PERC 2025 Abstract Detail Page
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| Abstract Title: | Evaluating recognition and recall formats of social network surveys in physics education research |
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| Abstract Type: | Contributed Poster Presentation |
| Abstract: | An increasing number of studies in physics education research use social network analysis to quantify interactions among students. These studies typically gather data through online surveys using one of two different survey formats: recognition, where students select peers' names from a provided course roster, and recall, where students type their peers' names from memory as an open response. These survey formats, however, may be subject to two possible systematic errors. First, students may report more peers' names on a recognition survey than a recall survey because the course roster facilitates their memory of their interactions, whereas they may only remember a subset of their interactions on the recall format. Second, recognition surveys may be subject to name order effects, where students are more likely to select peers' names that appear early on in the roster than those that appear later on (e.g., due to survey fatigue). Here we report the results of two methodological studies of these possible errors in the context of introductory physics courses: one directly comparing 65 student responses to recognition and recall versions of the same network survey prompt, and the other measuring name order effects on 54 recognition surveys from 27 different courses. We find that students may report more peer interactions on a recognition survey than a recall survey and that most recognition surveys are not subject to significant name order effects. These results help to inform survey design for future network studies in physics education research. |
| Footnote: | This material is based upon work supported by the National Science Foundation under Grant No. 2111128. |
| Session Time: | Poster Session C |
| Poster Number: | C-101 |
| Contributed Paper Record: | Contributed Paper Information |
| Contributed Paper Download: | Download Contributed Paper |
Author/Organizer Information | |
| Primary Contact: |
Meagan Sundstrom Drexel University Philadelphia, PA 19103 Phone: 5083330167 |
| Co-Author(s) and Co-Presenter(s) |
Justin Gambrell, Michigan State University Adrienne L. Traxler, University of Copenhagen Eric Brewe, Drexel University |
