One of the most puzzling aspects of gifted education is the field’s negative attitude towards the concepts of general intelligence (i.e., g) and IQ. For many years, leaders in the field have called intelligence tests biased (Harris & Ford, 1991), a narrow measure of ability (Sternberg et al., 2021) and flawed (Gallagher, 2008). Some even claim that the field of gifted education has moved beyond intelligence and IQ (Cross & Cross, 2017) or that it should do so (Dai, 2010).

And yet, intelligence keeps finding its way into gifted education. Intelligence tests have widespread usage in gifted education research (Cao et al., 2017). My article (Warne, 2016) in Gifted Child Quarterly (the field’s flagship journal) about the need to incorporate intelligence theory into gifted education was one of the most highly downloaded and cited articles that the journal published that year. And IQ’s status as a measure of giftedness and predictor of future life outcomes has been more consistently replicated than any other finding in gifted education (Lubinski, 2016).

Turning up again and again

So, why does IQ turn up like a bad penny in gifted education? The answer is simple: Any form of high aptitude or achievement in education requires intelligence. As long as “giftedness” gets measured or defined in terms of high performance on a cognitive or educational task, that measure will capture intelligence or g to some extent. In the 118 years since the very first intelligence test was invented, no one has ever found a cognitive variable that was uncorrelated with intelligence (Warne, 2020, Chapter 1).

Like a bad penny, IQ keeps turning up in gifted education. Decades of efforts from the field’s leaders haven’t kept IQ and intelligence out of the practice and research of gifted education. Image source

Intelligence saturates every cognitive behavior in humans. Even the most basic psychological tasks, like reaction time, are partially influenced by intelligence (Jensen, 1998). Thus, any definition of giftedness that is based on cognitive performance will be — at least partially — influenced by intelligence. There is no way around this because “g is to psychology what carbon is to chemistry” (Ree & Earles, 1993, p. 11). Just as a complete understanding of chemistry is not possible without referencing carbon, a complete understanding of human cognitive performance is not possible without referencing global intelligence.

And that incomplete knowledge shows in gifted education. From time to time, the field gropes around and “discovers” something well known to intelligence researchers. For example, some leaders in gifted education suggested in the 2000s that selecting children for gifted programs by using non-verbal matrix tests would reduce racial discrepancies (e.g., Naglieri & Ford, 2003). Fast forward a decade, and it was discovered that these non-verbal tests did not increase the number of children in underrepresented racial groups in gifted programs (Carman & Tylor, 2010; Carman et al., 2018, 2020). This disappointing result occurred because tests that are better measures of g (like matrix tests) tend to have the largest average gaps in scores for racial groups — a fact that has been known in the intelligence research community since the 1980s (Jensen, 1980, 1985).

Another example occurred at the 2017 conference of the National Association of Gifted Children when Linda Silverman (one of the field’s senior leaders) presented her finding that there is more variability in subscores on intelligence tests for gifted examinees (with a high IQ) than for a more typical sample. This phenomenon is very well known in the intelligence and even has a special name: Spearman’s law of diminishing returns.

When Silverman later published this information, she never mentioned Spearman’s work (Silverman & Gilman, 2020). Her “discovery” was already 90 years old (Spearman, 1927, pp. 217-221) when she announced it at the conference. This prompted me to tweet a picture of Charles Spearman:

You can run, but you can’t hide . . . from g

Try as they might, leaders in gifted education can’t keep intelligence out of gifted education. This is not because of some conspiracy from the IQ crowd, nor is it because of ignorance of new findings showing that intelligence as a concept is obsolete. Rather, it is because intelligence is real and it pervades every cognitive behavior in humans. IQ is the best predictor of scholastic performance (Zaboski et al., 2018) and is a strong predictor of job performance (Ree & Carretta, 2022). Ignoring intelligence or trying to “move on” will not change the dominance of intelligence in education and other cognitive endeavors.

Anyone working or doing research in a cognitive field, including gifted education, would benefit from learning more about intelligence. A good introduction to the topic is my book, In the Know: Debunking 35 Myths About Human Intelligence (Warne, 2020). People in gifted education may benefit from my introductory article in Gifted Child Quarterly (Warne, 2016).


Cao, T. H., Jung, J. Y., & Lee, J. (2017). Assessment in gifted education: A review of the literature from 2005 to 2016. Journal of Advanced Academics, 28(3), 163-203.

Carman, C. A., & Taylor, D. K. (2010). Socioeconomic status effects on using the Naglieri Nonverbal Ability Test (NNAT) to identify the gifted/talented. Gifted Child Quarterly, 54(2), 75-84.

Carman, C. A., Walther, C. A. P., & Bartsch, R. A. (2018). Using the Cognitive Abilities Test (CogAT) 7 nonverbal battery to identify the gifted/talented: An investigation of demographic effects and norming plans. Gifted Child Quarterly, 62(2), 193-209.

Carman, C. A., Walther, C. A. P., & Bartsch, R. A. (2020). Differences in using the Cognitive Abilities Test (CogAT) 7 nonverbal battery versus the Naglieri Nonverbal Ability Test (NNAT) 2 to identify the gifted/talented. Gifted Child Quarterly, 64(3), 171-191.

Cross, T. L., & Cross, J. R. (2017). Challenging an idea whose time has gone. Roeper Review, 39(3), 191-194.

Dai, D. Y. (2010). The nature and nurture of giftedness. Teachers College Press.

Gallagher, J. J. (2008). According to Jim: The flawed normal curve of intelligence. Roeper Review, 30(4), 211-212.

Harris, J. J., III, & Ford, D. Y. (1991). Identifying and nurturing the promise of gifted Black American children. The Journal of Negro Education, 60(1), 3-18.

Jensen, A. R. (1980). Précis of bias in mental testing. Behavioral and Brain Sciences, 3(3), 325-333.

Jensen, A. R. (1985). The nature of the black–white difference on various psychometric tests: Spearman’s hypothesis. Behavioral and Brain Sciences, 8(2), 193-219.

Jensen, A. R. (1998). The g factor: The science of mental ability. Praeger.

Lubinski, D. (2016). From Terman to today: A century of findings on intellectual precocity. Review of Educational Research, 86, 900-944.

Naglieri, J. A., & Ford, D. Y. (2003). Addressing underrepresentation of gifted minority children using the Naglieri Nonverbal Ability Test (NNAT). Gifted Child Quarterly, 47(2), 155-160.

Ree, M. J., & Carretta, T. R. (2022). Thirty years of research on general and specific abilities: Still not much more than g. Intelligence, 91, Article 101617.

Ree, M. J., & Earles, J. A. (1993). g is to psychology what carbon is to chemistry: A reply to Sternberg and Wagner, McClelland, and Calfee. Current Directions in Psychological Science, 2(1), 11-12.

Silverman, L. K., & Gilman, B. J. (2020). Best practices in gifted identification and assessment: Lessons from the WISC-V. Psychology in the Schools, 57(1), 1569-1581.

Spearman, C. (1927). The abilities of man: Their nature and measurement. The Macmillan Company.

Sternberg, R. J., Desmet, O. A., Ford, D. Y., Gentry, M., Grantham, T. C., & Karami, S. (2021). The legacy: Coming to terms with the origins and development of the gifted-child movement. Roeper Review, 43(4), 227-241.

Warne, R. T. (2016). Five reasons to put the g back into giftedness: An argument for applying the Cattell–Horn–Carroll theory of intelligence to gifted education research and practice. Gifted Child Quarterly, 60(1), 3-15.

Warne, R. T. (2020). In the know: Debunking 35 myths about human intelligence. Cambridge University Press.

Zaboski, B. A., II, Kranzler, J. H., & Gage, N. A. (2018). Meta-analysis of the relationship between academic achievement and broad abilities of the Cattell-Horn-Carroll theory. Journal of School Psychology, 71, 42-56.