Chemical and Biological Engineering, Colorado School of Mines, Golden, CO 80401.
Department of Earth System Sciences, University of California, Irvine, Irvine, CA 92697.
CBE Life Sci Educ. 2019 Sep;18(3):ar31. doi: 10.1187/cbe.18-12-0238.
College science courses aim to teach students both disciplinary knowledge and scientific literacy skills. Several instruments have been developed to assess students' scientific literacy skills, but few studies have reported how demographic differences may play a role. The goal of this study was to determine whether demographic factors differentially impact students' scientific literacy skills. We assessed more than 700 students using the Test of Scientific Literacy Skills (TOSLS), a validated instrument developed to assess scientific literacy in college science courses. Interestingly, we found that Scholastic Aptitude Test (SAT) reading score was the strongest predictor of TOSLS performance, suggesting that fundamental literacy (reading comprehension) is a critical component of scientific literacy skills. Additionally, we found significant differences in raw scientific literacy skills on the basis of ethnicity (underrepresented minority [URM] vs. non-URM), major (science, technology, engineering, and mathematics [STEM] vs. non-STEM), year of college (e.g., senior vs. freshman), grade point average (GPA), and SAT math scores. However, when using multivariate regression models, we found no difference based on ethnicity. These data suggest that students' aptitude and level of training (based on GPA, SAT scores, STEM or non-STEM major, and year of college) are significantly correlated with scientific literacy skills and thus could be used as predictors for student success in courses that assess scientific literacy skills.
大学理科课程旨在向学生传授学科知识和科学素养技能。已经开发出几种工具来评估学生的科学素养技能,但很少有研究报告表明人口统计学差异可能会产生什么作用。本研究的目的是确定人口统计学因素是否会对学生的科学素养技能产生不同的影响。我们使用经过验证的科学素养技能测试(TOSLS)评估了 700 多名学生,该工具旨在评估大学理科课程中的科学素养。有趣的是,我们发现学术能力倾向测验(SAT)阅读分数是 TOSLS 表现的最强预测指标,这表明基本素养(阅读理解)是科学素养技能的关键组成部分。此外,我们发现基于种族(代表性不足的少数族裔[URM]与非 URM)、专业(科学、技术、工程和数学[STEM]与非 STEM)、大学年级(例如,高年级与新生)、平均绩点(GPA)和 SAT 数学分数,学生的原始科学素养技能存在显著差异。然而,当使用多元回归模型时,我们发现种族没有差异。这些数据表明,学生的能力和培训水平(基于 GPA、SAT 分数、STEM 或非 STEM 专业以及大学年级)与科学素养技能显著相关,因此可以用作评估科学素养技能课程学生成功的预测指标。