Cumulative centrality plots Non-traditional students’ conceptual scores and network centrality in SCALE-UP classes Emily N. Sandt, Adrienne L. Traxler Department of Physics, Wright State University Email: adrienne.traxler@wright.edu Goals Compare different models of network influence and FCI scores for non-traditional and traditional students in three differently sized SCALE-UP classes. Research questions: Do centrality values of non-traditional students show different trends than traditional students? Does class size have an effect on the amount of networking and conceptual gains students make? Figure 1: Network diagrams and cumulative centrality plots for Dataset B. Preliminary results Non-traditional students begin the class with lower degree centrality (fewer connections), but make connections throughout the class to reach comparable closeness values in Dataset B (pictured). Other datasets show that all NT centrality values are lower than traditional values. As class sized increased, non-traditional students’ FCI gains increased and traditional students’ FCI gains decreased, so class size appeared to have an effect on the amount of learning that occurs. (Significant difference in Dataset C.) One measure of centrality is not enough. Different measures of centrality provided different trends in the network. Motivation and background Social network analysis utilizes several different measures to describe a node’s position (centrality) [1]. Non-traditional (NT) students (age 22+) tend to have fewer on-campus connections and lower retention rates than traditional (Trad) students [2]. Social connections toward other students have consequences for long-term retention [3]. Higher centrality values have been linked to future success [4]. Cumulative centrality plots Degree (bottom left) plot shows non-traditional students consistently have fewer connections than traditional students. Closeness (bottom right) plot shows that non-traditional students begin with lower closeness values than traditional students but end with comparable closeness values. Methods Pre- and post-course data: Network survey question: “Who do you work with to learn physics in this class?” Force concept inventory (FCI) as success measure Course: Calculus-based physics I, SCALE-UP format Analyzed degree, betweenness, and closeness centrality Compared FCI scores and gains for NT/Trad students Significant results FCI and post-course centrality values with significant differences between NT and traditional students. [Mean (standard error)] Table 1: Number of students by NT/Trad status in each dataset. Table 2: Results for FCI and post-course centrality. Pre-Course Post-Course Dataset Student Type Enrolled FCI Network A NT 36 8 10 29 6 Trad 17 18 11 21 B 70 15 71 9 41 51 46 C 125 124 7 97 107 98 Dataset Measure NT Value Trad Value B FCI Post 12 (1) 15 (1) C Degree 1.5 (0.5) 3.3 (0.3) Betweenness 0.006 (0.003) 0.22 (0.003) FCI Gain 7 (2) 2.5 (0.6) Work in progress Repeat this study with additional class sections to see if trends in class size recur. Analyze additional centrality measures to determine if one measure gives a more complete picture of the network than those presented here. Do non-traditional students primarily network with other non-traditional students? [1] Kolaczyk, E. D., & Csárdi, G. (2014). Statistical analysis of network data with R (pp. 1-5). New York, NY: Springer. [2] Gilardi, S., & Guglielmetti, C. (2011). University life of non-traditional students: Engagement styles and impact on attrition. The Journal of Higher Education, 82(1), 33-53. [3] Tinto, V. (1997). Classrooms as communities: Exploring the educational character of student persistence. Journal of higher education, 599-623. [4] Bruun, J., & Brewe, E. (2013). Talking and learning physics: Predicting future grades from network measures and Force Concept Inventory pretest scores. Physical Review Special Topics-Physics Education Research, 9(2), 020109.