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      Four guiding principles for effective trainee-led STEM community engagement through high school outreach

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          Abstract

          To address ongoing academic achievement gap, there is a need for more school-university partnerships promoting early access to STEM education. During summer 2020, members of our institute initiated QBio-EDGE (Quantitative Biology—Empowering Diversity and Growth in Education), an outreach program for high schools in Los Angeles. In the hope of contributing to increasing diversity in academia, QBio-EDGE aims to make STEM education more accessible for students from historically excluded communities by exposing them to scientific research and diverse scientist role models. This program is led by early career researchers (ECRs), i.e., undergraduate, graduate, and postdoctoral researchers. In our first year, the outreach activities took place during virtual learning, presenting challenges and opportunities within the program development. Here, we provide a practical guide outlining our outreach efforts, key factors we considered in the program development, and hurdles we overcame. Specifically, we describe how we assembled our diverse team, how we established trusting partnerships with participating schools, and how we designed engaging student-centered, problem-based classroom modules on quantitative biology and computational methods applications to understand living systems. We also discuss the importance of increased institutional support. We hope that this may inspire researchers at all career stages to engage with local schools by participating in science outreach, specifically in quantitative and computational fields. We challenge institutions to actively strengthen these efforts.

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          Most cited references33

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          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.
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            Increased structure and active learning reduce the achievement gap in introductory biology.

            Science, technology, engineering, and mathematics instructors have been charged with improving the performance and retention of students from diverse backgrounds. To date, programs that close the achievement gap between students from disadvantaged versus nondisadvantaged educational backgrounds have required extensive extramural funding. We show that a highly structured course design, based on daily and weekly practice with problem-solving, data analysis, and other higher-order cognitive skills, improved the performance of all students in a college-level introductory biology class and reduced the achievement gap between disadvantaged and nondisadvantaged students--without increased expenditures. These results support the Carnegie Hall hypothesis: Intensive practice, via active-learning exercises, has a disproportionate benefit for capable but poorly prepared students.
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              Teachers, Race, and Student Achievement in a Randomized Experiment

              Thomas Dee (2004)
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Project administrationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: Project administrationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Project administrationRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: VisualizationRole: Writing – review & editing
                Role: Project administrationRole: ResourcesRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Project administrationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Comput Biol
                PLoS Comput Biol
                plos
                PLOS Computational Biology
                Public Library of Science (San Francisco, CA USA )
                1553-734X
                1553-7358
                25 May 2023
                May 2023
                : 19
                : 5
                : e1011072
                Affiliations
                [1 ] Institute for Quantitative and Computational Biosciences, University of California, Los Angeles, Los Angeles, California, United States of America
                [2 ] Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, Los Angeles, California, United States of America
                [3 ] Synergy Quantum Academy, Los Angeles, California, United States of America
                SIB Swiss Institute of Bioinformatics, SWITZERLAND
                Author notes

                The authors have declared that no competing interests exist.

                [¤]

                Current address: Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California, United States of America

                Author information
                https://orcid.org/0000-0001-5320-8110
                https://orcid.org/0000-0002-6308-346X
                https://orcid.org/0000-0002-5746-6480
                https://orcid.org/0000-0003-3992-5767
                Article
                PCOMPBIOL-D-22-01110
                10.1371/journal.pcbi.1011072
                10212071
                296d69b5-dc86-435a-be48-bba3b65137fd
                © 2023 Luecke et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Page count
                Figures: 3, Tables: 1, Pages: 13
                Funding
                Funded by: Institute for Quantitative and Computational Biosciences, University of California Los Angeles
                The authors received financial support from the Institute for Quantitative and Computational Biosciences at UCLA for food provided during the campus tours. The funders had no role in the program design, data collection and analysis, decision to publish, or preparation of the manuscript.
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