Justyna P. Zwolak

Students' network integration as a predictor of persistence in introductory physics courses

Justyna P. Zwolak,1, 2, ∗ Remy Dou,2, 3 Eric A. Williams,4 and Eric Brewe5, 6, 1, 2, 4 STEM Transformation Institute, Florida International University, Miami, Florida 33199 Department of Teaching and Learning, Florida International University, Miami, Florida 33199 Department of Physics, University of Maryland, College Park, Maryland, 20742 Department of Physics, Florida International University, Miami, Florida 33199 Department of Physics, Drexel University, Philadelphia, PA 19104 School of Education, Drexel University, Philadelphia, PA 19104 (Dated: March 10, 2017)

Using Social Network Analysis on classroom video data

We propose a novel application of Social Network Analysis (SNA) using classroom video data as a means of quantitatively and visually exploring the collaborations between students. The context for our study was a summer program that works with first generation students and deaf/hard-of-hearing students to engage in authentic science practice and develop a supportive community. We applied SNA to data from one activity during the two-week program to test our approach and as a means to begin to assess whether the goals of the program are being met. We used SNA to identify groups that were interacting in unexpected ways and then to highlight how individuals were contributing to the overall group behavior. We plan to expand our new use of SNA to video data on a larger scale.

Assessing student reasoning in upper-division electricity and magnetism at Oregon State University

is a more challenging task. Although several research groups are currently working on such tests, their reliability and validity are still under investigation. We analyze the results of the Colorado Upper-Division Electrostatics diagnostic from Oregon State University and compare it with data from University of Colorado. In particular, we show potential shortcomings in the Oregon State University curriculum regarding separation of variables and boundary conditions, as well as uncover weaknesses of the rubric to the free response version of the diagnostic. We also demonstrate that the diagnostic can be used to obtain information about student learning during a gap in instruction. Our work complements and extends the previous ndings from the University of Colorado by highlighting important dierences in student learning that may be related to the curriculum, illuminating diculties with the rubric for certain problems and verifying decay in post-test results over time.