The Relationship between Handedness and Mathematics Is Non-linear and Is Moderated by Gender, Age, and Type of Task

Abstract

The relationship between handedness and mathematical ability is still highly controversial. While some researchers have claimed that left-handers are gifted in mathematics and strong right-handers perform the worst in mathematical tasks, others have more recently proposed that mixed-handers are the most disadvantaged group. However, the studies in the field differ with regard to the ages and the gender of the participants, and the type of mathematical ability assessed. To disentangle these discrepancies, we conducted five studies in several Italian schools (total participants: N = 2,314), involving students of different ages (six to seventeen) and a range of mathematical tasks (e.g., arithmetic and reasoning). The results show that (a) linear and quadratic functions are insufficient for capturing the link between handedness and mathematical ability; (b) the percentage of variance in mathematics scores explained by handedness was larger than in previous studies (between 3 and 10% vs. 1%), and (c) the effect of handedness on mathematical ability depended on age, type of mathematical tasks, and gender. In accordance with previous research, handedness does represent a correlate of achievement in mathematics, but the shape of this relationship is more complicated than has been argued so far.

Full text

ORIGINAL RESEARCH
published: 09 June 2017
doi: 10.3389/fpsyg.2017.00948
Frontiers in Psychology | www.frontiersin.org 1June 2017 | Volume 8 | Article 948
Edited by:
Rick Thomas,
Georgia Institute of Technology,
United States
Reviewed by:
John David Jasper,
University of Toledo, United States
Martina Manns,
Ruhr University Bochum, Germany
*Correspondence:
Giovanni Sala
giovanni.sala@liv.ac.uk
†Present Address:
Giulia Barsuola
Center for Information and Neural
Networks (CiNet), Osaka University,
Japan
Specialty section:
This article was submitted to
Cognitive Science,
a section of the journal
Frontiers in Psychology
Received: 30 November 2016
Accepted: 23 May 2017
Published: 09 June 2017
Citation:
Sala G, Signorelli M, Barsuola G,
Bolognese M and Gobet F (2017) The
Relationship between Handedness
and Mathematics Is Non-linear and Is
Moderated by Gender, Age, and Type
of Task. Front. Psychol. 8:948.
doi: 10.3389/fpsyg.2017.00948
The Relationship between
Handedness and Mathematics Is
Non-linear and Is Moderated by
Gender, Age, and Type of Task
Giovanni Sala 1*, Michela Signorelli 2, Giulia Barsuola 3 †, Martina Bolognese 2and
Fernand Gobet 1
1Department of Psychological Sciences, University of Liverpool, Liverpool, United Kingdom, 2Department of Oncology and
Hemato-Oncology, University of Milan, Milan, Italy, 3Maastricht University, Maastricht, Netherlands
The relationship between handedness and mathematical ability is still highly controversial.
While some researchers have claimed that left-handers are gifted in mathematics and
strong right-handers perform the worst in mathematical tasks, others have more recently
proposed that mixed-handers are the most disadvantaged group. However, the studies
in the field differ with regard to the ages and the gender of the participants, and
the type of mathematical ability assessed. To disentangle these discrepancies, we
conducted five studies in several Italian schools (total participants: N=2,314), involving
students of different ages (six to seventeen) and a range of mathematical tasks (e.g.,
arithmetic and reasoning). The results show that (a) linear and quadratic functions
are insufficient for capturing the link between handedness and mathematical ability;
(b) the percentage of variance in mathematics scores explained by handedness was
larger than in previous studies (between 3 and 10% vs. 1%), and (c) the effect of
handedness on mathematical ability depended on age, type of mathematical tasks, and
gender. In accordance with previous research, handedness does represent a correlate
of achievement in mathematics, but the shape of this relationship is more complicated
than has been argued so far.
Keywords: handedness, mathematics, lateralization, non-linearity, cognitive ability
INTRODUCTION
Students’ achievement in mathematics is a matter of high practical relevance. Mathematical skill
is necessary to major in Science, Technology, Engineering, and Mathematics (STEM) subjects,
and therefore to attain STEM jobs. The job market requires worldwide more graduates in STEM
subjects than in other disciplines (e.g., humanities, social sciences) and has also become increasingly
more competitive (Halpern et al., 2007). For this reason, the cognitive and biological correlates of
mathematical ability have been the object of extensive debate (e.g., Deary et al., 2007; Rohde and
Thompson, 2007; Wai et al., 2009; Lubinski, 2010; Peng et al., 2016). One of these correlates is
handedness.
Handedness is a manifestation of the lateralization of human brain function, and consequently,
hand preference is believed to affect human overall cognitive skills (McManus, 2002). However,
in spite of much research carried out on this topic, the shape of this relationship is still highly
controversial.

Sala et al. Handedness and Mathematical Ability
The effect of handedness on mathematical ability have been
a matter of interest too (e.g., Annett and Kilshaw, 1982; Benbow,
1986, 1987; Annett and Manning, 1990; Crow et al., 1998; Cheyne
et al., 2010). However, no distinct pattern of results has emerged
from the research addressing this topic. For example, while some
studies considered left-handedness as a sign of giftedness in
mathematics (e.g., Benbow, 1986), others found that left-handers
performed slightly worse than right-handers on measures of
mathematical ability (e.g., Johnston et al., 2013). The unclear
relationship between handedness and mathematics reflects
the discrepancies between the models relating handedness to
cognitive abilities. In fact, according to Nicholls et al. (2010), four
main models linking handedness to human cognition have been
proposed. Each of these models makes different predictions about
how handedness affects mathematical ability.
One of the most influential models linking handedness,
cognition, and mathematical ability is Annett’s (1985, 2002)
right shift theory. According to this theory, most people inherit
the so-called “right-shift factor,” which is a dominant allele
(RS+) that predisposes them to be both right-handed and left-
hemisphere dominant for language. Whoever inherits this allele
has a good probability of being right-handed (see Corballis,
1997, for a review). While people with a heterozygous genotype
(RS±) are mostly moderately right-handed (i.e., they do not
show an exclusive preference for the right hand in experimental
or daily life tasks), and benefit from a balanced cognitive
profile, those who inherit a homozygous genotype for the
RS+are mostly strongly right-handed and may suffer from a
deficit in spatial ability, because of the costs the RS+allele
to the right-hemisphere. Finally, in people who do not inherit
the right-shift factor (i.e., homozygous for the RS– allele),
handedness is determined by random factors (active during fetal
development) and by environmental pressure on hand use. In
this situation, a person ends up being randomly either right- or
left-handed, and may suffer from a deficit specific to language
ability.
Annett’s right-shift theory thus predicts a general cognitive
advantage for moderate right-handers. In line with this
hypothesis, Annett (1992) found an advantage in spatial ability
for moderate right-handers in a sample of 14–15-year-olds.
Further support for this hypothesis was also provided by Casey’s
(1995, 1996a) studies, which found an advantage for moderate
right-handers in general intelligence in a sample of primary
school children, and mental rotation ability in a sample of female
college students, respectively. However, some studies failed to
replicate these outcomes (e.g., McManus et al., 1993; Cerone and
McKeever, 1999). Finally, a more recent study (Nicholls et al.,
2010) showed that moderate right-handers performed slightly
better than the rest of the sample in a test measuring several
cognitive skills such as attention, executive functions, language
ability, and memory. Interestingly, in that study, both strong
right- and left-handers achieved the worst results, thus showing a
quadratic relationship between hand skill and test scores.
Concerning mathematical ability, Annett’s right shift theory
predicts a disadvantage for strongly right-handed individuals
(Peters, 1991) and an inverse linear relationship between
dextrality. Since mathematical ability relies to a large extent on
spatial ability (Wai et al., 2009; Lubinski, 2010), those who inherit
the homozygous dominant genotype are more likely to perform
poorly in mathematics (Annett and Manning, 1990).
Following another line of research, Benbow (1986)
claimed that left-handedness is a predictor of mathematical
precociousness in young students. In that study, it was found that
the rates of left-handers among students talented in mathematics
were much greater than among the general population. Benbow
(1986) found that the frequency of left-handedness among gifted
students was significantly higher than in the general population.
Moreover, this alleged superiority of left-handers seems to occur
mostly in males and when mathematical ability is assessed with
tasks involving reasoning (e.g., mathematical problems; Benbow,
1988).
Benbow’s hypothesis—i.e., left-handers tend to be
overrepresented among gifted students—is based on the
fact that left-handers are more likely1to have a more developed
right-hemisphere (Geschwind and Behan, 1984; Geschwind
and Galaburda, 1987; O’Boyle and Benbow, 1990), which is
involved in processes related to mathematical ability—such
as spatial reasoning (Ganley and Vasilyeva, 2011) and mental
rotation ability (O’Boyle et al., 2005; Hoppe et al., 2012), and
a larger corpus callosum (Witelson, 1985; Beaton, 1997). This
may foster interhemispheric connectivity and bi-hemispheric
representation of cognitive functions (Benbow, 1986), with
positive effects on left-handed individuals’ intellectual skills,
such as verbal reasoning (Halpern et al., 1998) and verbal
fluency (Hines et al., 1992), episodic memory (Christman and
Propper, 2001), intelligence among gifted children (Hicks and
Dusek, 1980), and spatial abilities (Casey et al., 1992; Reio et al.,
2004). In addition, the relationship between left-handedness and
giftedness seems to occur in several domains. For example, left-
handedness appears to be more common among gifted musicians
(Kopiez et al., 2006), chess players (Gobet and Campitelli, 2007;
Oremosu et al., 2011), artists (Preti and Vellante, 2007), and
mathematicians (Annett and Kilshaw, 1982).
Recently, however, the idea that left-handedness is a predictor
of superior intellectual ability has been challenged. Several
authors have claimed that left-handedness is not related
to any advantage in cognitive skills, and may even exert
detrimental effects on general cognitive abilities and hence
academic achievement. Left-handedness may be caused by
left-hemisphere damage occurring pre- or peri-natally (Satz
et al., 1985), and consequently, a portion of left-handed
individuals may suffer from an overall cognitive deficit. In
line with this hypothesis, Johnston et al. (2009) found that
left-handed children slightly underperformed in a series of
developmental measures, compared to right-handers. Also, two
recent meta-analyses (Papadatou-Pastou and Tomprou, 2015;
Somers et al., 2015) reported that left-handers were over-
represented among intellectually challenged individuals and did
1It is worth mentioning that there is not a perfect correspondence between
handedness and lateralization of cognitive function. For example, only about 40%
of left-handers have their motor speech area located in the right-hemisphere
(Gutwinski et al., 2011). Analogously, only one third of the people with more
developed right hemisphere are not right-handed (Geschwind and Behan, 1984).
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Sala et al. Handedness and Mathematical Ability
slightly worse in spatial ability tasks, respectively. Consistent
with these results, Johnston et al. (2013) found that left-handers
underperformed in mathematical ability in a sample of children
aged 5–14.
The last theory drawing a causal link from handedness
to mathematical ability through cognition is the hemispheric
indecision hypothesis (Crow et al., 1998). This theory focuses
on the importance of handedness as a continuous variable, in
opposition to the dichotomy left/right. The lateralization of
brain function seems to be an advantage from an evolutionary
perspective, because it obviates functional redundancy, and
therefore makes neural processing run more efficiently
(Gutwinski et al., 2011). Thus, the most decisive factor is
how much a person is right or left-handed because a weak
lateralization may be associated with a delay in development
(Orton, 1937; Zangwill, 1960; Bishop, 1990).
This hypothesis has recently received empirical support. Crow
et al. (1998) found that the tendency to show an equal skill for
right and left hand in a square-checking task predicted deficits in
verbal, non-verbal, and mathematical abilities in a sample of 11-
year-old children. Peters et al. (2006) reported that individuals
with no preferred hand in writing had the lowest performance
in mental rotation ability. Corballis et al. (2008) observed that
children who had no hand preference for writing performed
significantly worse than right- and left-handers in several tasks
including arithmetic, memory, and reasoning. Finally, Cheyne
et al. (2010) found similar results in a large sample of 11-year-old
children.
MATERIALS AND METHODS
The Present Study
The research that has been carried out on the effects of
handedness on mathematical ability depicts an intricate
tapestry. The outcomes of the studies are, at least partially,
contradictory, and it is hard to infer a definitive conclusion
from them. However, research also suggests that one reason for
the discrepant findings may be methodological inconsistencies.
Studies differed with regard to (a) how participants were
categorized according to handedness (e.g., right-/left-handers,
right-/left-/mixed-handers, non-right-/right-handers), which
causes difficulties for comparing the outcomes between
studies (Casey, 1996b; Cerone and McKeever, 1999; Li et al.,
2003; Nicholls et al., 2010); (b) ages and educational levels
(e.g., primary school children, middle- and high-school
students, adults) of the participants; and (c) the specific
mathematical abilities assessed (e.g., simple arithmetic or
problem-solving).
The aim of this study was to reconcile the discrepancies
observed in previous research in the field. First, we used
a continuous measured of handedness without using any
categorization. Second, we systematically manipulated
the age of the participants and the mathematical tasks to
evaluate the effect of these moderating variables on the
relationship between handedness and performance on tests of
mathematics.
A Theoretical Challenge: The Use of
Quartic Functions
Along with the abovementioned methodological issues, another
aspect of the research in the field may be a critical limitation.
While the four theories we have reviewed differ in important
ways, a common characteristic is that they consider the link
between handedness and mathematical ability as dichotomous
(e.g., left-handers vs. than right-handers), or, when a continuous
measure of handedness is used, linear or quadratic. However,
no study, to the best of our knowledge, has investigated
the possibility that the relationship between handedness and
mathematical ability is more complex and requires a polynomial
function with a cubic and quartic term to be described properly.
Quartic functions can have up to five maxima and minima
(three relative, and two at the extremes of the domain),
be both monotonic and non-monotonic, and reduce into
smaller-degree functions if necessary (by attributing the value
0 to one or more coefficients). For these reasons, quartic
functions may be able to detect patterns of the relationship
between handedness and mathematical ability impossible to
identify with categorical measures or quadratic functions.
Thus, our hypothesis is that including cubic and quartic
terms in polynomial functions substantially contributes to the
amount of variance in mathematical ability accounted for by
handedness.
Procedure
We ran five experiments differing from each other regarding
the age of the participants and the type of mathematical
skills assessed (e.g., arithmetic, reasoning). The aims of these
experiments were (a) to evaluate which of the models introduced
above best describes the relationship between handedness and
mathematical ability; (b) to investigate the mediating effect of
age, gender, and type of task on the link between handedness and
mathematical ability; and (c) to quantitatively assess the effect of
handedness on mathematical ability by calculating the percentage
of variance (R2) of the participants’ scores in mathematics
explained by handedness, using 4th-degree polynomials.
The participants, aged 6–17, were recruited in Italian schools,
between December 2013 and June 2015. Most of the participants
(∼80–85%) were from Italian middle-class families, while the
rest were from foreign families.2All the participants spoke fluent
Italian and were not diagnosed with any learning disability.
Parental consent was obtained for all the participants.3The
2Due to restrictions related to Italian privacy laws, we could not collect
any information about parental income and countries of provenance of the
participants. The large majority of the participants with foreign origins consisted of
children from Eastern Europe and Northern Africa who were born or spent most of
their lives in Italy. With regard to parental income, Johnston et al. (2009) reported
that handedness was not related to socioeconomic characteristics in a large sample
of children. Thus, there is no reason to think that socio-economic status may be a
confounding variable for the present study.
3Most of the parents provided the school with written and informed consent. In
some cases, the schools had previous official agreements with the parents regarding
the type (e.g., paper and-pencil tests) of permitted activities their children could
engage in. In the remaining cases, the schools adopted other customary practices
(e.g., opt-out consent). This process was entirely led by the principals (who are
the legal representatives of the schools) or a delegate teacher. This study was not
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Sala et al. Handedness and Mathematical Ability
participants were administered (a) a set of different tests assessing
mathematical ability (one for each experiment), and (b) the
10-item version of the Edinburgh Handedness Inventory (EHI;
Oldfield, 1971)4. EHI is a multiple-item questionnaire, and thus
is more sensitive and reliable than categorical measures of hand
preference (Johnston et al., 2009). EHI provides a continuous
measure of handedness (H), which was calculated using the
formula:
H=R−L
R+L
where Rand Lindicate the number of preferences for the
right and left hand, respectively. The range of values is between
−1, for extreme left-handedness, and +1, for extreme right-
handedness. Importantly, the participants were not divided into
groups according to their hand preference. In fact, categories
(e.g., right-handers, left-handers, and mixed-handers) are always
arbitrary to some extent and hence may cause difficulties for
comparing outcomes.
Data Analysis
Since our data were nested (i.e., most of the participants
were recruited from different schools), a multi-level linear
modeling (Goldstein, 2011) approach was applied to control
for possible confounding effects (e.g., Type I error) due to
the school of provenance of the participants. As noticed by
several authors (e.g., Cheyne et al., 2010; Nicholls et al., 2010),
the relationship between handedness and academic skills is
not necessarily linear. Therefore, preliminarily to building the
models, a series of linear regression analyses (method backward)
was performed with H,Hquadratic (H2), cubic (H3), and quartic
(H4) functions as possible predictors, to look for potential non-
linear (i.e., polynomial) relationships between Hand scores in
mathematics.5Then, the functions of H[i.e., F(H)] calculated
by the linear regression analysis were inserted—along with the
participants’ age and gender—into the models as independent
variables. For each experiment, three multi-level linear models
were run and compared to each other: the intercept model,
the model including all the independent variables except the
functions of handedness, and the model including all the
independent variables. Finally, two additional regression analyses
were performed (with predictors Hand its functions) for
males and females separately, in order to investigate possible
gender differences in the relationship between handedness and
mathematical ability.
required to be reviewed and approved by an ethics committee according to the
national and institutional requirements for this type of research.
4The item “striking a match” was considered inappropriate and obsolete for the
participants, and thus with the item “dealing cards” (Groen et al., 2013).
5It must be mentioned that the current investigation does not directly address
the issues regarding the dichotomy between direction (i.e., positive or negative
EHI score) and degree (i.e., how far from zero the EHI score is) of handedness
(for an outlook on this debate, see Prichard et al., 2013). Additional research is
needed to evaluate the role of the direction and degree of handedness in affecting
cognitive/academic skills.
EXPERIMENT 1
In this experiment, we investigated the relationship between
handedness and mathematical precocity in a sample of
children aged 7–9. To evaluate whether Benbow’s (1986, 1988)
hypothesis—i.e., left-handers tend to be more precocious in
mathematics—generalizes to the general population of third and
fourth graders, we used items designed to assess the mathematical
ability of 15-year-old students.
Method
Participants
A total of 413 third and fourth graders (187 males, 226 females)
with a mean age of 8.32 (SD =0.62) years took part in this
experiment only. The participants were recruited from five
different schools in Italy.
Procedure
Along with the EHI, the participants were administered a set of
seven OECD-Pisa items (OECD, 2012) assessing mathematical
skill (score range 0–7). These items require the student to
infer the correct solution from a given set of data and hence
involve mathematical reasoning ability. In all the seven items, the
participants were asked to choose one of the five possible answers.
The OECD-Pisa items are designed for students aged 15.
Therefore, we expected the children to perform relatively
poorly. Nonetheless, the contents of the selected items were
manageable for children of third and fourth grades (e.g.,
problems involving only whole numbers, operations of addition
and subtraction, and simple geometry), and the instructions were
easily understandable.
Results
The mean score for Hwas 0.584 (SD =0.470), while the mean
score for mathematics was 1.55 (SD =1.16). The linear regression
analysis showed that only the quartic function of H(i.e., H4)
was significantly correlated to the scores in mathematics (b4=
−0.312, t= −2.073, r=0.102, R2=0.010, p=0.039; intercept
=1.684, p<0.001). The quartic function can be appreciated in
Figure 1A.
The multi-level linear models showed a significant effect of
age, no effect of gender, and only a marginally significant (p<
0.10) effect of H4(Table 1). The effect of the school of provenance
(random factor) was not significant.
Gender Analysis
Two linear regression—one for males and one for females—were
performed. The analysis showed no predictor in males, whereas it
did in females (b1= −1.275, b3=1.242, b4= −0.885, t=2.547,
r=0.284, R2=0.081, p<0.001; intercept =2.102, p<0.001).
The following function
F(H)= −1.275 H+1.242 H3−0.885 H4+2.102
depicting the relationship between Hand mathematics scores in
females can be seen in Figure 1B.
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Sala et al. Handedness and Mathematical Ability
FIGURE 1 | (A) The function [F(H)] of handedness (H) correlating with the score
of mathematics in the whole sample. The blue circles represent F(H) values for
the Hvalues for which there were human observations. The black dots
represent the trend line. The values on the y-axis were normalized by dividing
F(H) by the possible maximum score (i.e., 7) on the test of mathematical ability.
(B) The function [F(H)] of handedness (H) correlating with the score of
mathematics in the female sample. The blue circles represent F(H) values for
the Hvalues for which there were human observations. The black dots
represent the trend line. The values on the y-axis were normalized by dividing
F(H) by the possible maximum score (i.e., 7) on the test of mathematical ability.
TABLE 1 | Parameters, coefficients, and standard errors in the multilevel models
of Experiment 1.
Parameter Model 1 Model 2 Model 3
FIXED EFFECTS
Intercept 1.555 (0.076)*** −2.298 (0.759)** −2.092 (0.765)**
Age 0.449 (0.090)*** 0.438 (0.090)***
Gender 0.175 (0.111) 0.169 (0.110)
H4a −0.256 (0.145)†
RANDOM PARAMETERS
Intercept (School) 0.014 (0.018) 0.026 (0.026) 0.025 (0.025)
−2*log likelihood 1,290.6 1,263.5 1,260.4
***p<0.001, Two tailed; **p<0.01, two tailed; *p<0.05, two tailed; †p<0.10, two
tailed.
aThe intercept was not inserted in the model because it is superfluous.
Discussion
The results of this experiment suggest a quartic relationship
between handedness and mathematical ability, especially for
females. Benbow’s (1986) hypothesis that left-handedness is a
predictor of precocity in mathematical reasoning ability is not
supported. In fact, the results appear to suit more—marginally in
the whole sample, and significantly in females—Annett’s (2002)
conception of the disadvantage of the extremes.
EXPERIMENT 2
Experiment 1 showed a quartic relationship between H
and scores in mathematics, especially in females. However,
the low scores achieved by the participants, due to the
difficulty of the mathematical tasks, may have hidden other
potential relationships between the two variables (e.g., the same
relationship in males as well).
In this experiment, we replaced the OECD-Pisa items
with six items designed for assessing mathematical literacy in
fourth graders, and hence more suitable for the participants.
Thus, we investigated the relationship between handedness and
mathematical reasoning ability in primary school children again,
but not focusing on mathematical precocity.
Method
Participants
A total of 300 (151 males, 149 females) third and fourth graders
took part in this experiment only. The participants’ mean age was
8.46 (SD =0.67) years. The children were recruited from nine
schools in northern Italy.
Procedure
The participants were administered the EHI and a test
consisting of six items of IEA-TIMSS (Mullis and Martin, 2013)
international survey assessing mathematical literacy in fourth
graders. Similar to OECD-PISA, the items of the IEA-TIMSS
survey require solving a mathematical problem from a given set
of data. The participants have to select an option among four
possible answers.
Results
The mean score for Hwas 0.614 (SD =0.529), while the mean
score for mathematics was 2.57 (SD =1.33). The regression
analysis showed that only the quartic function of H(i.e., H4)
was significantly correlated to the scores in mathematics (b4=
−0.438, t= −2.244, r=0.130, R2=0.017, p=0.026; intercept =
2.801, p<0.001; Figure 2A).
The multi-level linear models showed a significant effect of
gender, H4, and age (Table 2), while the effect of the school of
provenance (random factor) was not significant.
Gender Analysis
Regression analysis showed that H4was still a predictor
of the dependent variable (mathematics scores) for males
(b4= −0.779, t= −2.649, r=0.212, R2=0.045, p=
0.009; intercept =3.239, p<0.001; Figure 2B), but not for
females.
Discussion
The results showed that the children at the two extremes of
the distribution tended to achieve the poorest performance,
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Sala et al. Handedness and Mathematical Ability
FIGURE 2 | (A) The function [F(H)] of handedness (H) correlating with the score
of mathematics in the whole sample. The blue circles represent F(H) values for
the Hvalues for which there were human observations. The black dots
represent the trend line. The values on the y-axis were normalized by dividing
F(H) by the possible maximum score (i.e., 6) on the test of mathematical ability.
(B) The function [F(H)] of handedness (H) correlating with the score of
mathematics in the sample of males. The blue circles represent F(H) values for
the Hvalues for which there were human observations. The black dots
represent the trend line. The values on the y-axis were normalized by dividing
F(H) by the possible maximum score (i.e., 6) on the test of mathematical ability.
TABLE 2 | Parameters, coefficients, and standard errors in the multilevel models
of Experiment 2.
Parameter Model 1 Model 2 Model 3
FIXED EFFECTS
Intercept 2.532 (0.105)*** −0.593 (0.948) −0.172 (0.956)
Age 0.349 (0.113)** 0.325 (0.112)**
Gender 0.412 (0.149)** 0.448 (0.149)**
H4a −0.447 (0.190)*
RANDOM PARAMETERS
Intercept (School) 0.041 (0.043) 0.000b(0.000) 0.000b(0.000)
−2*log likelihood 1,018.5 1,002.1 996.7
***p<0.001, Two tailed; **p<0.01, two tailed; *p<0.05, two tailed.
aThe intercept was not inserted in the model because it is superfluous.
bThe coefficient is set to 0 because it is redundant.
but among males only. This outcome again supported Annett’s
(2002) conception of the disadvantage of the extremes. In this
experiment too, gender moderated the effect that handedness
exerted on the scores in mathematics. We will take up this issue
in the General Discussion.
EXPERIMENT 3
While the previous two experiments examined the effect
of handedness on children’s ability to solve mathematical
tasks involving reasoning, this experiment evaluated the role
of handedness on children’s arithmetical ability. The used
arithmetical tasks demanded only the knowledge and the
application of simple algorithms (e.g., adding in column).
Moreover, those who took part in this and the following
two experiments were administered a mental rotation ability
(MRA) task. Since MRA has been proposed as one possible
link connecting handedness to mathematical ability (Annett and
Manning, 1990; Casey et al., 1992), we tested whether the effect of
handedness on arithmetical ability would remain significant even
when MRA was controlled for.
Method
Participants
One-hundred and sixty-two (78 males, 84 females) children took
part in this experiment only. The participants were first, second,
and third graders, and their mean age was 7.79 (SD =0.89) years.
The participants were recruited from one school in northern
Italy.
Procedure
The participants were administered (a) the EHI,6(b) a test of
arithmetic, designed by the experimenters (score range 0–27),
and (c) a 2-D mental rotation ability task suitable for children
(score range 0–16; for details, see Cheng and Mix, 2014). In the
test of arithmetic, the participants solved simple mathematical
equations (e.g., 3 +4=?) and missing-term problems (e.g.,
3+?=7).
Results
The mean score was 0.604 (SD =0.473) for H, 17.43 (SD =8.28)
for the scores in arithmetic, and 13.65 (SD =2.51) for mental
rotation ability. The regression analysis showed that only the
cubic function of H(i.e., H3) was significantly correlated to the
scores in mathematics (b3= −3.192, t= −2.192, r=0.171, R2
=0.029, p=0.030; intercept =18.759, p<0.001), which can be
appreciated in Figure 3.
The multi-level linear models showed a significant effect of
F(H), mental rotation skills, and age, but no effect of gender
(Table 3).
Moreover, the analysis showed no significant correlation
between F(H) and MRA scores (r= −0.053, p=0.504).
Gender Analysis
The regression analysis did not find any significant predictors
either in males or females.
6The youngest participants (i.e., first graders; 6- and 7-year-olds) were read
the instructions of the questionnaire. When necessary, the testers explained the
inquired manual act and asked the children to mimic it.
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Sala et al. Handedness and Mathematical Ability
FIGURE 3 | The function [F(H)] of handedness (H) correlating with the score of
mathematics in the whole sample. The blue circles represent F(H) values for the
Hvalues for which there were human observations. The black dots represent
the trend line. The values on the y-axis were normalized by dividing F(H) by the
possible maximum score (i.e., 27) on the test of mathematical ability.
TABLE 3 | Parameters, coefficients, and standard errors in the multilevel models
of Experiment 3.
Parameter Model 1 Model 2 Model 3
FIXED EFFECTS
Intercept 17.426 (0.648)*** −44.883 (3.429)*** −43.353 (3.390)***
Age 7.083 (0.431)*** 7.036 (0.421)***
Gender 0.818 (0.742) 0.839 (0.724)
MRA 0.543 (0.155)*** 0.527 (0.151)***
H3a −2.302 (0.811)**
RANDOM PARAMETERS
Intercept (School) 0.000b(0.000) 0.000b(0.000) 0.000b(0.000)
−2*log likelihood 1,143.6 958.1 950.3
***p<0.001, Two tailed; **p<0.01, two tailed; *p<0.05, two tailed.
aThe intercept was not inserted in the model because it is superfluous.
bThe coefficient is set to 0 because it is redundant.
Discussion
The results showed that handedness exerted a significant effect
on the scores in mathematics even when MRA was controlled
for. Interestingly, MRA and the function of handedness
correlated with the scores in mathematics were not significantly
correlated. This outcome suggests that the effects of handedness
and MRA did not overlap. With respect to the shape
of the relationship between handedness and arithmetical
ability, the function showed a monotonic trend in favor of
left-handers.
However, the relatively small number of participants may
have been insufficient to detect potential alternative patterns
among left-handers. Since left-handers were underrepresented
compared to right-handers (as in the general population),
the function might have fit the dependent variable regardless
of the few left-handers of the sample. Put simply, the
advantage of left-handers may have been due to a statistical
artifact.
EXPERIMENT 4
This experiment aimed at improving the design of the previous
one by recruiting a larger sample. We thus wanted to test the
advantage of left-handers in arithmetical tasks found in the
previous experiment.
Method
Participants
Seven-hundred and ninety-eight (417 males, 381 females)
children took part in this experiment only. The participants were
first, second, and third graders, and their mean age was 7.22 (SD
=0.91) years. The participants were recruited from six schools in
northern Italy.
Procedure
Along with the EHI7and the MRA task, the participants
were administered a test of arithmetical abilities (AC-MT 6-11;
Cornoldi et al., 2012). This test consisted of 26 items (score
range 0–26) of basic arithmetic (e.g., addition, subtraction,
multiplication, and identifying the greatest or the smallest
number in a series).
Results
The mean scores were 0.626 (SD =0.522) for H, 21.81 (SD =
4.77) for arithmetical ability, and 13.04 (SD =3.04) for mental
rotation ability. The linear regression analysis showed that the
quadratic (H2) and the quartic (H4) functions of handedness were
correlated to the scores in the arithmetic test (b2=7.763, b4=
−9.083, t=5.375, r=0.260, R2=0.068, p<0.001; intercept =
21.693, p<0.001). We thus built the following function:
F(H)=7.763 H2−9.083 H4+21.693
which is shown in Figure 4A.
The multi-level linear model showed a significant effect of
F(H), MRA, and age, whereas no significant effect of gender was
found (Table 4). The effect of the school of provenance (random
factor) was not significant.
The correlation analysis showed that F(H) and MRA were
correlated (r=0.150, p<0.001). We thus calculated the partial
correlation—with the effect of the scores in MRA being partialled
out—between F(H) and the scores in mathematics, and still
found a significant correlation (r=0.221, R2=0.049, p<0.001).
Gender Analysis
The regression analysis showed that H4was a predictor (b4=
−2.346, t= −4.220, r=0.203, R2=0.041, p<0.001; intercept
=23.337, p<0.001) of the dependent variable (mathematics
scores) in males, while H2and H4were predictors (b2=11.788,
b4= −12.739, t=4.542, r=0.314, R2=0.098, p<0.001;
intercept =20.824, p<0.001) in females. The two functions are
shown in Figures 4B,C.
No correlation was found between MRA scores and the
quartic function in males. By contrast, a significant correlation
7Like in Experiment 3, the first-graders were assisted in the administration of the
EHI (see footnote 5).
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Sala et al. Handedness and Mathematical Ability
FIGURE 4 | (A) The function [F(H)] of handedness (H) correlating with the
score of mathematics in the whole sample. The blue circles represent F(H)
values for the Hvalues for which there were human observations. The black
dots represent the trend line. The values on the y-axis were normalized by
dividing F(H) by the possible maximum score (i.e., 26) on the test of
mathematical ability. (B) The function [F(H)] of handedness (H) correlating with
the score of mathematics in males. The blue circles represent F(H) values for
the Hvalues for which there were human observations. The black dots
represent the trend line. The values on the y-axis were normalized by dividing
F(H) by the possible maximum score (i.e., 26) on the test of mathematical
ability. (C) The function [F(H)] of handedness (H) correlating with the score of
mathematics in females. The blue circles represent F(H) values for the Hvalues
for which there were human observations. The black dots represent the trend
line. The values on the y-axis were normalized by dividing F(H) by the possible
maximum score (i.e., 26) on the test of mathematical ability.
was found between MRA scores and F(H) in females (r=0.271, p
<0.001). We thus calculated the correlation between the females’
scores in mathematics and F(H) with the scores in MRA being
partialled out. This partial correlation was still significant (r=
0.234, p<0.001).
TABLE 4 | Parameters, coefficients, and standard errors in the multilevel models
of Experiment 4.
Parameter Model 1 Model 2 Model 3
FIXED EFFECTS
Intercept 22.023 (0.552)*** 3.933 (1.321)** 5.187 (1.324)***
Age 1.561 (0.171)*** 1.424 (0.171)***
Gender 0.477 (0.288)†0.423 (0.284)
MRA 0.480 (0.049)*** 0.456 (0.049)***
F(H)a0.574 (0.118)***
RANDOM PARAMETERS
Intercept (School) 1.573 (1.078) 0.873 (0.610) 0.802 (0.564)
−2*log likelihood 4,724.1 4,507.8 4,484.4
***p<0.001, Two tailed; **p<0.01, two tailed; *p<0.05, two tailed; †p<0.10, two
tailed.
aThe intercept was not inserted in the model because it is superfluous.
Discussion
The results of this experiment revealed once again that the
participants occupying the two extremes of the handedness
distribution achieved the worst scores in mathematics, and
that the pattern obtained in the previous experiment (i.e., an
advantage for left-handers over right-handers) was probably
a statistical artifact. Moreover, the mixed-handed children—
the ones in the center of the distribution—also obtained a
relatively poor performance, especially among females. The
latter outcome lends some support to the idea that mixed-
handers are disadvantaged in mathematical abilities due to their
hemispherical indecision (Crow et al., 1998; Cheyne et al., 2010).
Interestingly, the results show an M-shaped pattern—indicating
the inferior performance of the strong right- and left-handers,
and of the mixed-handers—similar to the one found for mental
rotation ability in Peters et al. (2006).
The shape of the relationship between handedness and scores
in arithmetical ability does not differ substantially between
genders. In fact, strong right- and left-handers achieved the worst
results both in males and females, and the fact that mixed-
handers do not seem to underperform among males might only
be due to lack of statistical power. However, handedness appears
to exert a greater influence on females’ than does on males’
arithmetical ability (R2=0.098 and R2=0.041, respectively).
EXPERIMENT 5
The previous experiments tested the role of handedness in
affecting children’s mathematical ability. This experiment dealt
with the relationship between handedness and high-school
students’ mathematical ability. The aim of this experiment was to
examine whether handedness maintains a significant effect also
on adolescents’ performance in mathematics.
Method
Participants
A total of 641 (211 males, 430 females) youngsters (aged 14–17)
took part in this experiment only. The participants were ninth
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Sala et al. Handedness and Mathematical Ability
and tenth graders, and their mean age was 14.71 (SD =0.76)
years. The participants were recruited from three high schools8
in northern Italy.
Procedure
The participants were administered (a) the EHI, (b) a set of
10 OECD-Pisa items (OECD, 2012; score range 0–10) to assess
mathematical ability, and (c) a revised version of Vandenberg and
Kuse’s (1978) 3-D mental rotation task assessing MRA (Version
A; Peters et al., 1995; score range 0–24).
Results
The mean scores were 0.655 (SD =0.432) for H, 5.46 (SD =
2.03) for mathematical ability, and 9.16 (SD =5.03) for MRA.
The linear regression analysis showed that the quadratic (H2) and
the cubic (H3) functions of handedness were correlated to the
participants’ scores in mathematics (b2=0.934, b3= −1.024, t
=2.524, r=0.140, R2=0.020, p=0.002; intercept =5.369, p<
0.001). We thus built the following function:
F(H)=0.934 H2−1.024 H3+5.369
which can be appreciated in Figure 5A.
The model showed a significant effect of F(H), scores in
MRA, and age, whereas no significant effect of gender was found
(Table 5). The effect of the school of provenance (random factor)
was not significant.
The correlation analysis showed no significant correlation
between F(H) and MRA scores (r= −0.050, p=0.207).
Gender Analysis
The linear regression analysis showed that H2and H3were
significant predictors (b2=1.968, b3= −1.436, t=2.625,
r=0.249, R2=0.062, p=0.001; intercept =5.431, p<
0.001) of the dependent variable (mathematics scores) in males
only (Figure 5B) whereas no effect of handedness was found in
females.
Discussion
Handedness seems to affect mathematical ability in adolescents
too. Surprisingly, this time, the left-handed participants
happened to achieve the best scores. Moreover, as shown in
Figure 5A, moderate right-handers were slightly better than
strong right-handers and mixed-handers. Finally, this pattern
occurred in males only. These outcomes support Benbow’s (1986)
idea that left-handers tend to be more talented in mathematics
and that this occurs primarily in males. It must be noticed that
this pattern occurred in a sample of the general population,
and not only among extremely talented students as in Benbow’s
(1986) study.
GENERAL DISCUSSION
The results of the five experiments show a significant effect of
handedness on the participants’ mathematical ability. The two
8The schools were labeled as liceo according to the Italian school system. Liceos are
high schools whose curricula are designed to prepare students for college.
FIGURE 5 | (A) The function [F(H)] of handedness (H) correlating with the
score of mathematics in the whole sample. The blue circles represent F(H)
values for the Hvalues for which there were human observations. The black
dots represent the trend line. The values on the y-axis were normalized by
dividing F(H) by the possible maximum score (i.e., 10) on the test of
mathematical ability. (B) The function [F(H)] of handedness (H) correlating with
the score of mathematics in the sample of males. The blue circles represent
F(H) values for the Hvalues for which there were human observations. The
black dots represent the trend line. The values on the y-axis were normalized
by dividing F(H) by the possible maximum score (i.e., 10) on the test of
mathematical ability.
TABLE 5 | Parameters, coefficients, and standard errors in the multilevel models
of Experiment 5.
Parameter Model 1 Model 2 Model 3
FIXED EFFECTS
Intercept 5.513 (0.497)** 0.225 (1.467) 0.101 (1.461)
Age 0.291 (0.094)** 0.296 (0.094)**
Gender −0.229 (0.164) −0.240 (0.164)
MRA 0.118 (0.015)*** 0.118 (0.015)***
F(H)a0.551 (0.245)*
RANDOM PARAMETERS
Intercept (School) 0.724 (0.604) 0.598 (0.503) 0.564 (0.475)
−2*log likelihood 2,610.4 2,540.1 2,535.1
***p<0.001, Two tailed; **p<0.01, two tailed; *p<0.05, two tailed.
aThe intercept was not inserted in the model because it is superfluous.
main hypotheses of this study are supported: (a) the link between
handedness and mathematical ability is more complex than linear
and quadratic, and requires a polynomial function with cubic
and quartic terms; and (b) the shape of this relationship seems
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Sala et al. Handedness and Mathematical Ability
to be moderated by participants’ age and gender and the type of
mathematical tasks used. Thus, handedness appears to be one of
the biological correlates of mathematical ability.
Several additional points must be highlighted. First, the
relationship between handedness and students’ mathematical
ability seems to be neither linear nor monotonic. This outcome
suggests that the mere comparison between right- and left-
handers is inadequate for describing how handedness and
mathematical ability interact. It is also worth noting that non-
linearity occurs in other well-known psychological phenomena,
such as decision making (e.g., Hick’s law; Hick, 1952), rate of
forgetting (Sikström, 2002), and power of learning (Anderson
et al., 1999). Second, the percentage of variance of scores in
mathematics explained by handedness was between 3% and
10%. This amount is larger than the 1% previously reported
for mathematical ability (Cheyne et al., 2010), overall cognitive
ability (Nicholls et al., 2010) and mental rotation ability (Peters
et al., 2006). Probably, this finding is due to the use of the
cubic and quartic functions of the continuous measure of H
(i.e., H3and H4), which fit the data better than the simple
linear and quadratic functions of H(i.e., Hand H2), or the
categorical measure of handedness. Third, handedness plays a
significant role in the scores in mathematics even when the effect
of MRA and age are controlled for. Moreover, even if MRA was a
predictor of mathematical ability in experiments 3, 4, and 5, only
a weak and often non-significant correlation was found between
MRA and handedness functions. These considerations suggest
that the relationship between handedness and mathematical
ability is only partially mediated by MRA. Possibly, in line with
Johnston et al. (2009) and Nicholls et al. (2010), the influence
of handedness on mathematical ability reflects the effects of
handedness on overall cognitive ability, rather than a specific
one. Finally, the participants’ gender and age, and the type
of mathematical task influenced the shape of the relationship
between handedness and mathematical ability. This result leads
us to think that the predictions of the four models described in
the Introduction are not necessarily mutually exclusive.
The Results in the Light of the Four Models
The overall results seem to suit best Annett’s (1985) conception of
the heterozygous advantage. In Experiments 1, 2, and 4, strongly
right- and left-handed children underperformed with respect to
the rest of the sample. Interestingly, our results uphold Annett
and Manning’s (1989, 1990) concept of the disadvantage of
dextrality. According to this hypothesis, strong right-handers—
but not strong left-handers—are more likely to suffer from a
deficit in spatial ability and, consequently, mathematical ability.
In fact, in all the five experiments, the strong right-handed
individuals showed a poorer performance compared to most (if
not all) their peers.
Nonetheless, it seems reasonable that mathematical ability in
children is based on their overall level of cognitive skill, and not
only on their spatial ability. For example, strongly left-handed
individuals may be more likely to suffer from some language-
related deficits (Annett, 1985) due to an increased development
of the right-hemisphere at the expense of the left-hemisphere
(Geschwind and Galaburda, 1985).9This possible language
impairment may, in turn, affect negatively mathematical
performance (e.g., difficulties in the comprehension of the
instructions and terms of the task). Moreover, this pattern—i.e.,
strong right- and left-handers underperforming in mathematical
ability—is also in line with Nicholls et al.’s (2010) concept of the
disadvantage of the extremes in overall cognitive ability.
Benbow’s (1986) hypothesis of the advantage of left-handers
finds some support in our results too. While Experiments 1,
2, and 4 did not show any clear advantage for left-handers
compared to right-handers, Experiments 3 and 5 did. Even
assuming that the results of Experiment 3 concerning left-
handers were not reliable because of the small number of left-
handed participants, Experiment 5 strongly supported Benbow’s
hypothesis. In fact, consistent with Benbow (1986, 1988), the
advantage of left-handers in mathematical ability concerned tasks
involving reasoning, and occurred in males only. However, it is
yet to be explained why the left-handers’ advantage occurred only
among high-school students, while the left-handed children’s
mathematical ability in tasks involving reasoning was not
superior to the right-handers’ one. Possibly, as proposed by
Noroozian et al. (2002), left-handers may be considered as a
heterogeneous group, consisting in part of gifted individuals,
in part of typically developing individuals, and in part of
underachievers. When individuals are tested in contexts of
relative excellence—such as colleges or, in our case, liceos—the
advantage of left-handers can occur, because those left-handers
who suffer from any cognitive deficit are not likely to be in
those contexts due to self-exclusion or academic selection. This
explanation relies on the belief that both gifted and people
with below-average cognitive ability are overrepresented among
left-handers, in line with Benbow (1986) and Johnston et al.
(2009, 2013), respectively. In other words, the alleged cause of
left-handedness—superior development of the right-hemisphere
(Geschwind and Galaburda, 1987) or pre- or peri-natal brain
damage (Satz et al., 1985)—predicts when left-handedness is a
correlate of giftedness or a disadvantage for cognitive ability.
However, the outcomes of the present study showed little
evidence of the disadvantage of left-handers. The overall results
seem to suggest a substantial equality between left- and right-
handers—at least among primary school children. Possibly, the
sample used in this study is too small to detect tiny differences
between left- and right-handers. In fact, in Johnston et al. (2013),
the difference in mathematical ability between left-handers
and right-handers—in favor of the latter—barely reached the
statistical significance in a sample of more than 5,000 children.
Thus, the disadvantage of left-handers in mathematical ability, if
any, may be extremely limited in size, and hence hard to detect.
Another possible explanation is that, since Johnston et al. (2009,
2013) assessed handedness by considering only the participants’
preferred writing hand, the disadvantage of left-handedness
9It is worth noting that more recent studies have suggested that the right
hemisphere also contributes to language comprehension and production (for
a review, see Poeppel et al., 2012). Nonetheless, the primary role of the left
hemisphere in such functions has been convincingly established (e.g., Turken and
Dronkers, 2011).
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Sala et al. Handedness and Mathematical Ability
occurs when writing hand preference is considered. Conversely,
when handedness is assessed as a continuous variable, the effect
disappears.
Finally, the results support, at least to some extent, the
hemispheric indecision hypothesis (Crow et al., 1998) as well.
While the first three experiments did not offer any evidence
of a disadvantage of mixed-handedness, in Experiment 4 and
5, mixed-handers showed a relatively poor performance in
mathematical ability. Probably, Experiment 1, 2, and 3 did
not have sufficient statistical power to identify a possible
disadvantage of the mixed-handers, whereas the two experiments
with the largest samples—i.e., Experiment 4 (N=798) and 5 (N
=641)—did.
In a broader perspective, these results are in line with
more recent research suggesting that the relationship between
handedness and cognition is far too complex to be accounted
for by simple models. For example, handedness appears to be
a polygenetic—rather than monogenetic (e.g., Annett, 2002)—
trait (Ocklenburg et al., 2013). It is thus reasonable to think
that lateralization patterns are more complex than the right-left
(or right-non-right) dichotomy may suggest (for a review, see
Badzakova et al., 2016).
Gender Effects
Gender was a significant moderator of the relationship between
handedness and mathematical problem-solving reasoning
(Experiments 1, 2, and 5), whereas no effect was observed with
arithmetical ability (Experiments 3 and 4). Interestingly, while
in Experiment 1 handedness affected the female participants, in
Experiment 2 and 5 only males’ mathematics scores were related
to handedness.
Providing an explanation of this pattern showing an
interaction between handedness, gender, and type of
mathematical ability is not simple. While the pattern occurred
in females in Experiment 1, in Experiments 2, and 5 it did in
males only. Regrettably, this is an outcome hardly accountable
for by any of the four models. A possible explanation is that,
unlike males, females tend to use verbal rather than spatial
strategies when solving mathematical problems (Pezaris and
Casey, 1991). Thus, the effects of handedness on performance
in mathematical reasoning tasks—which usually involve spatial
reasoning—may be less evident in females. Nonetheless, the fact
that, in Experiment 1, only females’ scores in mathematics were
influenced by handedness does not fit the above hypothesis.
Possibly, this empirical anomaly was due to the particular
features of the design (e.g., a test for 15-year-olds administered
to primary school children).
Conclusions and Recommendation for
Future Research
The present study had two main aims: (a) evaluating the
relationship between handedness and mathematical ability by
using quartic functions of H-values; and (b) exploring the
role of the moderating effects of age, gender, and type of
mathematical task on this relationship. The results showed
several significant interactions between the above variables—
along with a nearly generalized tendency toward the disadvantage
of the extremes. Moreover, the amount of variance (R2) in
mathematics performance accounted for by handedness was
approximately between 3 and 10%, and remained significant
even when the effects of participants’ mental rotation ability
(MRA) were partialled out. Such high percentages were probably
the consequence of using cubic and quartic functions, which
fit the pattern of data better than linear and quadratic
functions.
These outcomes have two important consequences. First, the
different predictions of the four models on the role of handedness
on cognitive and mathematical abilities are not necessarily
irreconcilable. The present study, however, represents only a first
step toward the development of a more comprehensive model.
Second, the size of the effects of handedness on mathematical
ability seems to be more relevant (up to 10% of the variance)
than it has been proposed so far (1%). Thus, handedness
cannot be considered a negligible predictor of mathematical
ability.
Further research is needed to draw a more precise causal
model of the effect of handedness on cognition and mathematical
ability. We thus propose some recommendations for extending
the design of the present study. First, we found that mental
rotation ability was weakly correlated with the polynomial
functions of handedness predicting the scores in mathematics.
Examining the relationship between handedness and a broader
range of measures of cognitive ability (e.g., fluid intelligence,
working memory, and phonological processing) is thus necessary
to find a “cognitive link” between handedness and mathematical
ability. For example, the use of path analysis and latent-
factor analysis may enable us to find more complex systems
of relationships between handedness, cognitive abilities, and
academic skills such as mathematics. Second, future studies
should include participants of different ages (e.g., younger than
six, older than 17), to have a more comprehensive view of the
effects of handedness on cognitive and mathematical skills during
development. Third, gender seems to affect the relationship
between handedness and mathematical problem-solving ability
significantly. For this reason, future investigations should control
for gender differences in the strategies adopted when solving
mathematical tasks involving reasoning. Fourth, the type of
mathematical task appears to be another moderating variable.
Therefore, testing the same participants on both arithmetical
and problem-solving skills would help to evaluate better the role
played by this variable on the relationship between handedness
and mathematical ability. Moreover, the research on the topic
should go beyond academic measures of mathematical ability—
like the ones used in the current investigation—and be extended
to numerical cognition (Feigenson et al., 2004; Reyna et al., 2009;
Peters, 2012) and its components (e.g., Peters and Bjalkebring,
2015). For example, it has been found that the approximate
number sense correlates with measures of mathematical literacy
(Libertus et al., 2011). It is thus important to investigate whether
the relationship between handedness and numerical cognition
presents the same features reported in the current study (e.g.,
non-linearity and influence of the type of task, age, and gender).
In a broader perspective, including measures of cognitive ability
(e.g., fluid intelligence and working memory capacity) to draw
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Sala et al. Handedness and Mathematical Ability
more complex systems of relationships between handedness,
cognition, and mathematical ability should be a priority in the
field. Finally, using measures of hand skill (e.g., square checking
task)—along with questionnaires assessing hand preference in
everyday life activities (e.g., Annett, 1970; Oldfield, 1971)—
would help test whether the shape of the relationship between
handedness and mathematical ability varies according to how
handedness is assessed.
ETHICS STATEMENT
The principals of the schools involved provided written
permission for the administration of the tests. Parental consent
was asked and obtained for all the participants. Individuals with
any diagnosed learning disability were excluded.
AUTHOR CONTRIBUTIONS
GS and FG developed the study concept. MS, GB, and MB
collected the data. GS performed the analyses of the data. All the
authors contributed to the drafting of the paper.
ACKNOWLEDGMENTS
The authors gratefully thank all the teachers, participants, and
parents involved in this study.
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