Our study is among the first to provide a comprehensive review of cross-national patterns of gender differences in various STEM-related constructs—achievement, beliefs, attitudes, aspirations, and participation, concerning country-level gender equality. We complement our review with empirical analyses utilizing rigorous methodologies and richer datasets from individual and country levels. Specifically, we examine gender differences in relative strength measures (e.g., strength in science relative to math and reading) and STEM aspirations and graduation, using PISA 2015 and PISA 2018 data from 78 countries/regions (N = 941,475). Our analysis corroborates our literature review, indicating that support for both the gender stratification hypothesis and the gender equality paradox (i.e., whether gender gaps favoring male students are smaller or larger in more gender-equal countries) is generally inconsistent and weak. Various factors contribute to this inconsistency, including specific outlier countries, different years of data collection, diverse data sources, a range of composite and domain-specific measures of gender equality, and statistical models. Our study also introduces a robust statistical model to compare performances in three subjects and evaluate the predictive power of relative strength measures for STEM aspirations at the student level. Our analyses reveal that general academic achievement and math achievement relative to reading are key predictors of STEM aspirations, compared with science achievement relative to math and reading. By juxtaposing both levels of analysis, our findings offer a more nuanced understanding of gender differences in decision-making processes that lead to careers in STEM-related fields.

我们的研究是第一个对各种 STEM 相关结构（涉及国家层面性别平等的成就、信念、态度、愿望和参与）中性别差异的跨国模式进行全面审查的研究之一。我们利用严格的方法和来自个人和国家层面的更丰富的数据集进行实证分析来补充我们的审查。具体来说，我们使用来自 78 个国家/地区的 PISA 2015 和 PISA 2018 数据（ N = 941,475 ），研究相对优势指标（例如，科学相对于数学和阅读的优势）以及 STEM 愿望和毕业方面的性别差异。我们的分析证实了我们的文献综述，表明对性别分层假说和性别平等悖论（即，在性别更加平等的国家中，有利于男学生的性别差距是更小还是更大）的支持通常不一致且薄弱。造成这种不一致的因素有很多，包括特定的异常国家、不同年份的数据收集、不同的数据源、一系列综合和特定领域的性别平等衡量标准以及统计模型。我们的研究还引入了一个强大的统计模型来比较三个科目的表现，并评估相对强度指标对学生层面 STEM 抱负的预测能力。我们的分析表明，与数学和阅读相关的科学成就相比，与阅读相关的一般学术成就和数学成就是 STEM 抱负的关键预测因素。通过并列两个层面的分析，我们的研究结果让我们对决策过程中的性别差异有了更细致的了解，而这些差异会导致 STEM 相关领域的职业发展。