Friday, November 22, 2024

The Evolution of #Intelligence (journals)—the two premiere intelligence journals compared—shout out to two #schoolpsychologists

The Evolution of Intelligence: Analysis of the Journal of Intelligence and Intelligence 

Click here to read and download the paper.

by 
Fabio Andres Parra-Martinez
 1,*
Ophélie Allyssa Desmet
 2 and 
Jonathan Wai
 1
1
Department of Education Reform, University of Arkansas, Fayetteville, AR 72701, USA
2
Department of Human Services, Valdosta State University, Valdosta, GA 31698, USA
*
Author to whom correspondence should be addressed. 
J. Intell. 202311(2), 35; https://doi.org/10.3390/jintelligence11020035

Abstract

What are the current trends in intelligence research? This parallel bibliometric analysis covers the two premier journals in the field: Intelligence and the Journal of Intelligence (JOI) between 2013 and 2022. Using Scopus data, this paper extends prior bibliometric articles reporting the evolution of the journal Intelligence from 1977 up to 2018. It includes JOI from its inception, along with Intelligence to the present. Although the journal Intelligence’s growth has declined over time, it remains a stronghold for traditional influential research (average publications per year = 71.2, average citations per article = 17.07, average citations per year = 2.68). JOI shows a steady growth pattern in the number of publications and citations (average publications per year = 33.2, average citations per article = 6.48, total average citations per year = 1.48) since its inception in 2013. Common areas of study across both journals include cognitive ability, fluid intelligence, psychometrics–statistics, g-factor, and working memory. Intelligence includes core themes like the Flynn effect, individual differences, and geographic IQ variability. JOI addresses themes such as creativity, personality, and emotional intelligence. We discuss research trends, co-citation networks, thematic maps, and their implications for the future of the two journals and the evolution and future of the scientific study of intelligence.

Yes….a bit of a not-so-humble brag.  In the co-citation JOI figure below, the Schneider, W. J. is the Schneider & McGrew (2012) chapter, which has now been replaced by Schneider & McGrew (2018; sorry, I don’t have good PDF copy to link).  In the second Intelligence co-citation network figure, the McGrew, K. S. (2009) paper, next to Carroll’s (1993) seminal work, is your’s truly—my most cited journal article (see Google Scholar Profile).  The frequent citation of the Schneider & McGrew (2012) and McGrew (2009) journal publications are indicators of the “bridger” function Joel and I have provided—providing a bridge between intelligence research/theory and intelligence test development, use, and interpretation in school psychology.  

(Click on images to enlarge for better viewing)



Research Byte: Beyond Individual #Tests: Youths’ #Cognitive Abilities, Basic #Reading, and #Writing—relevant to #schoolpsychologists #CHC

An impressive multiple test-battery CHC theory cognitive and achievement (cross-battery) confirmatory factor analysis study based on a research design first conceptualized by Jack McArdle (planned missing data reference variable design) that finds that multiple broad CHC abilities are important in explaining reading and writing achievement above and beyond psychometric g.  Of course, the results would be different if a bi-factor model were run (see McGrew et al., 2023 for discussion of three major classes of cognitive-achievement CFA/SEM research designs).  

Click here to download/read this open access articles. 

This research group, IMHO, does some of the best CFA/SEM modeling in the assessment and school psychology literature.

Click on images to enlarge for easier viewing.



Beyond Individual Tests: Youths’ Cognitive Abilities, Basic Reading, and Writing 

by  1,* 1 2 and  3
1
Department of Educational Psychology, University of Connecticut, Storrs, CT 06268, USA
2
Department of Educational Psychology, University of Texas at Austin, Austin, TX 78712, USA
3
Department of Educational Psychology, University of Kansas, Lawrence, KS 66045, USA
*
Author to whom correspondence should be addressed. 
J. Intell. 202412(11), 120; https://doi.org/10.3390/jintelligence12110120
Abstract

Broadly, individuals’ cognitive abilities influence their academic skills, but the significance and strength of specific cognitive abilities varies across academic domains and may vary across age. Simultaneous analyses of data from many tests and cross-battery analyses can address inconsistent findings from prior studies by creating comprehensively defined constructs, which allow for greater generalizability of findings. The purpose of this study was to examine the cross-battery direct effects and developmental differences in youths’ cognitive abilities on their basic reading abilities, as well as the relations between their reading and writing achievement. Our sample included 3927 youth aged 6 to 18. Six intelligence tests (66 subtests) and three achievement tests (10 subtests) were analyzed. Youths’ general intelligence (g, large direct and indirect effects), verbal comprehension–knowledge (large direct effect), working memory (large direct effect), and learning efficiency (moderate direct effect) explained their basic reading skills. The influence of g and fluid reasoning were difficult to separate statistically. Most of the cognitive–basic reading relations were stable across age, except the influence of verbal comprehension–knowledge (Gc), which appeared to slightly increase with age. Youths’ basic reading had large influences on their written expression and spelling skills, and their spelling skills had a large influence on their written expression skills. The directionality of the effects most strongly supported the direct effects from the youths’ basic reading to their spelling skills, and not vice versa.

Wednesday, November 20, 2024

Research Byte: A Systematic #Review of #Working#Memory (#Gwm) Applications for #Children with #LearningDifficulties (#LD): Transfer Outcomes and Design Principles

 A Systematic Review of Working Memory Applications for Children with Learning Difficulties: Transfer Outcomes and Design Principles 

by 
Adel Shaban
 1,*
Victor Chang
 2
Onikepo D. Amodu
 1
Mohamed Ramadan Attia
 3 and 
Gomaa Said Mohamed Abdelhamid
 4,5
1
Middlesbrough College, University Centre Middlesbrough, Middlesbrough TS2 1AD, UK
2
Aston Business School, Aston University, Birmingham B4 7UP, UK
3
Department of Educational Technology, Faculty of Specific Education, Fayoum University, Fayoum 63514, Egypt
4
Department of Educational Psychology, Faculty of Education, Fayoum University, Fayoum 63514, Egypt
5
Department of Psychology, College of Education, Sultan Qaboos University, Muscat 123, Oman
*
Author to whom correspondence should be addressed. 
Educ. Sci. 202414(11), 1260; https://doi.org/10.3390/educsci14111260

Visit article page where PDF of article can be downloaded

Abstract

Working memory (WM) is a crucial cognitive function, and a deficit in this function is a critical factor in learning difficulties (LDs). As a result, there is growing interest in exploring different approaches to training WM to support students with LDs. Following the PRISMA 2020 guidelines, this systematic review aims to identify current computer-based WM training applications and their theoretical foundations, explore their effects on improving WM capacity and other cognitive/academic abilities, and extract design principles for creating an effective WM application for children with LDs. The 22 studies selected for this review provide strong evidence that children with LDs have low WM capacity and that their WM functions can be trained. The findings revealed four commercial WM training applications—COGMED, Jungle, BrainWare Safari, and N-back—that were utilized in 16 studies. However, these studies focused on suggesting different types of WM tasks and examining their effects rather than making those tasks user-friendly or providing practical guidelines for the end-user. To address this gap, the principles of the Human–Computer Interaction, with a focus on usability and user experience as well as relevant cognitive theories, and the design recommendations from the selected studies have been reviewed to extract a set of proposed guidelines. A total of 15 guidelines have been extracted that can be utilized to design WM training programs specifically for children with LDs. 


https://www.mdpi.com/2227-7102/14/11/1260#

#AI resource for #educators and #psychologists: Lockwood Educational and Psychological Consutling

I just connected (via LinkedIn) with Lockwood Educational and Psychological Consulting.  The group describes itself below.  Given the considerable interest in AI in education and psychology, I would suggest checking out their web page. I’ve not yet conducted a deep dive into the website, but it appears to be a solid AI-related resource.  I plan to take a closer look.


Is your district, organization, or practice considering implementing AI but concerned about the ethical and practical implications? You've come to the right place. With expertise in both AI, education, and psychology, I provide guidance to navigate these complex waters, ensuring ethical, effective, and confidence-inspiring AI integration in educational, and psychological practice settings.


 

Research Byte: Domain-specific and domain-general skills as predictors of #arithmetic #fluency development—New #WJV will have similar measure—#MagnitudeComparison test

 Domain-specific and domain-general skills as predictors of arithmetic fluency development

Link to PDF appears available at journal page (click here to go directly to PDF)

Abstract

We investigated Norwegian children's (n = 262) development in arithmetic fluency from first to third grade. Children's arithmetic fluency was measured at four time points, domain-specific (i.e., symbolic magnitude processing and number sequences) and domain-general skills (i.e., working memory, rapid naming, non-verbal reasoning, and sustained attention) once in the first grade. Based on a series of growth mixture models, one developmental trajectory best described the data. Multigroup latent growth curve models showed that girls and boys developed similarly in their arithmetic fluency over time. Symbolic magnitude processing and number sequence skills predicted both initial level and growth in arithmetic fluency, and working memory predicted only initial level, similarly for boys and girls. Mother's education level predicted the initial level of arithmetic fluency for boys, and rapid naming predicted growth for girls. Our findings highlight the role of domain-specific skills in the development of arithmetic fluency.

As an FYI, the forthcoming WJ V (Q1, 2025) has a new test (Magnitude Comparison) that measures abilities similar to the symbolic magnitude processing ability measure used in this study (COI - I’m a coauthor of the WJ V)


https://www.sciencedirect.com/science/article/pii/S104160802400178X

Tuesday, November 19, 2024

Research Byte: Revising Baddeley and Hitch’s #workingmemory (#Gwm) 50 years later—relevance to #children and #developmental models.

 EXPRESS: Revisiting Working Memory Fifty Years after Baddeley and Hitch: A Review of Field-specific Conceptualizations, Use and Misuse, and Paths Forward for Studying Children


As trained educational and developmental psychologists who study the role of working memory in educational outcomes, we know the various assumptions made about definitions and measurements of this cognitive ability. Considering the popularity of the Baddeley and Hitch working memory model (1974) in these fields, we raise challenges related to measurement, overlap with executive function, and adopting working memory measurement approaches from adult models. We propose that researchers consider how working memory tasks might tap multiple other abilities. This is problematic in the context of child cognitive development and in understanding which factors explain educational outcomes in children. We recommend giving greater attention to the central executive, acknowledging the overlap between the central executive and executive function in study design, and investigating a developmental model in the context of the broader abilities evoked in measurement. These recommendations may provide a fuller understanding of working memory's mechanistic role in children's learning and development and assist in developing reasonable adjustments for specific aspects of working memory for children who struggle

Occam’s razor and human #intelligence (and #cognitive ability tests)….yes…but sometimes no…food for thought for #schoolpsychologists

 


Occam's razor (also spelled Ockham's razor or Ocham's razorLatinnovacula Occami) is the problem-solving principle that recommends searching for explanations constructed with the smallest possible set of elements. It is also known as the principle of parsimony or the law of parsimony (Latinlex parsimoniae)”

In the context of fitting structural CFA models to intelligence test data, it can be summarized as “given two models with similar fit to the data, the simpler model is preferred” (Kline, 2011, p. 102).” The law of parsimony is frequently invoked in research articles when an investigator is faced with competing factor models regarding the underlying structure of a cognitive ability test battery. However, when complex human behavior is involved, especially something as complex as human intelligence and the brain, it is possible that Occam’s razor might interfer with a thourough understanding of human intelligence and test batteries designed to measure intelligence. The following quote2note has stuck with me as an important reminder that when faced with alternative and more complex statistical CFA models, these models should not be summarily dismissed based only on the parsimony principle. As stated by Stankov, Boyle, and Cattell (1995)


while we acknowledge the principle of parsimony and endorse it whenever applicable, the evidence points to relative complexity rather than simplicity…the insistence on parsimony at all costs can lead to bad science” (p. 16).


Stankov, L., Boyle, G. J., & Cattell, R. B. (1995). Models and paradigms in personality and intelligence research. In D. Saklofske & M. Zeidner (Eds.), International handbook of personality and intelligence (pp. 15–43). New York, NY: Plenum Press.