Network positions in active learning environments in physics
Abstract
This study uses positional analysis to describe the student interaction networks in four research-based introductory physics curricula. Positional analysis is a technique for simplifying the structure of a network into blocks of actors whose connections are more similar to each other than to the rest of the network. This method describes social structure in a way that is comparable between networks of different sizes and densities and can show large-scale patterns such as hierarchy or brokering among actors. We detail the method and apply it to class sections using Peer Instruction, SCALE-UP, ISLE, and context-rich problems. At the level of detail shown in the blockmodels, most of the curricula are more alike than different, showing a late-term tendency to form coherent subgroups that communicate actively among themselves but have few inter-position links. This pattern may be a network signature of active learning classes, but wider data collection is needed to investigate.
Cite
@article{arxiv.2004.06446,
title = {Network positions in active learning environments in physics},
author = {Adrienne L. Traxler and Tyme Suda and Eric Brewe and Kelley Commeford},
journal= {arXiv preprint arXiv:2004.06446},
year = {2020}
}
Comments
17 pages, 10 figures; supplemental 10 pages, 9 figures