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University of Maine
US
2 researchers0 verified2 linked papers9,807 indexed citations
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2014 · Proceedings of the National Academy of Sciences · 9,482 citations
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.
2014 · Science · 325 citations
Applying evolutionary biology to address global challenges
BACKGROUND Differences among species in their ability to adapt to environmental change threaten biodiversity, human health, food security, and natural resource availability. Pathogens, pests, and cancers often quickly evolve resistance to control measures, whereas crops, livestock, wild species, and human beings often do not adapt fast enough to cope with climate change, habitat loss, toxicants, and lifestyle change. To address these challenges, practices based on evolutionary biology can promote sustainable outcomes via strategic manipulation of genetic, developmental, and environmental factors. Successful strategies effectively slow unwanted evolution and reduce fitness in costly species or improve performance of valued organisms by reducing phenotype-environment mismatch or increasing group productivity. Tactics of applied evolutionary biology range broadly, from common policies that promote public health or preserve habitat for threatened species—but are easily overlooked as having an evolutionary rationale, to the engineering of new genomes. ADVANCES The scope and development of current tactics vary widely. In particular, genetic engineering attracts much attention (and controversy) but now is used mainly for traits under simple genetic control. Human gene therapy, which mainly involves more complex controls, has yet to be applied successfully at large scales. In contrast, other methods to alter complex traits are improving. These include artificial selection for drought- and flood-tolerant crops through bioinformatics and application of “life course” approaches in medicine to reduce human metabolic disorders. Successful control of unwanted evolution depends on governance initiatives that address challenges arising from both natural and social factors. Principal among these challenges are (i) global transfer of genes and selection agents; (ii) interlinked evolution across traditional sectors of society (environment, food, and health); and (iii) conflicts between individual and group incentives that threaten regulation of antibiotic use and crop refuges. Evolutionarily informed practices are a newer prospect in some fields and require more systematic research, as well as ethical consideration—for example, in attempts to protect wild species through assisted migration, in the choice of source populations for restoration, or in genetic engineering. OUTLOOK A more unified platform will better convey the value of evolutionary methods to the public, scientists, and decision-makers. For researchers and practitioners, applications may be expanded to other disciplines, such as in the transfer of refuge strategies that slow resistance evolution in agriculture to slow unwanted evolution elsewhere (for example, cancer resistance or harvest-induced evolution). For policy-makers, adoption of practices that minimize unwanted evolution and reduce phenotype-environment mismatch in valued species is likely essential to achieve the forthcoming Sustainable Development Goals and the 2020 Aichi Biodiversity Targets.