Abstract:In the current study, we investigated windows for enhanced learning of cognitive skills during adolescence. Six hundred thirty-three participants (11–33 years old) were divided into four age groups, and each participant was randomly allocated to one of three training groups. Each training group completed up to 20 days of online training in numerosity discrimination (i.e., discriminating small from large numbers of objects), relational reasoning (i.e., detecting abstract relationships between groups of items), … Show more
“…Either reducing working memory load, decreasing time constraints, or training working memory and fluid ability capacity in such populations may therefore be promising lines of inquiry for intervention studies. It is worth highlighting, however, that cognitive training studies have so far shown little evidence of (far) transfer: Training abstract reasoning, a common measure of g f , has not resulted in robust increases in working memory (Knoll et al 2016) and working memory training has not been shown to transfer to reasoning skills or school performance (Dunning et al 2013; Schwaighofer et al 2015). Similarly, transfer from processing speed to reasoning seems to be limited (Mackey et al 2011).…”
12Fluid intelligence is the capacity to solve novel problems in the absence of task-specific 13 knowledge, and is highly predictive of outcomes like educational attainment and 14 psychopathology. Here, we modelled the neurocognitive architecture of fluid intelligence in 15 two cohorts: CALM (N = 551, aged 5 -17 years) and ). We 16 used multivariate Structural Equation Modelling to test a preregistered watershed model of 17 fluid intelligence. This model predicts that white matter contributes to intermediate cognitive 18 phenotypes, like working memory and processing speed, which, in turn, contribute to fluid 19 intelligence. We found that this model performed well for both samples and explained large 20 amounts of variance in fluid intelligence (R 2 CALM = 51.2%, R 2 NKI-RS = 78.3%). The relationship 21 between cognitive abilities and white matter differed with age, showing a dip in strength 22 around ages 7 -12 years. This age-effect may reflect a reorganization of the neurocognitive 23 architecture around pre-and early puberty. Overall, these findings highlight that intelligence 24 is part of a complex hierarchical system of partially independent effects. 25 Keywords 26 Working memory, processing speed, fractional anisotropy, watershed model, structural 27 equation modeling 28 Fluid intelligence (g f ) is a core part of human cognition and refers to the capacity to solve 29 novel problems in the absence of task-specific knowledge. It is highly predictive of a number 30 of important life span outcomes, including educational attainment (Primi et al. 2010; Roth et 31 al. 2015) and psychopathology (Gale et al. 2010). Despite years of investigation, however, our 32 understanding of the neurocognitive architecture of g f remains limited. Longstanding debates 33 have considered, for instance, how g f relates to more fundamental cognitive functions such 34 as working memory and processing speed, and how all of these cognitive functions relate to 35 brain structure and function (Kyllonen and
“…Either reducing working memory load, decreasing time constraints, or training working memory and fluid ability capacity in such populations may therefore be promising lines of inquiry for intervention studies. It is worth highlighting, however, that cognitive training studies have so far shown little evidence of (far) transfer: Training abstract reasoning, a common measure of g f , has not resulted in robust increases in working memory (Knoll et al 2016) and working memory training has not been shown to transfer to reasoning skills or school performance (Dunning et al 2013; Schwaighofer et al 2015). Similarly, transfer from processing speed to reasoning seems to be limited (Mackey et al 2011).…”
12Fluid intelligence is the capacity to solve novel problems in the absence of task-specific 13 knowledge, and is highly predictive of outcomes like educational attainment and 14 psychopathology. Here, we modelled the neurocognitive architecture of fluid intelligence in 15 two cohorts: CALM (N = 551, aged 5 -17 years) and ). We 16 used multivariate Structural Equation Modelling to test a preregistered watershed model of 17 fluid intelligence. This model predicts that white matter contributes to intermediate cognitive 18 phenotypes, like working memory and processing speed, which, in turn, contribute to fluid 19 intelligence. We found that this model performed well for both samples and explained large 20 amounts of variance in fluid intelligence (R 2 CALM = 51.2%, R 2 NKI-RS = 78.3%). The relationship 21 between cognitive abilities and white matter differed with age, showing a dip in strength 22 around ages 7 -12 years. This age-effect may reflect a reorganization of the neurocognitive 23 architecture around pre-and early puberty. Overall, these findings highlight that intelligence 24 is part of a complex hierarchical system of partially independent effects. 25 Keywords 26 Working memory, processing speed, fractional anisotropy, watershed model, structural 27 equation modeling 28 Fluid intelligence (g f ) is a core part of human cognition and refers to the capacity to solve 29 novel problems in the absence of task-specific knowledge. It is highly predictive of a number 30 of important life span outcomes, including educational attainment (Primi et al. 2010; Roth et 31 al. 2015) and psychopathology (Gale et al. 2010). Despite years of investigation, however, our 32 understanding of the neurocognitive architecture of g f remains limited. Longstanding debates 33 have considered, for instance, how g f relates to more fundamental cognitive functions such 34 as working memory and processing speed, and how all of these cognitive functions relate to 35 brain structure and function (Kyllonen and
“…This, in turn, is followed by a significantly higher focus on and capability for divergence in late childhood and adolescence. 47,49,50 It is not entirely clear, however, whether this extends to all domains of life or is restricted to, for instance, social interactions. 15 What role does material culture play here?…”
Section: Cross-culturally Children Find Ways Of Incorporating Play Imentioning
In this contribution, we address a major puzzle in the evolution of human material culture: If maturing individuals just learn their parental generation's material culture, then what is the origin of key innovations as documented in the archeological record? We approach this question by coupling a life‐history model of the costs and benefits of experimentation with a niche‐construction perspective. Niche‐construction theory suggests that the behavior of organisms and their modification of the world around them have important evolutionary ramifications by altering developmental settings and selection pressures. Part of Homo sapiens' niche is the active provisioning of children with play objects — sometimes functional miniatures of adult tools — and the encouragement of object play, such as playful knapping with stones. Our model suggests that salient material culture innovation may occur or be primed in a late childhood or adolescence sweet spot when cognitive and physical abilities are sufficiently mature but before the full onset of the concerns and costs associated with reproduction. We evaluate the model against a series of archeological cases and make suggestions for future research.
“…Given the continuing development of language and communication in adolescence, the window of opportunity for improving cognitive function is much wider than once thought (Knoll et al . ).…”
Section: Introductionmentioning
confidence: 97%
“…While interventions for language and communication difficulties have been found to have moderate to large effect sizes in primary school children, there is limited research into the effectiveness of interventions in secondary school students (Cirrin and Gillam 2008). Given the continuing development of language and communication in adolescence, the window of opportunity for improving cognitive function is much wider than once thought (Knoll et al 2016).…”
Background
Although language and communication difficulties are common in secondary school students, there has been limited research into the efficacy of interventions for adolescents with language and communication difficulties.
Aims
To investigate the efficacy of teaching assistant (TA)‐delivered narrative and vocabulary interventions to mainstream secondary school‐aged students with language disorder.
Methods & Procedures
A randomized controlled trial (RCT) of a language and communication intervention was used to evaluate the efficacy of vocabulary and narrative interventions to improve the vocabulary and narrative performance of adolescents (mean age = 12.8 years) with language disorder. The language and communication programmes (narrative, vocabulary and combined narrative and vocabulary) were delivered by TAs in the classroom, three times per week, for 45–60 min each, over 6 weeks, totalling 18 sessions. Standardized and intervention‐specific measures were used as outcomes.
Outcomes & Results
Twenty‐one schools with 358 eligible participants were recruited. The three intervention groups showed significant improvements (
d
= .296) on a narrative latent variable defined by a standardized narrative assessment (the Expression, Reception and Recall of Narrative Instrument—ERRNI), but there were no significant improvements on an overall vocabulary latent variable compared with the waiting control group. Differential effects were found on some non‐standardized intervention‐specific measures with the narrative group making significantly more progress on narrative tasks compared with the waiting control group, the vocabulary group showing the same pattern on specific vocabulary tasks, and the combined narrative and vocabulary group making significantly more progress on some of the intervention‐specific narrative, and all the intervention‐specific vocabulary outcomes compared with the waiting control group.
Conclusions & Implications
It is possible to improve narrative but not vocabulary skills, as assessed by standardized measures, in secondary school students with a relatively brief group TA‐delivered intervention. There were differential effects for both narrative and vocabulary with intervention‐specific measures. Future work is required to explore whether more intensive and longer lasting interventions would be more effective and to identify which students in this age group are most likely to benefit from such interventions.
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