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Proceedings of the National Academy of Sciences· 2014Q1· Meta-analysis

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

Scott Freeman, Sarah L. Eddy, Miles McDonough, Michelle K. Smith et al.

Short summary

A meta-analysis of 225 studies reveals that active learning methods significantly improve student performance in STEM courses, increasing average exam scores by 6% and reducing failure rates compared to traditional lecturing.

AI-generated from the title and abstract; the full text is not read.

Key points

  • Active learning boosts average STEM exam scores by 6% compared to traditional lectures.
  • Students in active learning classes are 1.5 times less likely to fail.
  • Improvements were consistent across STEM fields and class sizes.
  • Active learning showed greater gains on concept inventories than course exams.

AI-generated from the title and abstract; the full text is not read.

Abstract

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.

The authors' abstract, as published at the source. Proceedings of the National Academy of Sciences, 2014 · DOI ↗

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Field: Education

EducationSocial Sciences