Thursday, April 26, 2018

Practice effects and progressive error practice effects on speeded tests

Journal of Intelligence

Response Time Reduction Due to Retesting in Mental Speed Tests: A Meta-Analysis (article link)

Jana Scharfen, Diego Blum and Heinz Holling


As retest effects in cognitive ability tests have been investigated by various primary and meta-analytic studies, most studies from this area focus on score gains as a result of retesting. To the best of our knowledge, no meta-analytic study has been reported that provides sizable estimates of response time (RT) reductions due to retesting. This multilevel meta-analysis focuses on mental speed tasks, for which outcome measures often consist of RTs. The size of RT reduction due to retesting in mental speed tasks for up to four test administrations was analyzed based on 36 studies including 49 samples and 212 outcomes for a total sample size of 21,810. Significant RT reductions were found, which increased with the number of test administrations, without reaching a plateau. Larger RT reductions were observed in more complex mental speed tasks compared to simple ones, whereas age and test-retest interval mostly did not moderate the size of the effect. Although a high heterogeneity of effects exists, retest effects were shown to occur for mental speed tasks regarding RT outcomes and should thus be more thoroughly accounted for in applied and research settings.

Keywords: meta-analysis; mental speed; processing speed; retest effect; practice effect; response time; reaction time; automatization

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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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Thursday, April 19, 2018

The Flynn Effect and IQ Disparities Among Races, Ethnicities, and Nations: Are There Common Links? | Psychology Today

The Flynn Effect and IQ Disparities Among Races, Ethnicities, and Nations: Are There Common Links? | Psychology Today

The Flynn Effect and IQ Disparities Among Races, Ethnicities, and Nations: Are There Common Links?

Connecting the Flynn Effect to racial, ethnic, and national disparities in IQ

The 20th century witnessed a dramatic increase in IQ, as much as 3 points per decade (see Are you smarter than Aristotle? Part I). The fact that IQ scores increased so much in such a short amount of time has raised many issues about the nature of intelligence, and what intelligence tests are measuring. For instance, while an individual's IQ test performance within a particular generation tends to be relatively stable and is determined by a complex mix of nature and nurture, such dramatic increases across generations demonstrates the potent influence of the environment on the development of cognitive abilities.

Multiple researchers have proposed theories to explain the Flynn effect. One of the most elaborate is Dickens and Flynn's 'social multiplier effect'. Their proposed effect takes into account the importance of culture in influencing what particular forms of intelligence it educates, spotlights, and nurtures.


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I like to use breakdancing as an example (see IQ Bashing, The Flynn Effect, and Genes). Within a particular generation, really athletic individuals will tend to score higher on a wide variety of tests that require athleticism (a trait that is influenced both by genetic and environmental factors). Athletic individuals will tend to run faster, life heavier weights, swim faster, and probably even look better breakdancing. But imagine that breakdancing suddenly became an Olympic sport (I can only dream). In this imaginary world, society suddenly shifts interest in basketball to breakdancing. We drop more money into educating everyone in the fine art of the baby-freeze, the windmill, and the headstand. Breakdancing becomes a craze, appearing in grade school classrooms, on streets, and on all sorts of job applications. What would come about as a result?

This sort of situation would up the ante on breakdancing skills. Sure, those naturally inclined toward athleticism would still have a breakdancing advantage, but the average standard of breakdancing performance would be greatly increased. In order to remain competitive, aspiring breakdancers would have to step their game up and learn increasingly complex moves. Given enough generations with such high levels of breakdancing training, you would start to see a rise in mean scores on tests of breakdancing ability.

This breakdancing example also applies to the rise seen in IQ scores across generations. Within each generation, people who tend to do well on one test of cognitive ability will tend to do well on other tests that tap to some extent complex reasoning ability. But across generations, the particular types of tests that show the most dramatic increases indicate to a considerable degree our cultural priorities. The Flynn Effect serves as a reminder that when we give people more opportunities to prosper, more people do prosper. We've come quite a long way since the pre-industrial revolution in terms of our cultural emphasis on reading, writing, abstract reasoning, and scientific thinking. The Flynn Effect is a partial indicator of this progress (see Are you smarter than Aristole?: On the Flynn Effect and the Aristotle Paradox).

Over the years, various 'social multipliers' (Dickens & Flynn, 2006) have been proposed to account for the Flynn Effect, including increased nutrition, increased test familiarity, heterosis, increased scientific education, video games, TV show complexity, modernization, and more. Surely a combination of factors contributed to the rise. In this post, I want to focus though on a few changes over the course of the past 100 years that have particular implications for understanding race, ethnic, and national disparities in IQ. First let's look at literacy.

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Literacy involves the ability to write, read, and comprehend information of varying levels of complexity. It is estimated that there are 774 million illiterate adults in the world, 65% whom are women (UNESCO Institute for Statistics, 2007). In the United States alone, 5% of the adult population is completely nonliterate (Kirsch, Jungeblut, Jenkins, & Kolstad, 1993). Self-reported literacy skills of both White and Black populations of the U.S. have been increasing steadily since 1870, however (National Center for Education Statistics, 1993). One study showed that the IQ and literacy scores of Blacks increased in parallel from 1980 to 2000 (Dickens & Flynn, 2006).

The importance of being able to read for performance on an IQ test cannot be understated. Instead of measuring 'intelligence' in an illiterate test-taker, the test is measuring that person's inability to read. While 'intelligence' may certainly influence an individual's ability to read, society has a lot of influence on how many inhabitants even get the chance to read in the first place regardless of the intelligence level of any single individual. Therefore, reading skills may exert important effects on particular races and nationalities that have historically undergone much discrimination and as a result, limited opportunity for literacy development.

An enormous body of evidence collected over the past 50 years shows that different ethnicities and races within a country tend to show substantial differences in their average level of IQ. Some researchers argue that this gap is narrowing (Dickens & Flynn, 2006) whereas others argue that the IQ gap has remained stable (Murray, 2006). IQ test score discrepancies are also found between nations. For instance, sub-Saharan African countries have demonstrated statistically significantly lower IQs than other nations (Lynn, 2006, 2008). These findings have led some researchers to propose that such IQ gaps found across ethnicities, races, and nationalities suggests a difference in innate brain capacity (see Lynn & Vanhanen, 2006).

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Until recently, the phenomenon of the Flynn Effect, and IQ gaps found between different ethnicities, races, and nationalities have not been tied together. For the first time ever, Psychologist David F. Marks systematically analyzed the association between literacy skills and IQ across time, nationality, and race (Marks, 2010).

If increasing literacy were really explaining a number of seemingly different IQ trends, then you would expect to see a few things. First, within a population you should expect increased education of literacy skills to be associated with an increase in the average IQ of that population. Second, IQ gains should be most pronounced in the lower half of the IQ bell curve since this is the section of the population that prior to the education would have obtained relatively lower scores due to their inability to comprehend the intelligence test's instructions. With increased literacy, you should expect to see a change in the skewness of the IQ distribution from positive to negative as a result of higher rates of literacy in the lower half of the IQ distribution (but very little change in the top half of the distribution). You should also expect to see differences on the particular intelligence test subscales, with increased literacy showing the strongest effects on verbal tests of intelligence and minimal differences on other tests of intelligence. If all these predictions hold up, there would be support for the notion that secular IQ gains and race differences are not different phenomena but have a common origin in literacy.

To test these predictions, Marks looked at samples representative of whole populations (rather than individuals), and used ecological methods to calculate statistical associations between IQ and literacy rates across different countries. Were Marks' findings consistent with the predictions?

Strikingly, yes. He found that the higher the literacy rate of a population, the higher that population's mean IQ, and the higher that population's mean IQ, the higher the literacy rate of that population. When literacy rates declined, mean IQ also declined. Marks also found evidence for unequal improvements across the entire IQ spectrum: the greatest effects of increased literacy rates were on those in the lower half of the IQ distribution. Interestingly, he also found that both the Flynn Effect and racial/national IQ differences showed the largest effects of literacy on verbal tests of intelligence, with the perceptual tests of intelligence showing no consistent pattern.

It must be noted that literacy wasn't the only factor responsible for the Flynn effect. Adopting the Cattell-Horn-Carroll (C-H-C) framework (McGrew, 2005, 2009) Marks found that Visual processing (Gv) and Processing Speed (Gs) also made important contributions.

It should also be noted that Mark's findings only speak to populations (not individuals) and do not say much about causation. The findings can only definitively say that some not-yet-identified variable is causing both literacy and IQ scores to change. To really test for causation, future experimental studies should be conducted to look at the effect of literacy intervention on IQ scores in comparison with a control group not receiving literacy intervention and should also investigate intervening variables that affect both literacy and IQ. Still, the result that population level literacy changes with population IQ is suggestive that increased literacy is causing increased IQ.

Even though there is still much work to be done, their findings have some very strong implications for our understanding of the Flynn effect, the nature of intelligence, and the origin of race and secular differences in intelligence.


In Hernstein & Murray's 1994 book The bell curve: intelligence and class structure in American life, most of their controversial claims about IQ differences, ethnicity, and social issues came from the United States Department of Labor's National Longitudinal Survey of Youth. This survey includes the Armed Forces Qualifications Test, which was developed by the Department of Defense and measures the ability of potential recruits to learn how to perform military duties. Since many of Hernstein & Murray's conclusions were based on this test, it's important to really examine what that test measures.

Marks did just that by scanning the literature for datasets containing test estimates for populations of groups taking both the Armed Forces Qualifications Test and tests of literacy. One study on nine groups of soliders differing in job and reading ability found a correlation of .96 between the Armed Forces Qualifications Test and reading achievement (Sticht, Caylor, Kern, & Fox, 1972). Another study showed significant improvements among Black and Hispanic populations in their Armed Forces Qualifications Test scores between 1980 and 1992 while Whites only showed a slight decrement (Kilburn, Hanser, & Klerman, 1998). Another study obtained reading scores for 17-year olds for those same ethnic groups and dates (Campbell et al., 2000) and found a correlation of .997 between reading scores and Armed Forces Qualifications Test scores. This nearly perfect correlation was based on six pairs of data points from six independent population samples evaluated by two separate groups of investigators. As Marks notes,

"On the basis of the studies summarized here, there can be little doubt that the Armed Forces Qualifications Test is a measure of literacy."

The Flynn Effect was intriguing all by itself. Now that researchers have shown common linkages between The Flynn Effect, race, ethnic, and nationality disparities, there are even more questions to be answered and potential research avenues to be explored. The Marks study suggests a crucial environmental factor is literacy. If this is so, then interventions that increase literacy will also narrow the IQ gap found between different races and nationalities.

Literacy intervention can take many forms though, both directly and indirectly. Researchers should consider not just improved access to schooling but also lots of other conditions that may affect literacy rates. For instance, recent research shows the important effects of parasites and pathogens on a nation's intelligence (see recent article in The Economist called Mens sana in corpore sano). Christopher Eppig and colleague's argue in their recent article in Proceedings of the Royal Society that the Flynn effect may be caused in part by the decrease in the intensity of infectious diseases as nations develop. Looking at data from 192 countries and 28 infectious diseases in those countries, they found that the higher the disease burden of that population, the lower that population's mean IQ level, with robust correlations ranging from -0.76 to -0.82. The chance that this correlation came about at random is reported by The Economist to be less than 10,000. Interestingly, when Eppig and colleagues controlled for other contributing variables to national differences in IQ (temperature, distance from Africa, gross domestic product per capita and various measures of education), infectious disease remained the most powerful predictor of average national IQ.

These results suggest that infections and parasites such as intestinal worms, malaria, and perhaps most importantly (according to Eppig and colleagues) bugs that cause diarrhea, can all have important effects on both literacy rates and IQ scores. The good news is that disease interventions such as vaccinations, clean water and proper sewage can have quite outstanding effects on multiple areas of cognition.


This latest research on the environmental effects of nutrition (Colom et al., 2005, but see Flynn, 2009), disease, literacy, and more on both the rise in IQ and ethnic, racial, and national disparities in IQ point to the importance of the environment for developing intelligence as well as the importance for researchers to be very careful when they use intelligence test performance (especially verbal tests) to make inferences about hereditary differences between different ethnic groups and nationalities.

© 2010 by Scott Barry Kaufman

Note: Portions of this post originally appeared as a guest post on the blog Intelligent Insights on Intelligence Theories and Test (see original post here), which is run by legendary IQ test maker, theorist, and researcher Kevin McGrew. I'm a long time follower of his blog and am honored to guest post for him.

Acknowledgments: Thanks to Louisa Egan for bringing The Economist article to my attention.

***Update*** Over at Kevin McGrew's blog, Bob Williams wrote an extensive reply to my post. You can read his very different perspective here.

For more on the Flynn Effect, see:


Campbell, J. R., Hombo, C. M., & Mazzeo, J. (2000) Trends in academic progress: three decades of student performance, NCES 2000-469. Washington, DC: U.S. Department of Education, Office of Educational Research and Improvement, National Center for Education Statistics, NAEP 1999.

Colom, R., Lluis-Font, J. M., & Andrés-Pueyo, A. (2005) The generational intelligence gains are caused by decreasing variance in the lower half of the distribution: supporting evidence for the nutrition hypothesis. Intelligence, 33, 83-91.

Dickens, W. T., & Flynn, J. R. (2006) Black Americans reduce the racial IQ gap: evidence from standardization samples. Psychological Science, 17, 913-920.

Eppig, C., Fincher, C.L., & Thornhill, R. (2010). Parasite prevalence and the worldwide distribution of cognitive ability. Proceedings of the Royal Society B, doi: 10.1098/rspb.2010.0973.

Flynn, J. R. (2009) Requiem for nutrition as the cause of IQ gains: Raven's gains in Britain 1938 to 2008. Economics and Human Biology, 7, 18-27.

Herrnstein, R. J., & Murray, C. (1994) The bell curve: Intelligence and class structure in American life. New York: Free Press.

Kilburn, M. R., Hanser, L. M., & Klerman, J. A. (1998) Estimating AFQT scores for National Educational Longitudinal Study(NELS) respondents. Santa Monica, CA: RAND Distribution Services.

Kirsch, I. S., Jungeblut, A., Jenkins, L., & Kolstad, A. (1993) Adult literacy in America: A first look ook at the results of the National Adult Literacy Survey. Princeton, NJ: Educational Testing Service.

Lynn, R. (2006) Race differences in intelligence: an evolutionary analysis. Augusta, GA: Washington Summit.

Lynn, R. (2008) The global bell curve. Augusta, GA: Washington Summit.

Lynn, R., & Vanhanen, T. (2002) IQ and the wealth of nations. Westport, CT: Praeger.

Marks, D.F. (2010). IQ variations across time, race, and nationality: An artifact of differences in literacy skills. Psychological Reports, 106, 3, 643-664.

McGrew, K. S. (2005) The Cattell-Horn-Carroll theory of cognitive abilities: past, present, and future. In D. P. Flanagan & P. L. Harrison (Eds.), Contemporary intellectual assessment: theories, tests, and issues. (2nd ed.) New York: Guilford. Pp. 136-182.

McGrew, K. (2009). Editorial. CHC theory and the human cognitive abilities project. Standing on the shoulders of the giants of psychometric intelligence research, Intelligence, 37, 1-10.

Murray, C. (2006) Changes over time in the Black-White difference on mental tests: evidence from the children of the 1979 cohort of the National Longitudinal Survey of Youth. Intelligence, 34, 527-540.

National Center for Education Statistics. (1993) 120 years of American educ ation: a statistical portrait. (T. Snyder, Ed.) Washington, DC: U.S. Department of Education, Institute of Education Sciences, NCES 1993.

Sticht, T. G., Caylor, J. S., Kern, R. P., & Fox, L. C. (1972) Project REALISTIC: determination of adult functional literacy skill levels. Reading Research Quarterly, 7, 424-465.

Wednesday, April 18, 2018

Early developmental trajectories of number knowledge and math achievement from 4 to 10 years: Low-persistent profile and early-life predictors

Early developmental trajectories of number knowledge and math achievement from 4 to 10 years: Low-persistent profile and early-life predictors

From Twitter, a Flipboard magazine by Journal of Sch Psych

Little is known about the development of number knowledge…

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Kevin McGrew, PhD
Educational Psychologist
Director, Institute for Applied Psychometrics

Tuesday, April 17, 2018

The Flynn Effect Reference Project updated

The Flynn Effect Reference Project document, maintained at the Intellectual Competence and the Death Penalty blog, was just updated today.  This information can be found here.

Monday, April 16, 2018

Interesting new book on cognitive capitalism

Research Byte: Differences in mathematical reasoning between typically achieving and gifted children

Differences in mathematical reasoning between typically achieving and gifted children
Derek H. Berg & Pamela A. McDonald (article link)


Mathematical giftedness refers to mastery in a specific mathematical domain at an earlier than expected age. The present study examined which cognitive processes accounted for differences in mathematical reasoning between gifted children (MRG) and their typically achieving peers (TA). Naming speed, phonological awareness, short-term memory, executive functioning, and working memory were examined in 51 children aged approximately 7 years. A series of stepwise regression models, using a contrast variable to capture differences in mathematical reasoning between MRG and TA children, were created to examine which cognitive domains accounted for differences in mathematical reasoning. Short-term memory (r2 = .08) and visual-spatial working memory (r2 = .39) emerged as the only cognitive predictors within a model that included gender, age, and fluid intelligence. This model captured all of the variance distinguishing mathematics reasoning between MRG and TA children, explaining an overall contribution of 70% of the variance in mathematical reasoning.

KEYWORDS: Giftedness, mathematical reasoning, working memory, child development

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Sunday, April 15, 2018

Mapping the Human Connectome

Nice brief video overview.

Mapping the Human Connectome

In the early 1800s, Lewis and Clark set out to map the western United States. Charting the network of rivers that wound their way across the land. Like those 19th century…

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Saturday, April 14, 2018

Speed and the Flynn effect research study

Speed and the Flynn Effect (article link)

Olev Must and Aasa Must

Keywords: Flynn Effect NIT Speed Tork Estonia


We investigated the role of test-taking speed on the Flynn Effect (FE). Our study compared two cohorts of Estonian students (1933/36, n = 888; 2006, n = 912) using 9 subtests from the Estonian adaptation of the National Intelligence Tests (NIT). The speededness of the items and the subtests was found by determining the proportion of unreached items from among the total number of errors (Stafford, 1971). The test-taking speed of the younger cohort was higher in all 9 of the subtests. This suggests that the younger cohort is able to solve more items than the older one. The lack of measurement invariance at the item and subtest level was quantitatively estimated using a method proposed by Dimitrov (2017). The test-taking speed and the non-invariance of the items was strongly, yet inversely correlated (up to - 0.89). The subtests versions that consisted of only invariant items showed no, or a small positive, FE. The subtest versions consisting of only speeded items showed a large positive FE, with cohort differences of up to 50%. If the requirement of measurement invariance is ignored then this effect becomes apparent. The rise in test-taking speed between cohorts can be attributed to an increase in automated responses, which is an outgrowth of modern education (differences in the mandatory age of school attendance, and in the student's readiness to solve abstract items also affected the test-taking speed of the cohorts). We were able to conclude that the younger cohort is faster than the older one.

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Possible Gf subprocesses

Interesting conceptual framework for understanding performance on Gf tasks. However, it is Important to note that factor analysis studies have suggested a number of subprocesses that do not necessarily fit in this task-analysis based model.

Signatures of multiple processes contributing to fluid reasoning performance (article link)

Ehsan Shokri-Kojoria and Daniel C. Krawczyk


Keywords: Fluid intelligence Individual differences Multi-process Raven's progressive matrices


We aimed to achieve a better understanding of the cognitive processes of fluid reasoning (or fluid intelligence; Gf), the ability to reason in novel conditions. While fluid reasoning has often been considered a unitary con-struct, multiple cognitive processes are expected to affect fluid reasoning performance. Yet, the contribution of various cognitive processes in fluid reasoning performance remains under-explored. We hypothesized that in-dividual differences in fluid intelligence can be viewed as a composite of individual differences in performance in various processes of Gf. Change detection, rule verification, and rule generation were the three processes-of-interest that were additively recruited in a novel visuospatial reasoning task. We observed decreases in accuracy and increases in response time as the processing requirements increased across task conditions. Hierarchical multiple linear regression analyses showed that individual differences in the likelihood of success and speed of each of these processes, accounted for different aspects of individual differences in accuracy and response time in fluid reasoning performance, as measured by Raven's Progressive Matrices. Change detection was a significant contributor to performance in problems with higher visuospatial demand, however, rule verification and rule generation consistently contributed to performance for all problem types. Our findings support the position that individual differences in fluid intelligence emerge as a composite of performance on separable cognitive op-erations, with rule processing being important for differentiating performance on high difficulty problem.

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Tuesday, April 10, 2018

Caffeine causes widespread brain entropy (and that’s a good thing)

Caffeine causes widespread brain entropy (and that's a good thing)

From Brain, a Flipboard magazine by Andy A

By Christian JarrettBasic neuroscience teaches us how individual brain cells communicate with each other, like neighbours chatting…

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Executive functioning (fully) and processing speed (mostly) mediate intelligence deficits in children born very preterm


Children born very preterm (<32 weeks gestational age) are known to be at increased risk of neurocognitive impairments, in domains including executive functioning, processing speed, and fluid and crystallised intelligence. Given the close association between these constructs, the current study investigated a specific model, namely whether executive functioning and/or processing speed mediates the relationship between preterm birth and intelligence. Participants were 204 children born very preterm and 98 full-term children, who completed a battery of tasks measuring executive functioning, processing speed, and fluid and crystallised intelligence. Independent-samples t-tests found significantly poorer performance by children born preterm on all measures, and a confirmatory factor analysis found preterm birth to be significantly related to each of the cognitive domains. A latent-variable mediation model found that executive functioning fully mediated the associations between preterm birth and both fluid and crystallised intelligence. Processing speed fully mediated the preterm birth-fluid intelligence association, but only partially mediated the preterm birth-crystallised intelligence association. Future research should consider a longitudinal study design to test whether these deficits and mediating effects remain throughout childhood and adolescence.


  • Executive function
  • Processing speed
  • Intelligence
  • Preterm birth

Kevin McGrew, PhD
Educational Psychologist
Director, Institute for Applied Psychometrics

Working memory and the Big Five

Kevin McGrew, PhD
Educational Psychologist
Director, Institute for Applied Psychometrics

Friday, April 06, 2018

AJT CHC Intelligence Test launch in Jakarta - a measure of 9 broad CHC abilities

Yesterday’s AJT CHC cognitive test launch yesterday in Jakarta was a big success. I was taken aback by the special “event” flavor. Extremely professional. As I’ve stated before, the AJT is based on an Indonesia norm sample of 4,800 and will be one if the most comprehensive intelligence tests in the world (on par with the WJ IV COG). It measures 9 broad CHC domains (Gf, Gc, Gwm, Ga, Gv, Gs, Gl, Gr, and some of Gp-separate from cognitive). This has been the most personally rewarding and important project I have worked on in my 40+ years in psychology and education. It is bringing the core concept of individual differences to the education system of the fourth largest country in the world.

George and Laurel Tahija (see picture below), and their YDB foundation, are the visionaries behind this project and other projects focused on helping unique learners in their country. In my five years on this project I can say that I’ve never worked with so many nice people. It was a grand effort by many. I am very impressed how together we built such a comprehensive and technically sound battery of tests from scratch. I have developed a fondness for Indonesia and the people of this wonderful country. The genuine warmth and enthusiasm of the participants was personally moving.

For more information check out these two links (one; two)

Conflict of interest disclosure.  I have been a paid consultant for this project but do not receive any royalties from sales of the test.

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A Heavy Working Memory Load May Sink Brainwave ‘Synch’

A Heavy Working Memory Load May Sink Brainwave 'Synch'

Researchers report synchrony of brain waves within three regions of the brain can 'break down' when visual working memory load becomes too…

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Kevin McGrew, PhD
Educational Psychologist 
Institute for Applied Psychometrics

Wednesday, April 04, 2018

Indonesia AJT CHC Intelligence test first official launch at UGM in Jogyakarta.

Next stop Jakarta.

One of the most comprehensive intelligence tests in the world (on par with WJ IV). When I have time I will post more. The most important project I have worked on in my 40+ years in psychology and education.