Mareva Silvana, Holmes Joni
Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge.
J Appl Res Mem Cogn. 2022 Jun;11(2):209-217. doi: 10.1037/h0101870. Epub 2021 Nov 8.
Mutualistic theories assume that the mastering of a skill, either cognitive or academic, supports and amplifies the development of other such abilities. The current study uses network science to model cross-sectional associations between cognitive and academic performance in two age-matched developmental cohorts. One cohort was a community sample drawn from the general school population, while the other included struggling learners. The community sample outperformed the struggling learners across all measures. Network models suggested that although the tasks were similarly interrelated across cohorts, there were some notable differences in association strength: Academic skills were more closely coupled in the community sample, while maths was more strongly related to cognitive skills in the struggling learners. We demonstrate the utility of network models as an analytic framework that is consistent with contemporary theories of learning difficulties and the nature of the relationship between cognitive and learning skills more broadly.
共生理论认为，掌握一项技能，无论是认知技能还是学术技能，都会支持并促进其他此类能力的发展。本研究运用网络科学对两个年龄匹配的发展队列中认知表现与学业成绩之间的横断面关联进行建模。一个队列是从普通学校人群中抽取的社区样本，另一个队列则包括学习困难的学生。在所有测量指标上，社区样本的表现均优于学习困难的学生。网络模型表明，尽管各队列中的任务相互关联方式相似，但在关联强度上存在一些显著差异：在社区样本中，学术技能之间的联系更为紧密，而在学习困难的学生中，数学与认知技能的关联更为强烈。我们证明了网络模型作为一种分析框架的实用性，它与当代关于学习困难的理论以及更广泛意义上认知技能与学习技能之间关系的本质是一致的。
