Confidence Disparities: Pre-course Coding Confidence Predicts Greater Statistics Intentions and Perceived Achievement in a Project-Based Introductory Statistics Course

JOURNAL OF STATISTICS AND DATA SCIENCE EDUCATION(2024)

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摘要
Self-efficacy is associated with a range of educational outcomes, including science and math degree attainment. Project-based statistics courses have the potential to increase students' math self-efficacy because projects may represent a mastery experience, but students enter courses with preexisting math self-efficacy. This study explored associations between pre-course math confidence and coding confidence with post-course statistical intentions and perceived achievement among students in a project-based statistics course at 28 private and public colleges and universities between fall 2018 and winter 2020 (n = 801) using multilevel mixed-effects multivariate linear regression within multiply imputed data with a cross-validation approach (testing n = 508 at 20 colleges/universities). We found that pre-course coding confidence was associated with, respectively, 9 points greater post-course statistical intentions and 10 points greater perceived achievement on a scale 0-100 (0.09, 95% confidence interval (0.02, 0.17), p = 0.02; 0.10, 95% CI (0.01, 0.19), p = 0.04), and that minoritized students have greater post-course statistical intentions than nonminoritized students. These results concur with past research showing the potential effectiveness of the project-based approach for increasing the interest of minoritized students in statistics. Pre-course interventions to increase coding confidence such as pre-college coding experiences may improve students' post-course motivations and perceived achievement in a project-based course. for this article are available online.
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关键词
Math,Passion-driven statistics,Programming,Self-efficacy,Statistics education
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