lecture methods as a baseline. We propose to move beyond such comparisons to understand the mechanisms that make different active learning styles unique. Here, we use COPUS observations to record student and instructor activities in six known styles of active learning in physics, and use latent profile analysis to classify these observations. Latent profile analysis using two profiles successfully groups COPUS profiles into interactive lecturelike and other. Five latent profiles successfully sorts observations into interactive lecturelike, Modeling Instruction, ISLE labs, context-rich problems labs, and recitationlike or discussionlike. This analysis serves as a proof of concept, and suggests instructional differences across pedagogies that can be further investigated using this method.

U2 - 10.1103/PhysRevPhysEducRes.18.010113

DO - 10.1103/PhysRevPhysEducRes.18.010113

M3 - Journal article

VL - 18

JO - Physical Review Physics Education Research

JF - Physical Review Physics Education Research

SN - 2469-9896

IS - 1

M1 - 010113

ER -

ID: 332195465