Active learning increases student performance in science, engineering, and mathematics.

To test the hypothesis that lecturing maximizes learning and course performance, we metaanalyzed 225 studies that reported data on examination scores or failure rates when comparing student performance in undergraduate science, technology, engineering, and mathematics (STEM) courses under traditional lecturing versus active learning. The effect sizes indicate that on average, student performance on examinations and concept inventories increased by 0.47 SDs under active learning (n = 158 studies), and that the odds ratio for failing was 1.95 under traditional lecturing (n = 67 studies). These results indicate that average examination scores improved by about 6% in active learning sections, and that students in classes with traditional lecturing were 1.5 times more likely to fail than were students in classes with active learning. Heterogeneity analyses indicated that both results hold across the STEM disciplines, that active learning increases scores on concept inventories more than on course examinations, and that active learning appears effective across all class sizes--although the greatest effects are in small (n ≤ 50) classes. Trim and fill analyses and fail-safe n calculations suggest that the results are not due to publication bias. The results also appear robust to variation in the methodological rigor of the included studies, based on the quality of controls over student quality and instructor identity. This is the largest and most comprehensive metaanalysis of undergraduate STEM education published to date. The results raise questions about the continued use of traditional lecturing as a control in research studies, and support active learning as the preferred, empirically validated teaching practice in regular classrooms.

Crowdsourced Data Indicate Widespread Multidrug Resistance in Skin Flora of Healthy Young Adults.

In a laboratory exercise for undergraduate biology majors, students plated bacteria from swabs of their facial skin under conditions that selected for coagulase-negative Staphylococcus; added disks containing the antibiotics penicillin, oxacillin, tetracycline, and erythromycin; and measured zones of inhibition. Students also recorded demographic and lifestyle variables and merged this information with similar data collected from 9,000 other students who had contributed to the database from 2003 to 2011. Minimum inhibitory concentration (MIC) testing performed at the Harborview Medical Center Microbiology Laboratory (Seattle, WA) indicated a high degree of accuracy for student-generated data; species identification with a matrix-assisted laser desorption ionization (MALDI) Biotyper revealed that over 88% of the cells analyzed by students were S. epidermidis or S. capitus. The overall frequency of resistant cells was high, ranging from 13.2% of sampled bacteria resistant to oxacillin to 61.7% resistant to penicillin. Stepwise logistic regressions suggested that recent antibiotic use was strongly associated with resistance to three of the four antibiotics tested (p = 0.0003 for penicillin, p << 0.0001 for erythromycin and tetracycline), and that age, gender, use of acne medication, use of antibacterial soaps, or makeup use were associated with resistance to at least one of the four antibiotics. Furthermore, drug resistance to one antibiotic was closely linked to resistance to the other three antibiotics in every case (all p values << 0.0001), suggesting the involvement of multidrug-resistant strains. The data reported here suggest that citizen science could not only provide an important educational experience for undergraduates, but potentially play a role in efforts to expand antibiotic resistance (ABR) surveillance.