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Friday, October 4
Fri, Oct 4, 11:45 AM - 1:15 PM
Evergreen G
Concurrent Session - Issues in Data Science and Statistics Education

Mind the Gap: Active Learning in Undergraduate STEM Classes Narrows Achievement Gaps, but What About in Statistics Classes? (306496)

Scott Freeman, University of Washington 
*Elli Theobald, University of Washington 

Keywords: education, achievement gap, active learning, statistics

Despite widespread effort to increase access to and inclusion in STEM, women and minority students remain underrepresented in both STEM majors and STEM professions. Achievement gaps in college (i.e., differential performance between represented and under-represented students) contribute to this problem because lower performing students are more likely to drop out and less likely to major in STEM. Using two sources of evidence, we tested the hypothesis that active learning (instructional methods that promote knowledge construction) closes achievement gaps in university classes. First, from a meta-analysis of 133 studies, we find that active learning is effective across contexts (e.g., class size, course level), but when used infrequently (<30% of total class time), learning gains are equivalent to those from lecturing. Critically, statistics active learning is woefully understudied–our meta-analysis contained no statistics studies. Second, by pooling data across studies, we found that on average, active learning nearly halves gaps. In all, our work suggests that historical achievement gaps in STEM can be reduced or eliminated with evidence-based instruction.