Research Alert: Cognitive (CHC)–Mathematics Relations: A Meta-Analysis of Norm-Referenced Standardized Test Batteries

This is an impressive, and much needed, contribution to the CHC cognitive-math achievement relations modeling research literature.  It is open access available here. 

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Abstract

The relationships between cognitive abilities and mathematics skills are important to examine to help clarify how cognitive abilities promote mathematics development and inform why some individuals have difficulty acquiring mathematics skills. Meta-analyses of cognitive–mathematics relations can help summarize this research across a wide variety of test batteries and samples. This study compiled data from technical manuals of 122 norm-referenced standardized test batteries and included over 47,000 correlations from over 550 correlation matrices to summarize cognitive–mathematics relations using meta-analysis. The meta-analytic correlations were used to estimate cognitive–mathematics relations in an integrated model of cognitive abilities and mathematics skills. Fluid reasoning and comprehension-knowledge were two of the most consistent cognitive predictors of mathematics skills, and foundational mathematics skills (e.g., number sense and math fluency) were consistent predictors of advanced mathematics skills (e.g., math problem solving). A supplemental analysis examined how several narrow cognitive abilities (e.g., lexical knowledge, induction) predict mathematics skills. Results suggested that some narrow cognitive abilities, like general knowledge and general sequential reasoning, were consistent predictors of mathematics skills. This study summarizes a large amount of data from norm-referenced standardized test batteries to clarify how cognitive abilities predict mathematics skills. These results can inform both theoretical models of mathematics development and practical strategies when evaluating individuals who may have difficulty acquiring mathematics skills.

Keywords: 

cognitive abilities; mathematical skills; cognitive–achievement relations; CHC theory; meta-structural equation modeling

Research alert: #Cognitive #networks for #knowledge modeling: A gentle introduction for data- and cognitive scientists

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An open access article available here. 

ABSTRACT 

In this paper, we introduce the reader to the field of cognitive network science, that is, the application of network science methods to study human cognition and knowledge structures. Cognitive networks are representations of associative knowledge between concepts in a cognitive system apt at acquiring, storing, processing and producing language, that is, the mental lexicon. In a cognitive network, nodes represent concepts with links expressing relations, such as semantic, syntactic, phonological and visual connections, for example, “canine” and “dog” (nodes) linked by “being synonyms” (link). Hence, cognitive networks represent associative knowledge in mathematical, measurable and quantifiable ways. Can such structure be used to gain insights over cognitive phenomena? We explore this research question by reviewing recent, pioneering key applications and limitations of cog-nitive networks across visual, auditory, and semantic language processing tasks, either in healthy or clinical populations. We also review applications of cognitive networks modeling language acquisition, reconstructing text content and assessing creativity or personality traits in individuals. Our paper also gently introduces the reader to mathematical notations, definitions and measures about single-layer and multiplex networks as well as hypergraphs. Last but not least, across phonological, semantic and syntactic networks, we guide the reader through relevant psychological frameworks, datasets and software packages that might all aid current and future cognitive network scientists.

IQs Corner: #Cloze test performance and #cognitive abilities: A comprehensive #meta-analysis - #intelligence #Grw #Gc #CHC #g #Gf #schoolpsychologists #schoolpsychologt

This is an open access article that can be read/downloaded at this link.

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Abstract

Cloze tests have a long history and have been used to measure various abilities, including intelligence, reading comprehension, and language proficiency. To locate cloze tests within a nomological network of cognitive abilities, we conducted a multilevel random effects meta-analysis covering 110 years of research. Studies were eligible if they provided a measure of association between a cognitive fill-in-the-blank test and any cognitive ability test. We synthesized manifest correlations from 89 studies (N = 37,912, k = 634) and found an average correlation of r = .54 (95% CI [.49, .59], k = 485) with crystallized intelligence, r = .48 (95% CI [.42, .54], k = 69) with fluid intelligence, and r =.61 (95% CI [.46, .77], k = 32) with general intelligence. While today's application of the typical cloze is to measure reading comprehension, our results revealed a similarly strong association with a broad range of crystallized abilities. Of the key moderators we investigated—text base, administration mode, deletion pattern, and response type—only the response type showed a significant effect. Sensitivity analyses supported the robustness of our findings. We conclude by revisiting the origin of the cloze test and highlighting the need for systematic studies on how different cloze test designs affect construct validity. Whereas the meta-analytic database predominantly originates from language research, where cloze tests are entrenched as markers of language proficiency, we propose reframing cloze tests as a versatile intelligence test format—just like multiple-choice tests constitute a testing method—that can be tailored to assess various specific cognitive abilities.

“Be and see” the #WISC-V correlation matrix: Unpublished analyses of the WISC-V #intelligence test

 I often “play around” with data sets until I satisfy my curiosity…and never submit the results for publication.  These WISC-V analyses were completed 3+ years ago.  I stumbled upon the folder today and decided to simply post the information for assessment professionals interested in the WISC-V.  These results have not been peer-reviewed.  One must know the WISC-V subtest names to decipher the test abbreviations in some of the figures.  

This is a Gv (visual; 8 slides) summary a set of exploratory structural analyses I completed with the WISC-V summary correlation matrix (Table 5.1 in WISC-V manual). View and enjoy. 

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Research byte: Prediction of human #intelligence (#g #Gf #Gc) from #brain (#network) #connectivity - #CHC

Choosing explanation over performance: Insights from machine learning-based prediction of human intelligence from brain connectivity 

,  ,  ,   

PNAS Nexus, Volume 3, Issue 12, December 2024, pgae519,

Online and PDF download available at this link:  https://doi.org/10.1093/pnasnexus/pgae519

Abstract

A growing body of research predicts individual cognitive ability levels from brain characteristics including functional brain connectivity. The majority of this research achieves statistically significant prediction performance but provides limited insight into neurobiological processes underlying the predicted concepts. The insufficient identification of predictive brain characteristics may present an important factor critically contributing to this constraint. Here, we encourage to design predictive modeling studies with an emphasis on interpretability to enhance our conceptual understanding of human cognition. As an example, we investigated in a preregistered study which functional brain connections successfully predict general, crystallized, and fluid intelligence in a sample of 806 healthy adults (replication: N = 322). The choice of the predicted intelligence component as well as the task during which connectivity was measured proved crucial for better understanding intelligence at the neural level. Further, intelligence could be predicted not solely from one specific set of brain connections, but from various combinations of connections with system-wide locations. Such partially redundant, brain-wide functional connectivity characteristics complement intelligence-relevant connectivity of brain regions proposed by established intelligence theories. In sum, our study showcases how future prediction studies on human cognition can enhance explanatory value by prioritizing a systematic evaluation of predictive brain characteristics over maximizing prediction performance (emphasis added).

machine learning, intelligence, cognitive ability, functional brain connectivity, predictive modeling

Research Byte: A special contribution from #spatial ability to #math word problem solving: Evidence from #SEM and #networkanalysis

 

Click here to see journal page.

Abstract

There is a growing body of research into the factors contributing to math word problem solving. However, these studies usually use limited number of potential predictors (precluding assessing of their contribution in comparison with other factors or “g” general intelligence) and some predictors (such as analogical and hypothetical reasoning) are largely omitted. Thus, the aim of the current study was to explore contributions of different types of reasoning to math word problem solving and whether these contributions have added value compared with each other and general cognitive ability. Chinese schoolchildren in Grades 3 (N = 199; Mage = 102.4 months), 4 (N = 162; Mage = 114.6), 5 (N = 174; Mage = 126.1) and 6 (N = 180; Mage = 138.6) completed 8 tasks tapping into spatial, mechanical, verbal, mathematic, hypothetical and analogical reasoning. Our data showed that when 6 general cognitive factors load onto General cognitive ability factor in a Structural Equation Model (SEM), only spatial visualization has additional contribution to Word problem solving factor. Gaussian Graphical models (GGMs) showed that 2 verbal tasks and spatial visualization showed stable (present in at least 3 out of 4 grades) contributions to both word problem solving tasks. Analogical reasoning showed contribution to process of word problem solving only. To sum up, both SEM and GGMs converged on the importance of spatial ability for math word problems solving. Our results call for verbal and spatial ability to be routinely assessed and targeted by educational interventions within math curriculum.

More support for the Gs—>Gwm—>—Gf/ Gc developmental cascade model as per CHC taxonomy

 More support for the developmental cascade model

https://www.sciencedirect.com/science/article/abs/pii/S0160289620300817?via%3Dihub

Speed of processing, control of processing, working memory and crystallized and fluid intelligence: Evidence for a developmental cascade 

Anna Tourva, George Spanoudis

 

Keywords: Fluid intelligence Crystallized intelligence Working memory Speed of processing Executive attention Developmental-cascade model 

A B S T R A C T  

The present study investigated the causal relations among age, speed of processing, control of processing, working memory and intelligence, fluid and crystallized. 158 participants aged from 7 to 18 years old completed a large battery of tests measuring latent factors of speed, control of processing and working memory. Intelligence was assessed using the Wechsler Abbreviated Scale of Intelligence. Structural equation modeling was performed to determine whether there is a cognitive-developmental cascade in which age-related increases in processing speed lead to improvements in control of processing that leads to increases in working memory, and whether improved working memory, in turn, leads to increases in both fluid and crystallized intelligence. Several alternative models of a different cascade order of the above factors were also tested. The results of the present study provide evidence of a cognitive-developmental cascade, confirming that this model describes cognitive development during childhood and adolescence.  

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Research suggests that Gq acquired knowledge has distinct neuro basis from other types of semantic knowledge (Gc)

Thanks to my colleague Joel Schneider for making me aware of this article which provides support for Gq acquired knowledge systems being distinct from Gc (as per CHC theory)

Cortical circuits for mathematical knowledge: evidence for a major subdivision within the brain's semantic networks

Cite this article: Amalric M, Dehaene S. 2017
Cortical circuits for mathematical knowledge: evidence for a major subdivision within the brain's semantic networks. Phil. Trans. R. Soc. B373: 20160515.

Marie Amalric and Stanislas Dehaene

Abstract

Is mathematical language similar to natural language? Are language areas used by mathematicians when they do mathematics? And does the brain comprise a generic semantic system that stores mathematical knowledge alongside knowledge of history, geography or famous people? Here, we refute those views by reviewing three functional MRI studies of the representation and manipulation of high-level mathematical knowledge in professional mathematicians. The results reveal that brain activity during professional mathematical reflection spares perisylvian language-related brain regions as well as temporal lobe areas classically involved in general semantic knowledge. Instead, mathematical reflection recycles bilateral intra-parietal and ventral temporal regions involved in elementary number sense. Even simple fact retrieval, such as remembering that ‘the sine function is periodical' or that ‘London buses are red', activates dissociated areas for math versus non-math knowledge. Together with other fMRI and recent intra-cranial studies, our results indicated a major separation between two brain networks for mathematical and non-mathematical semantics, which goes a long way to explain a variety of facts in neuroimaging, neuropsychology and developmental disorders. This article is part of a discussion meeting issue ‘The origins of numerical abilities'.

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Meta-analytic SEM of literacy and language development relations

Using Meta-analytic Structural Equation Modeling to Study Developmental Change in Relations Between Language and Literacy. Article link.

Jamie M. Quinn Richard K. Wagner

The purpose of this review was to introduce readers of Child Development to the meta-analytic structural equa-tion modeling (MASEM) technique. Provided are a background to the MASEM approach, a discussion of its utility in the study of child development, and an application of this technique in the study of reading compre-hension (RC) development. MASEM uses a two-stage approach: first, it provides a composite correlation matrix across included variables, and second, it fits hypothesized a priori models. The provided MASEM application used a large sample (N = 1,205,581) of students (ages 3.5–46.225) from 155 studies to investigate the factor structure and relations among components of RC. The practical implications of using this technique to study development are discussed.

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Research Byte: Multicomponent causal model of vocabulary (lexical knowledge) development

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Language acquisition: Figure for the Gv Gallery Hall of Fame

A cool Gv figure in this article that earns my nomination of the Gv Gallery Hall of Fame. Click on images to enlarge

 

 

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Research byte: Verbal ability (Gc) and knowledge (Gkn) highly related but still separate constructs

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Research Byte: Short-term memory for faces is related to general intelligence: A possible new CHC narrow ability taxonomy candidate?

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Intelligence

Available online 21 May 2016

In Press, Corrected Proof — Note to users

Short-term memory for faces relates to general intelligence moderately ^☆

• Gilles E. Gignac^, ,
• Mahesh Shankaralingam,
• Kipling Walker,
• Philippe Kilpatrick

 Show more

doi:10.1016/j.intell.2016.05.001

Get rights and content

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Highlights

•

Short-term memory for faces correlated positively with several stratum II factors.

•

Short-term memory for faces was associated with general intelligence at .34.

•

Short-term memory for faces should not be considered “special” (i.e., independent of g).

•

Prosopagnosia may be best characterised as a learning disability.

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Abstract

The results associated with a small number of investigations suggest that individual differences in memory for faces, as measured by the Cambridge Face Memory Test (CFMT), are independent of intelligence. Consequently, memory for faces has been suggested to be a special construct, unlike other cognitive abilities. However, previous investigations have measured intelligence with only one or two subtests. Additionally, the sample sizes upon which previous investigations were based were relatively small (N = 45 to 80). Consequently, in this investigation, a battery of eight cognitive ability tests and the CFMT were administered to a relatively large number of participants (N = 211). Based on a correlated-factor model, memory for faces was found to be correlated positively with fluid intelligence (.29), short-term memory (.23) and lexical knowledge ability (.19). Additionally, based on a higher-order model, memory for faces was found to be associated with g at .34. The results are interpreted to suggest that memory for faces, as measured by the CFMT, may be characterised as a relatively typical narrow cognitive ability within the Cattell–Horn–Carroll (CHC) model of intelligence, rather than a special ability (i.e., independent of other abilities). Future research with a greater diversity in the measurement of face recognition ability is encouraged (e.g., long-term memory), as the CFMT is a measure of short-term face memory ability.

Keywords

• Intelligence;
• CHC theory;
• Face identity recognition;
• Prosopagnosia

"Intelligent" intelligence testing with the WJ IV Tests of Cognitive Ability #6: Within-Gc assessment tree

Here is the second WJ IV Within-CHC Assessment Tree--this time for Gc.  See prior post where I explain the basis of these groupings (example is for Gf-tree) and what the various arrows and fonts designate.   I am now also including a tabular form of the information.  This is part of my "Intelligent intelligence testing with the WJ IV Tests of Cognitive Abilities" series.

A PDF copy, which is quite clean, can be downloaded here.

Relevant broad and narrow definitions are below

Comprehension-knowledge (Gc):  The depth and breadth of declarative and procedural knowledge and skills valued by one’s culture. Comprehension of language, words, and general knowledge developed through experience, learning and acculturation.

• General (verbal) information (K0): The breadth and depth of knowledge that one’s culture deems essential, practical, or worthwhile for most everyone to know.
• Language development (LD): The general understanding of spoken language at the level of words, idioms, and sentences.  An intermediate factor between broad Gc and other narrow Gc abilities.  It usually represents a number of narrow language abilities working together in concert—therefore it is not likely a unique ability. 
•  Lexical knowledge (VL): The knowledge of the word definitions and the concepts that underlie them. Vocabulary knowledge.
• Listening ability (LS): The ability to understand speech, starting with comprehending single words and increasing to long complex verbal statements. 

Domain-specific knowledge (Gkn): The depth, breadth, and mastery of specialized declarative and procedural knowledge typically acquired through one’s career, hobby, or other passionate interest. The Gkn domain is likely to contain more narrow abilities than are currently listed in the CHC model.  

• Knowledge of culture (K2): The range of knowledge about the humanities (e.g., philosophy, religion, history, literature, music, and art).

Click on images to enlarge and for clearer image.

I, Kevin McGrew, am solely responsible for this content.  The information presented here (and in this series) does not necessarily reflect the views of my WJ IV coauthors or that of the publisher of the WJ IV (HMH).

Language and Speech in Autism: Annual Review of Linguistics

Language and Speech in Autism

Annual Review of Linguistics

Vol. 2: 413-425 (Volume publication date January 2016)

First published online as a Review in Advance on November 4, 2015

DOI: 10.1146/annurev-linguistics-030514-124824

Morton Ann Gernsbacher,¹ Emily M. Morson,² and Elizabeth J. Grace³

¹Department of Psychology, University of Wisconsin, Madison, Wisconsin 53706; email: MAGernsb@wisc.edu

²Departments of Psychology and Neuroscience, Indiana University, Bloomington, Indiana 47405; email: emorson@umail.iu.edu

³Department of Special Education, National Louis University, Chicago, Illinois 60603; email: Elizabeth.Grace@nl.edu

     FULL-TEXT| PDF (353 KB)| Permissions | Reprints

Citation: Web of Science ®| Download| Email notification|

Web of Science ®: Related Records ®

 

ABSTRACT

Autism is a developmental disability characterized by atypical social interaction, interests or body movements, and communication. Our review examines the empirical status of three communication phenomena believed to be unique to autism: pronoun reversal (using the pronoun you when the pronoun I is intended, and vice versa), echolalia (repeating what someone has said), and a reduced or even reversed production-comprehension lag (a reduction or reversal of the well-established finding that speakers produce less sophisticated language than they can comprehend). Each of these three phenomena has been claimed to be unique to autism; therefore, each has been proposed to be diagnostic of autism, and each has been interpreted in autism-centric ways (psychoanalytic interpretations of pronoun reversal, behaviorist interpretations of echolalia, and clinical lore about the production-comprehension lag). However, as our review demonstrates, none of these three phenomena is in fact unique to autism; none can or should serve as diagnostic of autism, and all call into question unwarranted assumptions about autistic persons and their language development and use.

Research Byte: The relations between CHC cognitive abilities and aspects of social support

Which aspects of social support are associated with which cognitive abilities for which people?

Article in The Journals of Gerontology Series B Psychological Sciences and Social Sciences · January 2016 with 12 Reads

Impact Factor: 3.21 · DOI: 10.1093/geronb/gbv119

Abstract

Objectives.
To assess the relations between 11 aspects of social support and five cognitive abilities (vocabulary, reasoning, spatial visualization, memory, and speed of processing) and to determine whether these relations between social support and cognition are moderated by age or sex.

Method.
A sample of 2,613 individuals between the ages of 18 and 99 years completed a battery of cognitive tests and a questionnaire assessing aspects of social support. A measure of general intelligence was computed using principal components analysis. Multiple regressions were used to evaluate whether each aspect of support and/or its interactions with age or sex predicted each cognitive ability and g.

Results.
Several aspects of social support were significantly related to all five cognitive abilities and to g. When g was included as a predictor, there were few relations with specific cognitive abilities. Age and sex did not moderate any of the relations.

Discussion.
These results suggest that contact with family and friends, emotional and informational support, anticipated support, and negative interactions are related to cognition, whereas satisfaction with and tangible support were not. In addition, these aspects of support were primarily related to g, with the exception of family contact. Social support– cognition relations are comparable across the life span and the sexes.

Research Byte: Study suggests writing places greater demands on working memory than reading and listening

 

Adv Cogn Psychol. 2015; 11(4): 147–155.

Published online 2015 Dec 31. doi:  10.5709/acp-0179-6

PMCID: PMC4710969

Writing, Reading, and Listening Differentially Overload Working Memory Performance Across the Serial Position Curve

Richard Tindle and Mitchell G. Longstaff

Author information ► Article notes ► Copyright and License information ►

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Abstract

Previous research has assumed that writing is a cognitively complex task, but has not determined if writing overloads Working Memory more than reading and listening. To investigate this, participants completed three recall tasks. These were reading lists of words before recalling them, hearing lists of words before recalling them, and hearing lists of words and writing them as they heard them, then recalling them. The experiment involved serial recall of lists of 6 words. The hypothesis that fewer words would be recalled overall when writing was supported. Post-hoc analysis revealed the same pattern of results at individual serial positions (1 to 3). However, there was no difference between the three conditions at serial position 4, or between listening and writing at positions 5 and 6 which were both greater than recall in the reading condition. This suggests writing overloads working memory more than reading and listening, particularly in the early serial positions. The results show that writing interferes with working memory processes and so is not recommended when the goal is to immediately recall information.

Keywords: working memory, reading, listening, writing, serial recall

Vocabulary development and reading comprehension

File under Grw and Gc-VL (lexical knowledge) in the CHC taxonomy. Click on images to enlarge.

 

 

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WISC-V expanded index scores: Verbal Expanded Crystallized (Gc) and Expanded Fluid (Gf) index scores and tables

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Somehow I seemed to have missed this development on my research literature monitoring radar.  More comments and a link to the technical report can be found at Joel Schneider's excellent blog.

Gf and Gc differential effects on short-term educational learning

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Thursday, April 23, 2015

9:41 PM