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.
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- Original journal
- Journal of applied research in memory and cognition
- Published
- 2021-11-08
- DOI
- 10.1037/h0101870
- Open record
- PMC9254563
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