Reasons for gender differences in cognitive performance

  • girls tend to think predicatively
  • boys tend to think functionally
  • girls give „boy´s subjects“ not even a chance
  • girls have less motivation for abstract tasks
Overview of topics:
Predictive and functional thinking
Evolutionary perspective


Root cause analysis

We have summarized the differences between the sexes in cognitive performance. Now we want to investigate the question whether and to what extent these differences are congenital – which is not easy.

Even today, women and men are often exposed to different learning environments, for example due to their choice of studies and profession. If we observe gender differences in the tests, we do not know whether these differences were influenced by the genes or their different environments (presumably an interaction of both)1.

One possible approach is to look at different cultures, which provide different environments. If gender differences exist consistently across different environments, that´s an indicator they might be innate. Tests with children are carried out because stereotypes had less time on them to manifest. But, of course, every human being is exposed to and shaped by her environment from the day of birth. Children whose survival depends on the care of their environment have a particularly high incentive to behave in a likable way.

To be enjoyed with caution

Before we get started, let´s remember the assumptions we have made implicitly. We assume that we …

  1. can generalize the test results to the whole population of our society
  2. have actually measured the cognitive performance we wanted to. The results of the SAT test, for example, can be predicted by mental rotation by 64 percent. Instead of reading, arithmetic and writing skills, the test seems to measure primarily the ability of mental rotation.

Predictive and functional thinking

Inge Schwank (1990 Osnabrück, Germany) examined different approaches to programming and found that success depended largely on how the task was set. She then distinguished between two different styles of thinking:

Functional thinking:

Functional thinkers refer to the purpose and function of objects and focus on the relationships between objects.

e.g. „You can throw the ball and play football with it.“

Functional thinking is more process-oriented. You describe how something works and what can happen.

Predictive thinking:

Predictive thinkers have the whole picture in mind. They tend to use predicates and relations in descriptions.

e.g. „The ball is round.“

Predictive thinking has a static character describing the IS – situation.

In the tendencies with which the different thinking styles are used, we see a clear difference between the sexes2:

 [visualizer id=“1264″] 

 [visualizer id=“1268″] 

The clear majority of girls tend towards predictive thinking, whereas boys don´t show such a clear preference. The majority uses primarily functional thinking, but one third are predictive thinkers. It remains to be seen whether this theory of thinking styles can also be applied to other areas, since Schwank only examined programming.


These results suggest that the performance of pupils also depend on how tasks are presented to them and therefore as well who writes them. Predictive thinkers have to understand the entire problem first including all aspects, while functional thinkers simply start, try things out and thus come across connections.

Set theory and algebra require more predictive, infinitesimal calculus more functional thinking. How nice it would be if we can explain everything to all students in a suitable presentation. Intelligent pupils can translate tasks for themselves. However, this costs them time. Physics largely requires functional thinking. So that would explain why girls could catch up in math, but hardly in physics. According to the study, 80 percent of girls are predictive thinkers, but 65 percent of boys are functional thinkers.


Very few students run into their classes in the morning joyfully and full of enthusiasm to find out what they will learn today. In addition to stress and pressure, there is often also the question of „Why?“; „Why do I have to learn that? Who is that supposed to help?“ or „The task is ridiculous. Why would I go somewhere to build a house, but have nothing to measure?“. As it turns out the different thinking styles could have an influence on the motivation wanting to find a solution.

Dörner6 (1989 according to Bischof-Köhler 2006) tested solving realistic problems. Using computer simulations, his team asked the test subjects to implement development aid measures. The results did not correlate at all with the results of the intelligence tests. Furthermore, here the sexes did not differ in efficiency of the planning.

Math problems, on the other hand, usually give little information about the situation or even the reason why a problem must be solved at all. Qualitative aspects often find no place in the task´s description. Additionally, a given solution simply has to be applied which is not how things are in reality. In everyday problems, framework conditions often play a very important role in finding a solution and there are no given approaches. Perhaps pupils who value qualitative aspects and holistic views have lower motivation in such tasks. According to the study that would predominantly apply to girls as predictive thinkers.

Evolutionary perspective

Let us look at the perspective of why certain cognitive achievements may have been distributed differently among the sexes over millions of years.

Evolution of predictive and functional thinking

In the vast majority of cultures, women took on the role of family managers in addition to other tasks. As such, they had to know and coordinate a lot of details of the daily schedules of all family members. Predictive thinking is very advantageous for doing a good job in keeping everything running smoothly.

For men, on the other hand, it was often necessary to concentrate on a single problem. Men’s activities were less consistent across cultures than those of women. Perhaps that is why men do not have such a clear predominant style of thinking. These thoughts do not explain how the differences in thinking styles came about, but why they might have held over millions of years.

Evolution of other differences in cognitive performance

An excellent spatial orientation is probably very well suited for a big hunting trip. Collectors also had to find their way back home, but in a much slower version. Because collectors moved more strategically through the landscape and kept a smaller radius of action, it was probably more helpful to be able to remember placemarks3. Of course, these are just possibilities why men have slight advantages in spatial visualization, while women score a bit better in memory.

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Even if evolutively certain inclinations have prevailed, this does not mean that a corresponding behaviour will show. Instead, it is always an interplay between characteristics and socialization.

Encouraging congenital differences

For example, boys tend to show a stronger interest in explorative behaviour. If his interest is then praised by the environment and even further encouraged, for example by his father, a boy would end up receiving more training in exploring than a girl. Consequently he will probably become better. We observe a similar situation in mothers and daughters with regard to linguistic aptitude. Girls tend to show more interest in communication, which the mothers find rewarding and speak more to the daughters accordingly. A slightly higher congenital interest turns into more practice and eventually into higher ability.

Often it is not only actual congenital differences in the children that make parents treat boys and girls differently, but their stereotypes which they project onto their children. So they train their children unconsciously towards their own expectations and in the end, children develop accordingly. Thus, stereotypes are further confirmed in their minds.


We see girls getting better grades in math at school. Nevertheless, they do worse in the SAT and other math tests than boys. Maybe Girls try harder at school and then cannot apply their learned knowledge to the different tasks. It is also conceivable that a higher fear of testing prevents them from using their full performance potential in these moments.

Mathematics continues to be regarded a boys‘ subject. Parents assume that boys bring the higher talent. At worst, they believe that their daughters only have to ´somehow survive´ math in school. The effect on girls‘ self-confidence is immense. Some girls consider themselves bad in math without ever having given it a chance. Far too often, the skepticism of others causes girls to actually do worse as a result. This is called a self-fulfilling prophecy. In the case of math, we see how a stereotype adopted from outside affects actual performance. Even highly gifted girls simply do not believe in themselves.

We also know that there is a general effect that girls tend to attribute positive results to happy circumstances, while boys attribute positive results to their own ability4. Some studies show, moreover, that boys are more praised in mathematics than girls5. So girls might lack possibilities to grow self-confident in math.

Another aspect could be that young men define themselves more by their individual mathematical performance and young women by their social concerns and relationships7. Therefor boys have the higher motivation to achieve better scores.


The human brain consists of two halves and each half has its specializations. For example, we mainly need the left half of our brain for analytical tasks, reasoning and language-related performance, whereas the right half is the professional for spatial orientation, holistic comprehension, descriptive presentation and musicality. We call this functional asymmetry lateralization of the brain.

lateralization - cognitive performance - happyjona
Visualization of the brain hemispheres incl. their specializations

In men, a correlation between mathematical aptitude and left-handedness has been established. It is possible that cognitive differences between the sexes are due to the way they use the right hemisphere8. Other studies showed that women tend to have a stronger network between the two halves of the brain and are more likely to use both to solve problems (bilateral). In comparison men have a closer networking within the hemispheres9 and might use one hemisphere only per activity. That would mean that men show a higher lateralization.

Levy (1976) presented an interesting thesis on this subject, which has not yet been proven. The so-called „crowding hypothesis“ assumes that individual abilities compete with each other within a hemisphere. For example, if spatial-visual and linguistic abilities compete because both halves of the brain are used, the more dominant (linguistic) ability would suppress the other. This could lead to a situation in which the spatial imagination is not optimally developed in women, who tend to use both hemispheres.

Lateralization and hormons

With regard to lateralization, hormones come into play. Androgens, a predominantly male sex hormon, have a slowing effect on the growth of the left hemisphere. For this reason, the right hemisphere can meanwhile develop faster. Because with puberty androgens are increasingly released, that would explain why there is a momentum of boys in MINT subjects around this period.

So what about the female estrogen? Nyborg (1990) was able to show that a certain estrogen concentration is necessary for optimal spatial-visual performance, while insufficient estrogen leads to extremely low performance. With estrogen treatment, the levels improved dramatically, which has been demonstrated in patients with Turner syndrome who have only one X chromosome. According to Nyborg, women have more estrogen than necessary for optimal performance and men have too little, but are closer. This theory is also supported by the fact that women show better spatial-visual performance during menstruation.

» next topic:


Now we have already scratched that hormones influence the development of the brain. Let’s get on with it »


  1. Abruf 12.07.2019
  2. Bischof-Köhler 2006, S. 233 – 235
  3. Kimura 1999
  4. Hyde et al., 1990 nach Bischof-Köhler 2006 S. 229
  5. Eccles-Parsons et al., 1982
  6. Dörner 1989 nach Bischof-Köhler 2006
  7. Feather, 1988
  8. Abruf 13.07.2019
  9. Abruf 13.07.2019

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