AI Brief: Aligning AI agents with developmentally appropriate CHC (select) cognitive domains—a thought provoking AI approach for school-age children and youth

 The source article is an arXiv open-access article available here.  I have no idea if it has undergone peer-review and is a pre-print or if it is working draft paper.  

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Dr. Kevin McGrew with major assist from Google NotebookLM.  (Click here for brief explanation of how IQs Corner creates AI Alerts from article PDFs)

ChildAgentEval, a psychometrically grounded benchmark designed to evaluate how well artificial intelligence aligns with the cognitive development of children and youth. Inspired by the Wechsler Intelligence Scale for Children-IV four-factor CHC model (the study does not use actual WISC-IV items as per test security standards), this framework assesses multimodal AI agents across ten interactive subtests covering the CHC domains like working memory (Gwm), verbal abstraction and vocabulary (Gc), fluid-visual spatial reasoning (Gf/Gv), and processing speed (Gs).

The study reveals that standard prompting—simply asking an AI to "act like a child"—does not authentically replicate pediatric developmental cognition, as models often maintain adult-level reasoning. The authors introduced a skill-guided distillation strategy that applies data-driven filters to simulate age-appropriate cognitive constraints and limitations. While AI agents can successfully adapt their vocabulary, the research highlights significant challenges in mimicking human-like bottlenecks in perceptual processing and memory retention. 

ChildAgentEval is the first psychometrically grounded interactive benchmark designed to measure cognitive age alignment in multimodal large language model (MLLM) agents. The study addresses a critical gap in current AI development: while state-of-the-art agents excel at complex reasoning, they often do not scaffold learning within a child's Zone of Proximal Development, often using adult-level abstractions that exceed a young user's cognitive grasp. The authors advocate for a shift in AI development from maximizing raw capability to ensuring developmental appropriateness for young users (e.g., school-age children and youth)—a feature that is much needed if AI is to be used in with school-age children and youth. 

The ChildAgentEval Framework

Inspired by the Wechsler Intelligence Scale for Children (WISC-IV), the benchmark evaluates agents across ten interactive subtests mapped to four primary CHC cognitive factors:

• Crystallized Intelligence (Gc): Verbal abstraction and vocabulary.
• Fluid and Visual-Spatial Reasoning (Gf/Gv): Rule induction and spatial problem-solving.
• Working Memory (Gwm): Information retention and manipulation.
• Processing Speed (Gs): Quickness of visual scanning and timed execution.

Unlike static evaluations, ChildAgentEval utilizes a Playwright-driven browser environment where agents must perform physical actions like clicking and typing to solve tasks. The framework also implements clinical protocols such as reversal and discontinuation rules to ensure developmental validity.

Skill-Guided Distillation

A core contribution of the research is a data-driven skill distillation strategy that moves beyond simple "act like a child" prompts. By analyzing a multi-source corpus of real child and adolescent interactions (ages 6–17), the researchers developed cognitive profile vectors. These vectors are converted into executable constraints via five cognitive filter modules injected into the agent's prompt, memory, and reasoning layers:

1. Vocabulary Abstraction Filter: Limits academic concepts and controls syntactic complexity.
2. Working Memory Mask: Physically simulates shorter memory spans by injecting noise or restricting cross-page information.
3. Reasoning Budget Controller: Restricts the depth of multi-step logic.
4. Visual Reliance Module: Reproduces cognitive biases, such as being misled by physical arrangement illusions.
5. Social Perspective Filter: Restricts reasoning to age-appropriate viewpoints, such as first-person vs. institutional perspectives.

Key Findings and Experimental Results

The study evaluated several proprietary models (e.g., GPT-5.4, Gemini-3.1-Pro) and open-weight models (e.g., Qwen3.5-27B). The experiments revealed three major insights:

• Standard Prompting Fails: Merely asking an agent to "act younger" does not reliably change its underlying cognitive behavior; most models continue to maximize correctness regardless of the requested age.
• Skill Guidance Enables Alignment: In high-performing proprietary models, the distillation method successfully induced monotonic score trajectories, where performance expanded naturally as the target age increased—the results produced performances associated with developmental growth curves of cognitive abilities.
• Uneven Domain Alignment: While agents easily adapted their linguistic style (Gc), they struggled to authentically simulate human-like limits in working memory and perceptual reasoning. This "domain dissociation" suggests that MLLM architectures currently lack the structural developmental bottlenecks found in biological cognition.

Conclusion

The authors conclude that for sensitive applications like educational tutoring, technical correctness must be secondary to developmental appropriateness. ChildAgentEval establishes a new paradigm for AI safety and alignment, shifting the focus from maximizing raw capability to authentic cognitive simulation.

Research alert: Intriguing new “adaptive habits” executive function framework differentiating EF capacity and willingness to engage EF - #cognitive #intelligence #schoolpsychologists #schoolpsychology

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This thought-provoking article, which proposes and explains the “adaptive habits” executive functioning framework, is an open access article (free download and read) 

 

Abstract

Executive functions (EFs) develop dramatically across childhood and predict important outcomes, including academic achievement. These links are often attributed to individual differences in EF capacities. However, individual difference accounts underemphasize contextual influences on EF. We propose a complementary perspective, the adaptive habits framework, which emphasizes how contextual factors support or hinder EF engagement in children. Contexts that support repeated EF engagement establish habits for engaging EF in similar contexts and in similar ways. Such habits, in turn, reduce the effort associated with engaging EF and thus increase the likelihood of deciding to en-gage EF in the future. We interpret empirical findings through the lens of adaptive habits, discuss the implications of this framework, and propose novel research approaches and interventions to support EF in children.

From Conclusion

Why do children (such as the two in our opening example) differ in their academic and EF task performance? The reviewed evidence demonstrates that such differences should be viewed as a product of distinct learning histories, sociocultural influences, and environmental contexts in-stead of solely as differences in EF capacities. The adaptive habits framework emphasizes how contextual factors influence children's decisions to engage EF and how such engagement (or its absence) supports the development of habits that make it easier (or harder) to engage EF in similar contexts or for similar rewards in the future. Thus, two children may have the same EF capacities; however, one child may perform better on standard measures of EF because these measures better align with how the child has practiced engaging EF in the real world and how their behaviors have been rewarded and reinforced, which in turn reduces the mental effort needed for engaging EF. The adaptive habits framework thus identifies these contextual factors as promising targets for future research on EF as well as for interventions to support the EF and academic achievement of children.

[Do] Humans peak in midlife [?]: A combined #cognitive and #personality trait perspective - #intelligence #developmental #schoolpsychologists #schoolpsychology #CHC

Open access copy of article can be downloaded here.

 Highlights

• •
  Age trends reviewed across 16 key cognitive and personality-related dimensions.
• •
  All variables plotted on a common scale to enable direct cross-domain comparisons.
• •
  Age trajectories varied widely: some traits declined, others improved with age.
• •
  A weighted composite index of functioning was developed from theory and evidence.
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  Overall cognitive-personality functioning peaks between ages 55 and 60.

Abstract

Fluid intelligence, which peaks near age 20 and declines materially across adulthood, is often regarded as the most critical cognitive ability for predicting important life outcomes. Yet, human achievement in domains such as career success tends to peak much later, typically between the ages of 55 and 60. This discrepancy may reflect the fact that, while fluid intelligence may decline with age, other dimensions improve (e.g., crystallized intelligence, emotional intelligence). To examine this possibility, we analyzed age-related trends across nine constructs associated with life success: cognitive abilities, personality traits, emotional intelligence, financial literacy, moral reasoning, resistance to sunk cost bias, cognitive flexibility, cognitive empathy, and need for cognition. We extracted age-related findings from published studies for each dimension and standardized all scores to T-scores for comparability. We then constructed a Cognitive-Personality Functioning Index (CPFI) and compared two weighting approaches: a Conventional model, emphasizing intelligence and core personality traits, and a Comprehensive model, integrating a broader array of dimensions. Both models revealed a peak in overall functioning during late midlife (ages 55 to 60) but diverged at the younger and older ends of adulthood: under Conventional weighting, older adults scored well below young adults, whereas under Comprehensive weighting, the two groups were roughly equivalent. These findings suggest that functional capacity, defined in terms of key differential psychological traits, may peak in late midlife, closely aligning with the typical peak in career achievement. Also, individuals best suited for high-stakes decision-making roles are unlikely to be younger than 40 or older than 65.

Research Byte: #Cognitive #aging revisited: A cross-sectional analysis of the #WAIS-5 - #intelligence #developmental #cognition #schoolpsychologists #WAISV #schoolpsychology

Cognitive Aging Revisited: A Cross-Sectional Analysis of  the WAIS-5 

Emily L. Winter, Brittany A. Dale, Sachiko Maharjan, Cynthia R. Lando, Courtney M. Larsen,  Troy Courville and Alan S. Kaufman  

An open access article that can be read or downloaded at this link.

Abstract 

Historical cross-sectional approaches examining cognitive aging consistently reveal a pat-tern of steady decline on nonverbal problem-solving, speeded tasks, and maintenance on verbal tasks. However, as measures developed and broadened the factor structure to align with Cattell–Horn–Carroll (CHC) theory, and age ranges were extended from 75 to 90 years, a more nuanced approach to cognitive aging emerged. The present study, using the Wechsler Adult Intelligence Scale, Fifth Edition (WAIS-5), examined the cognitive aging process through a cross-sectional approach. WAIS-5 normative sample data (aligned with the 2022 U.S. census) were obtained from the test publisher. The sample included adult participants aged 20–24 through 85–90 (n = 1660), which were mapped into 11 age groups. Using post-stratification weighting to control for educational attainment, cognitive decline was observed throughout aging; verbal skills were maintained longer than other abilities, while processing speed declined steadily and rapidly from young adulthood to old age. Working memory was vulnerable to the aging process but demonstrated slower patterns of decline than the other vulnerable abilities. Fluid reasoning and visual spatial skills (although aligning with separate CHC broad abilities theoretically) were strikingly similar in their pattern of decline across a person's lifespan. Results are highly consistent with the large body of cross-sectional research conducted during the previous generation by Salthouse and his colleagues, as well as other teams of researchers. 

Keywords: cognitive aging; WAIS-5; cross-sectional design; verbal abilities; nonverbal abilities 

Research Byte: The #cultural construction of #executivefunction - EF tasks reflect culturally-specific forms of #cognitive development - #cognition #schoolpsychology #schoolpsychologists #neuropsych

The cultural construction of “executive function”.  PNAS:  Research Article:  Psychological and Cognitive Sciences.  This is open access and can be downloaded or read online.  Link here.

Ivan Kroupin , Helen Elizabeth Davis, Emily Burdette, Agustina Bani Cuataf, Vahumburuka Hartley, and Joseph Henrich

Abstract

In cognitive science, the term “executive function” (EF) refers to universal features of the mind. Yet, almost all results described as measuring EF may actually reflect culturally specific cognitive capacities. After all, typical EF measures require forms of decontextualized/arbitrary processing which decades of cross-cultural work indicate develop primarily in “schooled worlds”–industrialized societies with universal schooling. Here, we report comparisons of performance on typical EF tasks by children inside, and wholly outside schooled worlds. Namely, children ages 5 to 18 from a postindustrial context with universal schooling (UK) and their peers in a rural, nonindustrialized context with no exposure to schooling (Kunene region, Namibia/Angola), as well as two samples with intermediate exposure to schooled worlds. In line with extensive previous work on decontextualized/arbitrary processing across such groups, we find skills measured by typical EF tasks do not develop universally: Children from rural groups with limited or no formal schooling show profound, sometimes qualitative, differences in performance compared to their schooled peers and, especially, com-pared to a “typical” schooled-world sample. In sum, some form of latent cognitive control capacities are obviously crucial in all cultural contexts. However, typical EF tasks almost certainly reflect culturally specific forms of cognitive development. This suggests we must decide between using the term EF to describe 1) universal capacities or 2) the culturally specific skill set reflected in performance on typical tasks. Either option warrants revisiting how we understand what has been measured as EF to date, and what we wish to measure going forward.

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Research Byte: A longitudinal study of adolescent-to-young adult #executivefunction development in seven countries - #cognition #selfregulation #schoolpsychology #neuropsychology #developmental

A Longitudinal Study of Adolescent-to-Young Adult Executive Function Development in Seven Countries.  Developmental Science.  Sorry, this is not an open access article you can download

Abstract

Executive functioning (EF) is an important developing self-regulatory process that has implications for academic, social, and emotional outcomes. Most work in EF has focused on childhood, and less has examined the development of EF throughout adolescence and into emerging adulthood. The present study assessed longitudinal trajectories of EF from ages 10 to 21 in a diverse, international sample. 1093 adolescents (50.3% female) from eight locations in seven countries completed computerized EF tasks (Stroop, Tower of London [ToL], Working Memory [WM]) at ages 10, 14, 17, and 21. Latent growth curve models were estimated to understand the average performance at age 10 and the change in performance over time for each task. Meta-analytic techniques were used to assess the heterogeneity in estimates between study sites. On average, EF task performance improved across adolescence into young adulthood with substantial between-site heterogeneity. Additionally, significant individual differences in EF task performance at age 10 and change in EF task performance over time characterized the full sample. EF improves throughout adolescence into young adulthood, making it a potentially important time for intervention to improve self-regulation.

New National Acadamies Report on ”The future of #youth #development: Building #Systems and Strengthening #Programs”

 Downloadable here.

Research Byte: Development of #Arithmetic Across the #Lifespan: A Registered Report. - #Gq #CHC #Gwm #EF #Gs #schoolpsychology #SPED #SLD

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Development of Arithmetic Across the Lifespan: A Registered Report.  

Open access paper available at Developmental Psychology journal.  Click here to access

Abstract

 

Arithmetic skills are needed at any age. In everyday life, children to older adults calculate and deal with numbers. The processes underlying arithmetic seem to change with age. From childhood to younger adulthood, children get better in domain-specific numerical skills such as place-value processing. From younger to older adulthood, domain-general cognitive skills such as working memory decline. These skills are needed for complex arithmetic such as addition with carrying and subtraction with borrowing. This study investigates how the domain-specific (number magnitude, place-value processing) and domain-general (working memory, processing speed, inhibition) processes of arithmetic change across the lifespan. Thereby, arithmetic effects (carry and borrow effects), numerical effects (distance and compatibility effects), and cognitive skills were assessed in children, younger and older adolescents, and younger, middle-aged and older adults. The results showed that numerical and arithmetic skills improve from childhood to young adulthood and remain relatively stable throughout adulthood, even though domain-general pro-cesses, particularly working memory and processing speed, decline with age. While number magnitude and place-value processing both develop until adulthood, number magnitude processing shows deficits during aging, whereas place-value processing remains intact even in old age. The carry effect shifts from a categorical all-or-none decision (whether or not a carry operation is needed) to a more continuous magnitude process in adulthood, reflecting increasing reliance on domain-specific skills. In contrast, the borrow effect remains largely categorical across all age groups, depending on general cognitive processes. These results provide critical insights into how arithmetic skills change over the lifespan, relying on both domain-specific and domain-general processes.

Public Significance Statement 

Numerical and arithmetic skills improve significantly during school and are mostly preserved throughout adulthood—despite a decline in cognitive skills such as working memory and processing speed during aging. When facing complex arithmetic, all—from children up to older adults—need longer to calculate, but lifelong experience helps in dealing with arithmetic complexity. Throughout the lifespan, arithmetic requires both cognitive skills as well as numeric skills.

National Academies Press downloadable PDF publicaiton on #cognitive #aging - #developmental #cognitive #cognition

 Click here for more info and ability to download a free copy.

Institute of Medicine. 2015. Cognitive Aging: Progress in Understanding and Opportunities for Action. Washington, DC: The National Academies Press. https://doi.org/10.17226/21693.

Research Byte: Age-related change in #inhibitory processes when controlling for #workingmemory (#Gwm) capacity and #processingspeed (#Gs) - #cognition #intelligence #CHC #executivefunctions #Gwm #Gs #schoolpsychology

 

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This is a nice study/paper.  And it is open access and can be downloaded for reading by clicking here.

I recommend reading, if not the entire article, at least the introductory lit review.  The introductory lit review is worth a read if one wants to understand the basic literature re the definition, theories, and research regarding the relations between cognitive inhibition, working memory capacity (Gwm), and processing speed (Gs) in a developmental context.  

Abstract

The main purpose of this study was to examine the age-related changes in inhibitory control of 450 children at the ages of 7–8, 11–12, and 14–16 when controlling for working memory capacity (WMC) and processing speed to determine whether inhibition is an independent factor far beyond its possible reliance on the other two factors. This examination is important for several reasons. First, empirical evidence about age-related changes of inhibitory control is controversial. Second, there are no studies that explore the organization of inhibitory functions by controlling for the influence of processing speed and WMC in these age groups. Third, the construct of inhibition has been questioned in recent research. Multigroup confirmatory analyses suggested that inhibition can be organized as a one-dimension factor in which processing speed and WMC modulate the variability of some inhibition tasks. The partial reliance of inhibitory processes on processing speed and WMC demonstrates that the inhibition factor partially explains the variance of inhibitory tasks even when WMC and processing speed are controlled and some methodological concerns are addressed.

Book Nook: #Presidential age and #intelligence. #Executivefunctions and the #executive office

Talk about timely…given all the talk about the age of our current (Trump) and prior (Biden) presidents.  

About this book (from publisher web page)

This book on presidential age is not about Alzheimer's Disease and associated pathologies of the aging brain. It is instead about the normally aging brain. Brains don’t simply develop and maintain their functionality into older adulthood unless otherwise impaired by neurocognitive disease. Were this the case, this book might be about leveraging prodromal biomarkers of neurodegenerative diseases to screen prospective presidential candidates. Instead, the normal decline age brings to all human brains begs a different type of book—and a broader and more blanketed warning about electing increasingly older presidents.

Table of contents below.  It is clear from the breadth of coverage that this is a serious attempt to corral critical age-related cognitive abilities research in the context of executive decision making (e.g., being President)…which makes it clear that the assessment of intelligence is well beyond the quick and very limited MoCA screener that our current president likes to brag (incorrectly) about as an indication of his great intelligence.  

The book is due out the first week of March, 2025.  Thus, I have not read any of the chapters upon which to base an opinion.  I shall be ordering a copy.

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How to keep your memory as you age: Annual Review of Psychology

Annual Review of Psychology: Successful Memory Aging. Article link.

Lars Nyberg and Sara Pudas

Abstract

For more than 50 years, psychologists, gerontologists, and, more recently, neuroscientists have considered the possibility of successful aging. How to define successful aging remains debated, but well-preserved age-sensitive cognitive functions, like episodic memory, is an often-suggested criterion. Evidence for successful memory aging comes from cross-sectional and lon-gitudinal studies showing that some older individuals display high and sta-ble levels of performance. Successful memory aging may be accomplished via multiple paths. One path is through brain maintenance, or relative lack of age-related brain pathology. Through another path, successful memory aging can be accomplished despite brain pathology by means of efficient compensatory and strategic processes. Genetic, epigenetic, and lifestyle fac-tors influence memory aging via both paths. Some of these factors can be promoted throughout the life course, which, at the individual as well as the societal level, can positively impact successful memory aging.

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Stability of intelligence from infancy through adolescence

Stability of intelligence from infancy through adolescence: An autoregressive latent variable model (article link)

Huihui Yua, D. Betsy McCoach, Allen W. Gottfriedc, Adele Eskeles Gottfriedd

a Yale University, United States b University of Connecticut, United States c Fullerton Longitudinal Study, California State University, Fullerton, United States d California State University, Northridge, United States

A B S T R A C T

This study examined the stability of the latent construct of intelligence from infancy through adolescence, using latent variable modeling to account for measurement error. Based on the Fullerton Longitudinal Study data, the present study modeled general intelligence across four developmental periods from infancy through adolescence. The Fullerton Longitudinal Study included twelve assessments of intellectual performance over a sixteen-year interval. Three assessments of intellectual performance at each of four developmental periods served as in-dicators of latent intelligence during infancy (1, 1.5, and 2 years old), preschool (2.5, 3, and 3.5 years old), childhood (6, 7, and 8 years old), and adolescence (12, 15, and 17 years old). Intelligence exhibited a high degree of stability across the four developmental periods. For instance, infant intelligence revealed a strong cross-time correlation with preschool intelligence (r = 0.91) and moderate correlations with childhood and adolescent intelligence (r = 0.69 and 0.57, respectively). Intelligence followed a stage-autoregressive pattern whereby correlations between IQ scores decreased as the timespan between assessment waves increased. Further, from infancy to adolescence, the effect of intelligence during earlier periods was completely mediated by intelligence during the adjacent developmental period. In contrast to much prior research, this study demonstrated the stability of general intelligence, beginning in infancy.

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For the Gv Gallery Hall of Fame: Neurocognitive developmental model of cognitive control maturation

Another excellent visual presentation of complex psychological constructs, research and theory.  Click on image to enlarge.

Friday, July 10, 2015

7:18 PM

SES and IQ: Longitudinal twin study

Yet another study demonstrating the significant relation between SES and intelligence, this time a large longitudinal study of twins. Click on images to enlarge. Prior SES posts can be found here.







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Klingberg on working memory dev/trng, P-FIT model, neural/temporal efficiency, bran networks and cognitive development

Excellent article by Klingberg (2014) (copy with annnotated comments and links to other research) that brings together important constructs of working memory (Gwm), working memory training, brain networks and synchronization, white matter mattters, neuroal and temporal processing efficiency, and maturation and training effects on children's cognitive development.
The article does a good job of "connecting the dots" from many different programs of research.

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School readiness = self regulation learning competence?

Excellent review article on the relationship between the development of self-regulated learning strategies/competence and school readiness. Having worked in the schools as a school psychologist for 12 years, I would like to have a buck for every time a kindergarten teacher described children who where struggling in terms of self-regulation--although they did not use that term. A must ready for anyone working with preschool and early elementary students and stuff.

Click on images to enlarge. For more on self-regulated learning as per the Model of Academic Competence and Motivation (MACM), click here.










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Learning to read related to intellectual development - a longitudinal twins study

Wow...how about the complexity of that large path model?

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Circuit-based accounts of adolescent self-control issues

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Gs->working memory->Gf developmental-differential psych developmental cascade model

Very interesting research that suggests a developmental (neo-Piagetian) wrinkle to the developmental cascade model, a model that has shown that Gs influences working memory (Gwm), and working memory in turn influences Gf (but Gs has no direct influencee on Gf).

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"However, the exact role of speed and working memory is still debated. Some researchers emphasize speed as a purer index of the quality of information processing in the brain (e.g., Jensen, 1998). This interpretation is based on studies which estimate the relation between speed and intelligence without involving working memory. Others emphasize working memory because it is the workspace of thinking (Kyllonen & Christal, 1990). Studies emphasizing working memory usually measure all three constructs in young adults, when working memory is the dominant predictor of Gf, according to the patterns to be described below. Finally, others assume a causal linear relation between them such that changes in speed cause changes (or differences) in working memory which, in turn, cause changes (or differences) in Gf (Case, 1985; Coyle, Pillow, Snyder, & Kochunov, 2011; Kail, 1991; Kail & Ferrer, 2007). However, this chain of relations may only reflect the fact that working memory tasks are both timed, like speed tasks, and require information management, like Gf tasks, rather than a causal sequence. In fact, there is evidence that control of attention is common to all, speed, WM, and Gf, explaining their relations (Cowan, Morey, Chen, & Bunting, 2007; Engle et al., 1999; Stankov & Roberts, 1997)"

Note. Attentional control (AC) is now proposed to represent a narrow ability under the broad CHC domain of Gwm (short-term working memory) by the authors of the forthcoming WJ IV [Conflict of interest disclosure--I am one of the coauthors of the WJ III and WJ IV). This is consistent with Schneider and McGrew's (2012) recent book chapter CHC model update.

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"Demetriou et al. (2013) showed recently that the relations between these constructs are more complicated than originally assumed, because they vary with growth. Specifically, speed increases and WM expands. Gf evolves along a reconceptuali-zation sequence (ReConceP) where changes in the nature of representations alternate with changes in the command and interlinking of representations constructed earlier."

"These patterns provide support for an integrated developmental–differential theory of intelligence that would explicate why Gf changes coalesce with speed at the beginning of developmental cycles and with WM changes at the end. Gf undergoes three types of change: representational, inferential, and complexity."

I previously presented (McGrew, 2005) support for the developmental cascade model in 5 age-differentiated WJ III norm samples (see one of the sample models below). Instead of causal models with Gf as the criterion, I specified a criterion g-factor defined by Gv, Ga, Glr, Gf, and Gc. The results strongly supported the Gwm->g link, and significant causal links from Gs to working memory. Gs did not dispaly a direct link to g in the childhood samples, but did demonstrate small significant direct paths to g in the adolescent and adult samples.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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