Singh Varsha, Thakral Sonika, Singh Kunal, Garg Rahul
Humanities and Social Sciences, Indian Institute of Technology Delhi, Hauz Khas, Delhi 110016, India.
National Resource Center for Value Education in Engineering, Indian Institute of Technology Delhi, Hauz Khas, Delhi 110016, India.
Trends Neurosci Educ. 2022 Mar;26:100172. doi: 10.1016/j.tine.2022.100172. Epub 2022 Jan 23.
It is unclear how cognitive control accounts for academic performance in math-intensive higher education and how it links to male over-representation in math-intensive education in gender-inequitable countries.
To examine the link between cognitive control and math-intensive education with a focus on male overrepresentation by using cognitive performance (task and construct level) to account for academic grades, and examining sex-specificity in cognitive performance (task and construct level), and using sex-differences in cognitive performance to account for academic grades.
Four hierarchical regressions were used (two using task scores and two summed scores) with predictors entered in 3 blocks (working memory, flexibility, inhibition) to explain academic performance (bootstrapped sampling at 2000 samples; N = 39; males =69%). Task-level analysis (Corsi span & mental rotation) and construct-level analysis indicate working memory as a significant predictor of grades, model-fit improved for all-male sample. Results of analysis of variance using the performance of 183 students on four cognitive tasks (N = 183; males = 81%) showed high scores of working memory task and decision-making task among male participants; female scores were higher in a task assessing planning/cognitive flexibility and in the inhibition task. Differences in the two hierarchical regressions indicated that planning/cognitive flexibility accounts for the academic performance of the male-female mixed sample; however, working memory, most importantly decision-making related to risk and uncertainty, accounts for the academic performance of the all-male sample.
Similar to developing countries, working memory and decision making might contribute to academic performance, potentially explaining male over-representation in math-intensive higher education. Academic grades might disproportionately rely on working memory and risky decision-making; equal emphasis and inclusive development of all components of cognitive control via academic curriculum and assessment might improve diversity in math-intensive higher education.
尚不清楚认知控制如何影响数学密集型高等教育中的学业成绩，以及在性别不平等的国家中，它如何与数学密集型教育中男性占比过高相关联。
通过使用认知表现（任务和结构水平）来解释学业成绩，研究认知控制与数学密集型教育之间的联系，重点关注男性占比过高的情况，并研究认知表现（任务和结构水平）中的性别特异性，以及利用认知表现中的性别差异来解释学业成绩。
使用了四个层次回归（两个使用任务分数，两个使用总分），预测变量分三个模块输入（工作记忆、灵活性、抑制）以解释学业成绩（在2000个样本上进行自助抽样；N = 39；男性 = 69%）。任务水平分析（Corsi广度和心理旋转）和结构水平分析表明工作记忆是成绩的重要预测因素，全男性样本的模型拟合得到改善。对183名学生在四项认知任务上的表现进行方差分析的结果（N = 183；男性 = 81%）显示，男性参与者在工作记忆任务和决策任务上得分较高；女性在评估计划/认知灵活性的任务和抑制任务上得分更高。两个层次回归的差异表明，计划/认知灵活性解释了男女混合样本的学业成绩；然而，工作记忆，最重要的是与风险和不确定性相关的决策，解释了全男性样本的学业成绩。
与发展中国家类似，工作记忆和决策可能有助于学业成绩，这可能解释了在数学密集型高等教育中男性占比过高的现象。学业成绩可能过度依赖工作记忆和冒险决策；通过学术课程和评估对认知控制的所有组成部分给予同等重视和包容性发展，可能会提高数学密集型高等教育的多样性。
