2. Intelligence testing
Historically, the oldest definition defined Intelligence as the highest faculty of the mind,
being in charge of our cognitive abilities and our ability to form a judgement and think rationally.
The intelligence test is a method to test for the higher cognitive abilities of an individual, most
commonly measured by one’s Intelligence Quotient, which is “a total score derived from a set of
standardized tests designed to assess human intelligence” (Neisser et al., 1996).
Widely used intelligence tests such as the Stanford Binet test and Wechsler’s tests assess
a combination of reasoning, verbal and quantitative skills. In some cases, the intelligence test
also tests discipline-specific knowledge. IQ is commonly used as a predictor for an individual’s
success in one’s career of job performance. However, it is becoming increasingly difficult to
prove the relevance of intelligence testing today. Instead of testing our natural cognitive ability,
the environment has an increased influence as a result of the Flynn effect and role of motivation.
This effect will have an impact on the validity of the IQ score results. Besides, there is also a
need to acknowledge that this factor of an intelligence score is becoming less useful as the nature
of jobs shifts.
Firstly, intelligence tests are generally effective in predicting job performance as it is
indicative of their learning capacity and higher job satisfaction. According to a survey conducted
on 378 university faculty members in Lahore City, Pakistan, there is a correlation between one’s
intelligence quotient (IQ) score and their job performance. These faculty members have an
average of 4.6 years of working experience (Kulikowski & Orzechowski, 2018). The study
results showed that higher IQ people have better job performance than those with lower IQ. It
also discovered that having a higher IQ also leads to higher job satisfaction, which in turn also
affects an individual’s job performance (Kulikowski & Orzechowski, 2018). Hence, intelligence
3. testing is useful to predict qualities of employees and factor these qualities to the suitable job
roles during employment.
Besides, our cognitive capabilities affect our working memory capacity and fluid
intelligence, key traits in testing work engagement rates. Working memory(WM) is the
“workspace of the mind and the system for accessing goal-relevant information as needed to
support complex cognition” (Broadway and Engle, 2010, p.563) which meant that it was
responsible for storing important information and crucial for problem-solving. Working memory
capacity then reflects the limits of our working memory. Fluid Intelligence is the ability to
identify patterns and adaptability to novel situations and problems. These cognitive traits are
personal cognitive resources that stimulate personal development, aiding us to solve complex
problems and increase our energy and perseverance levels (Kulikowski & Orzechowski, 2018).
From the National Longitudinal Survey of Youth( NLSY), data from 219 participants who stayed
in the same occupation under the same employer were collected. Intelligence and job complexity
was measured alongside the control variables of sex, tenure, age and most importantly job
satisfaction. The results proved that intelligent people are more likely to report an increase in job
complexity, the positive regression coefficient of 0.25 (Fried and Ganzan, 2015; Hunter, 1984)
suggesting a positive correlation between intelligence and job complexity. Intelligence tests are
effective in informing employers on an individual’s capacity to learn, allowing them to hire or
position employees more strategically in suitable roles.
Secondly, factors such as the role of motivation and environment that can affect the
accuracy of the Intelligence test, which reduces the reliability and relevance of such tests in the
long run. Environmental factors can influence our performance on intelligence tests. The
environmental influence on intelligence testing can be accounted for by the Flynn Effect, the
4. phenomenon where IQ scores of standardized intelligence tests are observed to be rising over
time. Flynn’s research showed a 13.8 point increase from 1932 to 1978, which on average
increased by 0.3 points each year, or an average of 3 points per decade (Flynn, 1984).From
current research, Flynn Effect was also proven via the increase of IQ scores of 0.31 per year
between 1972 and 2006 using the Stanford-Binet, Wechsler Adult Intelligence Scale(WAIS) and
Wechsler Intelligence Scale for Children (WISC) (Flynn, 2009), which was similar to Flynn’s
original findings. The Flynn effect can be explained by environmental factors such as education.
In the United States of America, mean IQ scores of adults have increased by about 25 points over
the last 90 years. In the study, there is a positive correlation between the average years of
schooling and the increase in IQ scores (Baker et al., 2015). Similar results are also observed by
other countries where Flynn Effects correlate to educational attainment. Flynn effect was also
accounted for by the increased cognitive demand of school material as seen in study 3 of Baker’s
research. From the mid-1960s to 2000, through the analysis of math textbooks, found an increase
in the average number of problem strategies and concepts learnt by a student at a lower grade,
where advanced arithmetic and geometry increased from 11% to 22% during this period(Baker
et al., 2010). The more advanced questions required higher cognitive skills of conceptual
reasoning and complex reasoning. Increased exposure to such questions at a younger age will
better prepare individuals for an intelligence test which taps on similar knowledge and cognitive
skills. Hence, there is a phenomenon of Intelligence tests being an increasingly learnt skill and
certain learning methods will encourage higher IQ scores being tracked.
Another factor that can be explained by the Flynn Effect is the socio-economic
environment. The socio-economic environment determines one’s opportunity for education
which will, in turn, affect one’s IQ. In research studies, IQ and literacy scores have a high
5. correlation coefficient R of 0.95 and 0.9 for US whites and the US blacks respectively(Marks,
2010). In addition, there is a narrowing of IQ score gaps of the whites and blacks, attributing to
improvements of education and social policies in recent years (Marks, 2010). Motivation can
play a role in the accuracy of one’s IQ results, in terms of financial incentive or goal
achievement. The presence of motivation, however, will not negatively affect our IQ score and
only a lack of will result in an inaccurate representation (Duckworth et al., 2011). From both
studies 1 and 2 in Duckworth’s research, it can be concluded that motivation tends to be higher
and less significant for participants with an above-average IQ. Incentives caused IQ score to rise
by 0.96 SD for individuals with a score below- average IQs at baseline and only by 0.26 SD for
those above-average IQs. (Duckworth et al., 2011). Also, it was discovered that test motivation
was less likely to confound when incentives were given or will have a direct impact on the
participant, which is the case for IQ tests used for employment. There is also a link between
“higher test motivation, higher IQ scores and more positive life outcomes” (Duckworth et al.,
2011). Negative test motivation can inflate the results of the intelligence testing and result in an
underestimation of the individual’s score. The environmental factors of education and motivation
therefore can reduce the validity of intelligence tests as an indicator of one’s job capabilities.
However, the hidden factors of education and motivation are also small indicators of one's
suitability based on education or to gauge one’s attitude towards a particular job.
Thirdly, intelligence tests can be more useful when it is coupled with emotional
intelligence tests. Emotional Intelligence has a rising influence in the fields of Organizational
Behavior, Human resources and Management (O’Boyle et al., 2010). Having emotional
intelligence encompasses the abilities that allow individuals to “generate, recognize, express,
understand and evaluate their own and others emotions to guide thinking and action that
6. successfully cope with environmental demands and pressures.” (Van Rooy & Viswesvaran,
2004). Research studies found that all three methods to test EI, ability measures, self and peer
report, all predict job performance well (O’Boyle et al., 2010). While intelligence tests or
cognitive tests tend to predict performance on academics, emotional intelligence, on the other
hand, predicts better teamwork on student projects and groups. Both abilities together can
determine one’s leadership potential, which is useful for companies when they are looking up for
people to take up managerial roles. (O’Boyle et al., 2010). Higher emotional intelligence is also
indicative of positive intrapersonal and interpersonal outcomes (Schutte & Loi, 2014).
Intrapersonal outcomes would usually lead to better mental health and satisfaction and positive
outlook in life, which encourages such an employee to manage with the stresses of a challenging
job well. Interpersonal outcomes include good cooperation with others and better interpersonal
relationships, which will allow them to work well with others and be good at conflict resolution
(Schutte & Loi, 2014). The Meta-analysis shows that employees who are high in EI, display
better leadership skills (Harms & Credé, 2010) and are better at conflict management (Schlaerth
et al., 2013). The intelligence test is therefore more useful when coupled with the emotional test
when it comes to sorting or searching for individuals to take on leadership positions.
In conclusion, intelligence tests are accurate in testing certain cognitive abilities that can
contribute to our job performance. However, it is less valid when we consider environmental
factors, where the environment starts to influence our intelligence and can no longer accurately
test for our cognitive abilities. Apart from that, intelligence tests tend to have a higher validity in
more westernised societies where there is more priority over one's cognitive ability as it is a
strong determiner for success. Lastly, intelligence tests are the most useful when coupled with
the use of emotional intelligence tests to sieve out workers that are good team players and able to
7. work well in high-stress conditions. Overall, intelligence tests will be useful if companies aim to
test for the traits mentioned above.
8. References
Baker, D., Knipe, H., Collins, J., Leon, J., Cummings, E., Blair, C., & Gamson, D. (2010). One
hundred years of elementary school mathematics in the United States: A content analysis
and cognitive assessment of textbooks from 1900 to 2000. Journal for Research in
Mathematics Education, 41(4), 383–423.
https://doi.org/10.5951/jresematheduc.41.4.0383
Baker, D. P., Eslinger, P. J., Benavides, M., Peters, E., Dieckmann, N. F., & Leon, J. (2015). The
cognitive impact of the education revolution: A possible cause of the Flynn Effect on
population IQ. Intelligence, 49, 144–158. https://doi.org/10.1016/j.intell.2015.01.003
Broadway, J. M., & Engle, R. W. (2010). Validating running memory span: Measurement of
working memory capacity and links with fluid intelligence. Behavior Research Methods,
42(2), 563–570. https://doi.org/10.3758/brm.42.2.563
Duckworth, A. L., Quinn, P. D., Lynam, D. R., Loeber, R., & Stouthamer-Loeber, M. (2011).
Role of test motivation in intelligence testing. Proceedings of the National Academy of
Sciences, 108(19), 7716–7720. https://doi.org/10.1073/pnas.1018601108
Flynn, J. R. (1984). The mean IQ of Americans: Massive gains 1932 to 1978. Psychological
Bulletin, 95(1), 29–51. https://doi.org/10.1037/0033-2909.95.1.29
Flynn, J. R. (2009). The WAIS-III and WAIS-IV:DaubertMotions Favor the Certainly False over
the Approximately True. Applied Neuropsychology, 16(2), 98–104.
https://doi.org/10.1080/09084280902864360
Harms, P. D., & Credé, M. (2010). Emotional Intelligence and Transformational and
Transactional Leadership: A Meta-Analysis. Journal of Leadership & Organizational
Studies, 17(1), 5–17. https://doi.org/10.1177/1548051809350894
9. Kulikowski, K., & Orzechowski, J. (2018). Working memory and fluid intelligence as predictors
of work engagement - testing preliminary models. Applied Cognitive Psychology, 33(4).
https://doi.org/10.1002/acp.3500
Marks, D. F. (2010). IQ Variations across Time, Race, and Nationality: An Artifact of Differences
in Literacy Skills. Psychological Reports, 106(3), 643–664.
https://doi.org/10.2466/pr0.106.3.643-664
Murtza, M. H., Gill, S. A., Aslam, H. D., & Noor, A. (2020). Intelligence quotient, job
satisfaction, and job performance: The moderating role of personality type. Journal of
Public Affairs. https://doi.org/10.1002/pa.2318
Neisser, U., Boodoo, G., Bouchard, T. J. Jr., Boykin, A. W., Brody, N., Ceci, S. J., et al. (1996).
Intelligence: knowns and unknowns. Am. Psychol. 51, 77–101. doi: 10.1037/0003-
066X.51.2.77
O’Boyle, E. H., Humphrey, R. H., Pollack, J. M., Hawver, T. H., & Story, P. A. (2010). The
relation between emotional intelligence and job performance: A meta-analysis. Journal of
Organizational Behavior, 32(5), 788–818. https://doi.org/10.1002/job.714
Schlaerth, A., Ensari, N., & Christian, J. (2013). A meta-analytical review of the relationship
between emotional intelligence and leaders’ constructive conflict management. Group
Processes & Intergroup Relations, 16(1), 126–136.
https://doi.org/10.1177/1368430212439907
Schutte, N. S., & Loi, N. M. (2014). Connections between emotional intelligence and workplace
flourishing. Personality and Individual Differences, 66, 134–139.
https://doi.org/10.1016/j.paid.2014.03.031
Van Rooy, D. L., & Viswesvaran, C. (2004). Emotional intelligence: A meta-analytic
10. investigation of predictive validity and nomological net. Journal of Vocational Behavior,
65(1), 71–95. https://doi.org/10.1016/s0001-8791(03)00076-9
Vanhanen, T. (2012). National IQs and their demographic correlates. Personality and Individual
Differences, 53(2), 99–102. https://doi.org/10.1016/j.paid.2011.08.007