Abstract
Recent studies have identified an incomplete student understanding of how elastic rebound causes earthquakes. We hypothesized that realistic imaging of spatial patterns in ground motions over the course of the earthquake cycle would improve student understanding. Incorporating spatial change information in the form of both motion vectors and before-during-after contrasts should require most students to change an existing mental model or develop a new model. Using a quasi-experimental design, we developed instructional interventions for presenting variations in ground motion, including map views of fence bending and GPS velocity vectors. We measured the impact on student performance based on assignment questions related to the ground motion at different points in the earthquake cycle following several interventions in four undergraduate courses from introductory to upper level over 4 years. The first round of study was a free-response format and then multiple-choice answers were created from the most common answers, including new “worked example” questions inquiring about the reasons answers were correct or incorrect. We identified two key misconceptions based on student answer choices: (a) difficulty in recognizing velocity vector patterns when presented in a new reference frame, and (b) difficulty in reasoning that the fault must be locked for the strain to accumulate and produce an earthquake. Our analysis indicates the largest performance increases occur with simple animations that demonstrate the bending, breaking, and rebending of a fence, along with associated GPS vectors, plotted successively in different reference frames. This suggests difficulties in understanding elastic rebounds can be mitigated when spatial patterns are presented in a context with repeated opportunities to make predictions combined with animations to support mental models that connect the spatial patterns with ground movement.
Acknowledgments
This article benefited greatly from in-depth discussions with the GET-Spatial collaborative network (GET-Spatial, 2017) in addition to input from S. Graham, M. Hubenthal, D. Sumy, two peer reviewers, an associate editor, and a research editor. We are grateful to SERC for hosting the final form of the assignment and associated teaching resources. Materials provided by IRIS Consortium were used in the instruction.
Disclosure statement
The authors report there are no competing interests to declare. The views and conclusions contained in this document are those of the authors and do represent the opinions of the USGS or NSF. The data used in this study was collected under Temple IRB protocol 23869 and Miami IRB protocol 03584e.