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Abstract

It has been proposed that playing chess enables children to improve their ability in mathematics. These claims have been recently evaluated in a meta-analysis (Sala & Gobet, 2016, Educational Research Review, 18, 46–57), which indicated a significant effect in favor of the groups playing chess. However, the meta-analysis also showed that most of the reviewed studies used a poor experimental design (in particular, they lacked an active control group). We ran two experiments that used a three-group design including both an active and a passive control group, with a focus on mathematical ability. In the first experiment (N = 233), a group of third and fourth graders was taught chess for 25 hours and tested on mathematical problem-solving tasks. Participants also filled in a questionnaire assessing their meta-cognitive ability for mathematics problems. The group playing chess was compared to an active control group (playing checkers) and a passive control group. The three groups showed no statistically significant difference in mathematical problem-solving or metacognitive abilities in the posttest. The second experiment (N = 52) broadly used the same design, but the Oriental game of Go replaced checkers in the active control group. While the chess-treated group and the passive control group slightly outperformed the active control group with mathematical problem solving, the differences were not statistically significant. No differences were found with respect to metacognitive ability. These results suggest that the effects (if any) of chess instruction, when rigorously tested, are modest and that such interventions should not replace the traditional curriculum in mathematics.
Does chess instruction improve mathematical problem-solving
ability? Two experimental studies with an active control group
Giovanni Sala
1
&Fernand Gobet
1
#The Author(s) 2017. This article is an open access publication
Abstract It has been proposed that playing chess enables
children to improve their ability in mathematics. These claims
have been recently evaluated in a meta-analysis (Sala &
Gobet, 2016,Educational Research Review, 18, 4657),
which indicated a significant effect in favor of the groups
playing chess. However, the meta-analysis also showed that
most of the reviewed studies used a poor experimental design
(in particular, they lacked an active control group). We ran two
experiments that used a three-group design including both an
active and a passive control group, with a focus on mathemat-
ical ability. In the first experiment (N= 233), a group of third
and fourth graders was taught chess for 25 hours and tested on
mathematical problem-solving tasks. Participants also filled in
a questionnaire assessing their meta-cognitive ability for
mathematics problems. The group playing chess was com-
pared to an active control group (playing checkers) and a
passive control group. The three groups showed no statistical-
ly significant difference in mathematical problem-solving or
metacognitive abilities in the posttest. The second experiment
(N= 52) broadly used the same design, but the Oriental game
of Go replaced checkers in the active control group. While the
chess-treated group and the passive control group slightly
outperformed the active control group with mathematical
problem solving, the differences were not statistically signifi-
cant. No differences were found with respect to metacognitive
ability. These results suggest that the effects (if any) of chess
instruction, when rigorously tested, are modest and that such
interventions should not replace the traditional curriculum in
mathematics.
Keywords Chess .Expertise .Instruction .Learning .
Meta-analysis .Transfer
Studentspoor achievement in mathematics has been the sub-
ject of debate both in the United States (Hanushek, Peterson,
& Woessmann, 2012; Richland, Stigler, & Holyoak, 2012)
and in Europe (Grek, 2009). Researchers and policy makers
have investigated alternative methods and activities with the
purpose of improving the effectiveness of mathematics teach-
ing. One such activity is play. The rationale is that, because
children are highly motivated to play, they could learn impor-
tant concepts in mathematics (and other curricular domains)
without realizing it, through implicit learning (Brousseau,
1997;Pelay,2011); they could also acquire general cognitive
skills such concentration and intelligence, which would posi-
tively affect their school results generally.
Several authors have argued that chess is an ideal game for
educational purposes (Bart, 2014; Jerrim, Macmillan,
Micklewright, Sawtell, & Wiggins, 2016;Kazemi,Yektayar,
& Abad, 2012). Chess offers an optimal trade-off between
complexity and simplicity, and the balance between tactics
and strategy is ideal. It combines numerical, spatial, temporal,
and combinatorial aspects. In addition, unlike games such as
Awalé and Go, the diversity of pieces helps maintain atten-
tionan important consideration with younger children.
Altogether, these characteristics of chess may foster attention,
problem solving, and self-monitoring of thinking (i.e., meta-
cognition). Finally, there is some overlap between chess and
mathematics (e.g., basic arithmetic with the value of the
pieces, geometry of the board, piece movements), which is
*Giovanni Sala
giovanni.sala@liv.ac.uk
1
Department of Psychological Sciences, University of Liverpool,
Bedford Street South, Liverpool L69 7ZA, UK
Learn Behav
DOI 10.3758/s13420-017-0280-3
an obvious advantage when using chess to foster mathemati-
cal skills.
In recent years, considerable efforts have been made to
validate these ideas empirically. Not only has chess instruction
been included in the school curriculum in several countries,
but several educational projects and studies involving chess
are currently ongoing or have recently ended in Germany,
Italy, Spain, Turkey, the United Kingdom, and the United
States. Even the European Parliament has expressed its inter-
est and positive opinion on teaching chess in schools as an
educational tool (Binev, Attard-Montalto, Deva, Mauro, &
Takkula, 2011). If successful, using chess in school for foster-
ing academic achievement would shed considerable light on
the question of skill acquisition and transfer (Mestre, 2005).
One psychological mechanism has been regularly pro-
posed for explaining the putative effects of chess instruction:
Being a cognitively demanding activity, chess improves pu-
pilsdomain-general cognitive abilities (e.g., intelligence, at-
tention, and reasoning), abilities that then transfer to other
domains, and therefore benefits a wide set of non-chess-
related skills (e.g., Bart, 2014). The idea is intuitive and attrac-
tive. This view of chess as a cognitive enhancer has been
mentioned in popular newspapers in the United Kingdom
(e.g., Garner, 2012) and was the key theoretical assumption
of a recent large experimental study that took place in the
United Kingdom (Jerrim et al., 2016).
Chess skill and cognitive ability
The literature on the link between chess skill and cognitive
ability is certainly consistent with this mechanism. People
engaged in intellectual activities often show superior cognitive
ability compared to the general population (e.g., professional
musicians; Ruthsatz, Detterman, Griscom, & Cirullo, 2008),
and chess is no exception. A recent meta-analysis (Sala et al.
2017) reported that chess players outperformed nonchess
players in several cognitive skills (e.g., planning, numerical
ability, and reasoning).The difference between the two groups
was approximatively half a standard deviation. Another meta-
analysis (Burgoyne et al., 2016) found positive correlations
between chess skill and cognitive abilities such as fluid intel-
ligence, processing speed, short-term and working memory
(WM), and comprehension knowledge.
However, the positive relationship between chess skill and
cognitive ability does not necessarily imply thatchess instruc-
tion enhances cognitive ability. An alternative explanation is
that individuals with better cognitive ability are more likely to
excel and engage in the game of chess. To establish causality,
one needs to turn attention to studies where instruction is
under experimental control. This is the province of education-
al psychology and in particular the study of transfer of skills.
This literature is rather skeptical about the possibility that an
activity such as chess improves cognition generally and leads
to educational benefits in topics such as mathematics. This
skepticism is reinforced by the literature on expertise, which
has found that expertsknowledge is highly specialized and
thus unlikely to transfer to other domains. The following sec-
tion briefly summarizes these two fields of research.
Skepticism: The question of far transfer
and research into expertise
Transfer of learning occurs when a set of skills learned in one
domain generalizes to one (or more) domains. It is customary
to distinguish between near transfer, where transfer of learning
occurs between tightly related domains (e.g., from geometry
to calculus) and far transfer, where the source and target do-
mains are only loosely related. The presumed enhancement of
mathematical ability from chess instruction is a clear example
of far transfer.
It has been proposed that transfer is a function of the degree
to which two (or more) domains share common features
(Thorndike & Woodworth, 1901). Thorndike and
Woodworths(1901) common element theory thus predicts
that while near transfer is often observed, far transfer occurs
rarely. This theory has received strong support from different
areas of research, where interventions thatfailed to obtain far-
transfer effects have been documented. For example, several
meta-analyses have shown that neither music instruction nor
WM training enhances pupilscognitive ability or academic
achievement (Melby-Lervåg, Redick, & Hulme, 2016;Sala&
Gobet, 2017b,2017c,in press). Interestingly, all these meta-
analyses reported near-zero overall effect sizes when the treat-
ment groups were compared to active control groups. When
transfer occurs, it is almost always near transfer only. For
example, Oei and Patterson (2015) have suggested that action
video-game training enhances only those cognitive abilities
directly involved in the particular video game used during
training.
Beyond research into far transfer, research into the psychol-
ogy of expertise lends support to Thorndike and Woodworths
(1901) theory. For example, transfer is only partial between
subspecialties such as cardiology and neurology (Rikers,
Schmidt, & Boshuizen, 2002) and types of specialization in
chess, as operationalized by the openings (first moves of a
game) played (Bilalić, McLeod, & Gobet, 2009). A likely
explanation is that expert performance relies substantially on
perceptual information (Gobet, 2016;Gobet&Simon,1996;
Sala & Gobet, 2017a), and such information is hard to transfer
to other domains. Consistent with this explanation, individuals
acquire increasingly specific information as skill levels in-
crease and, as a consequence, the probability that transfer will
take place decreases considerably (Ericsson & Charness,
1994).
Learn Behav
Is chess special? Empirical results and the lack of an
active control group
Thus, the hypothesis according to which one can improve
ones achievement in a wide set of fields by engaging in cog-
nitively demanding activities is not supported in most areas. In
fact, the abovementioned examples ofmusic training and WM
training suggest that those activities (e.g., n-back tasks,
playing a musical instrument) do not provide any general cog-
nitive benefit or improvement in academic achievement.
Reviewing the experiments where the effects of chess instruc-
tion have been experimentally studied suggests that chess is
no exception.
A recent meta-analytic review (Sala & Gobet, 2016) has eval-
uated the available empirical evidence regarding the effects of
chess instruction on pupilscognitive ability and academic
achievement.In that meta-analysis, the overall effect size of chess
instruction was modest, with g= 0.34. It was also found that the
effect sizes about measures of mathematical ability and literacy
were g=0.38andg= 0.25, respectively. Most importantly, that
review pointed out that the poor experimental design used in
almost all the reviewed studies does not allow one to draw any
certain conclusion about the benefits of chess instruction. In par-
ticular, most interventions did not include ana ctive control group
to control for placebo effects. Potential elements able to trigger
placebo effects include the state of attention and excitement in-
duced by a novel activity, instructorsmotivation, and teachers
expectations. Only one study (Fried & Ginsburg, n.d.), which
focused on visuospatial and perceptual abilities, included an ac-
tive control group. This study showed no significant difference
between the chess-treated, active, and passive control groups.
Regrettably, Fried and Ginsburgs (n.d.) experiment did not ex-
amine the effects of chess practice on pupilsmathematical abil-
ity. Thus, that study cannot corroborate or refute any hypothesis
about the effectiveness of chess instruction in enhancing mathe-
matical ability.
Consistent with Sala and Gobets(2016) conclusion about
the difficulty of far transfer, no effect of chess instruction was
found in a recent large-scale study carried out by the Institute
of Education, London, in the United Kingdom (Jerrim et al.,
2016). A large sample of Year 5 pupils (910 years; N=
1,965) engaging in one year of chess instruction (ranging from
25 to 30 hours) were compared to a passive control group of
peers (N= 1,900). The classes were randomly assigned to one
of the two conditions. Pretest measures consisted of Key Stage
1 public examinations covering mathematics, science, and lit-
eracy. Posttest measures, which were obtained 1 year after the
end of the treatment, consisted of Key Stage 2 public exami-
nations in the same fields. No difference was found between
the two groups in any of the measures. While some aspects of
the design could have been improved (e.g., absence of an
active control group, absence of measures immediately after
the end of the experiment, and possible ceiling effect; Sala,
Foley, & Gobet, 2017), the study certainly had strengths (e.g.,
large sample and allocation of classes to condition by random-
ization) and the absence of any positive effect of chess instruc-
tionnot even placebo effectssupports the hypothesis that
far transfer is difficult.
The present study
Given the importance of controlling for placebo effects report-
ed in music and WM training (Melby-Lervåg et al., 2016;Sala
&Gobet,2017b,2017c), the lack of an active control group is
undoubtedly the main flaw of the studies in the field of chess
instruction (Gobet & Campitelli, 2006; Gobet, de Voogt, &
Retschitzki, 2004;Sala et al., 2017). The two experiments
presented in this article aim to correct this unsatisfactory state
of affairs. In the first experiment, primary school children
receiving a 30-hour chess course were administered a test of
mathematical ability and compared to both an active control
group, receiving instruction about checkers, and a passive
control group. Along with the test of mathematical ability,
the participants were given a questionnaire assessing
metacognitive abilities. Metacognitive skills have been
established to be one of the most important cognitive corre-
lates of mathematical ability (Desoete & Roeyers, 2003;
Vee n ma n, Va n H ou t- Wo l te r s, & A ff ler bac h, 2006). Since the
self-monitoring of ones thinking processes is essential in a
game like chess (De Groot, 1965), playing chess may be as-
sociated with improvements in metacognitive ability.
In the second experiment, three fourth-grade classes were
randomly chosen to take part either in a chess course, a Go
(Baduk) course, or regular school activities. The pupils were
pre- and posttested on the same tests of mathematical ability
and metacognitive ability as in the first experiment.
Experiment 1
Method
Participants
A total of 233 third and fourth graders from eight Italian
schools took part in this experiment only. The mean age was
8.50 years (SD = 0.67 years). Parental consent was asked and
obtained for all the participants.
Material
A 6-item test was designed to test the pupilsmathematical
ability (range score 06). The items used were all from the
IEA-TIMSS international survey among fourth graders
(Mullis & Martin, 2013). These items were selected because
they engage mathematical problem-solving ability. In fact, all
Learn Behav
the items required solving a mathematical problem starting
from a given set of data. An example of the kind of mathe-
matical problems used in IEA-TIMSS is shown in Fig. 1.
To assess participantsmetacognitive skills, we used the
Italian version of Panaoura and Philippous(2007) question-
naire (15-item version; range score 15-75). Participants were
given 45 minutes for completing the battery of tests.
Design
A convenience assignment to the three conditions was used.
The group playing chess was compared to an active control
group (playing checkers) and a passive control group (doing
regular school activities). The experimental group consisted of
three classes (two third-grade classes and one fourth-grade
class; N= 53), which attended 25 hours of chess lessons dur-
ing school hours,
1
along with regular school activities. The
active control group (placebo group) comprised four third-
grade classes (N= 82), which attended 25 hours of checkers
lessons during school hours, along with regular school activ-
ities. Finally, the passive control group consisted of four clas-
ses (three third-grade classes and one fourth-grade class; N=
98), which attended regular school activities only.
The interventions were delivered by professional instruc-
tors from the Italian ChessFederation and the Italian Checkers
Federation. The chess and checkers lessons followed a
prearranged teaching protocol, which consisted of the basic
rules of the games, tactical exercises, and playing complete
games. Most of the activities focused on problem-solving sit-
uations, such as spotting the correct move, calculating the
correct variation, and evaluating the advantages/weaknesses
of a position. Also, it should be noted that the two courses
(chess and checkers) did not introduce any mathematics-
related topics, unless these were part of the games (e.g., in
chess, a Bishop is worth three Pawns).
Results
Mathematical ability
A univariate analysis of covariance (ANCOVA) was used to
evaluate the role of group (independent variable), mathemat-
ics pretest scores (covariate), and age (covariate), in affecting
mathematics postintervention scores (dependent variable).
The results showed a significant effect of pretest scores, F(1,
228) = 58.14, p< .001, and age, F(1, 228) = 4.22, p= .041, but
no significant effect of group, F(2, 228) = 0.39, p= .679. The
descriptive statistics are summarized in Table 1.
Metacognitive ability
The same analysis (ANCOVA) was used to analyze the results
in meta-cognitive ability. The results showed a significant ef-
fect of pretest scores, F(1, 228) = 82.50, p< .001, and age,
F(1, 228) = 3.97, p= .047, but no significant effect of group,
F(2, 228) = 0.62, p= .541. The descriptive statistics are sum-
marized in Table 2.
Discussion
The results showed no significant differences between the
three groups in mathematical ability or metacognitive ability.
Fig. 1 An example of the kind of problems used in the test of
mathematics
1
The chess and checkers courses were implemented during school hours
accordingly to the teachersavailability. No particular discipline (e.g., mathe-
matics) was systematically replaced by the courses.
Tabl e 1 Mathematical ability scores in the three groups (Experiment 1)
Group Pretest Posttest Adjusted mean
Chess 1.75 (1.34) 1.81 (1.69) 1.64
Checkers 1.28 (0.96) 1.60 (1.14) 1.75
Control 1.41 (1.20) 1.87 (1.36) 1.83
Note. Standard deviations are shown in brackets
Learn Behav
Experiment 2
The second experiment
2
broadly used the same design but
also differed in three ways. First, the classes were randomly
assigned to the experimental conditions. Second, the active
control group played the Oriental game of Go (Baduk) instead
of checkers. Finally, chess and Go replaced part of the hours (n
= 15) originally dedicated to mathematics and sciences to
directly compare the two games with the traditional methods
of teaching mathematics and mathematics-related disciplines.
Method
Participants
Fifty-two fourth graders in three classes of a primary school in
Italy took part in this experiment. The mean age of the partic-
ipants was 9.32 years (SD = 0.32 years). Parental consent was
asked and obtained for all the participants.
Material
The same tests as those used in Experiment 1were adminis-
tered to the participants.
Design
The three classes were randomly assigned to three groups. The
first class attended 15 hours of chess lessons during school
hours, along with regular school activities (experimental
group). The second class attended regular school activities
only (passive control group). Finally, the third class attended
15 hours of Go lessons during school hours, along with regu-
lar school activities (active control/placebo group).
Importantly, the two interventionsthat is, chess and Go
coursessubstituted part of the hours originally devoted to
mathematics and sciences. This way, we could compare the
effectiveness of chess (and Go) instruction with the traditional
didactics of teaching mathematics and mathematics-related
disciplines, such as sciences. Like in Experiment 1, the chess
and Go lessons followed a prearranged teaching protocol. To
rule out possible effects related to instructor behavior (e.g.,
Pygmalion effect), the chess and Go interventions were deliv-
ered by the same instructor, who was both a chess and Go
trainer. The participants were pre- and posttested on mathe-
matical ability and metacognition, once before the beginning
of the intervention and once after the end.
Results
Mathematical ability
No significant differences between the three groups were
found in the pre-test scores, F(2, 51) = 1.03, p= .365. A
univariate analysis of covariance (ANCOVA) was used to
evaluate the role of group (independent variable) and mathe-
matics pretest scores (covariate) in affecting mathematics
postintervention scores (dependent variable). The results
showed a significant effect of the covariate, F(1, 48) =
21.83, p< .001, and a significant effect of group, F(2, 48) =
3.37, p= .043. The pairwise comparisons showed that the
control group outperformed the Go group (p= .017), the chess
group marginally outperformed the Go group (p= .088),
whereas no significant difference was found between the con-
trol and the chess group (p= .487). A more conservative post
hoc analysis (Bonferroni correction) showed only a marginal
difference between the control group and the Go group (p=
.052). No other significant difference was found. The descrip-
tive statistics are summarized in Table 3.
Metacognitive skills
No significant differences between the three groups were
found in the pretest scores, F(2, 51) = 0.49, p=.617.Auni-
variate analysis of covariance (ANCOVA) was used to evalu-
ate the role of group (independent variable) and metacognition
pretest scores (covariate) in affecting metacognition postinter-
vention scores (dependent variable). The results showed a
significant effect of the covariate, F(1, 48) = 47.81, p<.001,
and no significant effect of group, F(2, 48) = 0.37, p=.694.
The pairwise comparisons showed no differences between the
three groups. The descriptive statistics are summarized in
Table 4.
Discussion
The effects of chess instruction on mathematical problem-
solving ability were minimal. Children seemed to benefit
more from the traditional didactics than from chess and Go
instruction. Regarding metacognitive skills, children did not
seem to benefit from any advantage from the 15-hour chess
course. In fact, the participants performed equally across the
three groups, suggesting that metacognition does not represent
2
The results of this experiment were published in Sala, Gobet, Trinchero, and
Vent u r a ( 2016).
Tabl e 2 Metacognitive ability scores in thethree groups (Experiment 1)
Group Pretest Posttest Adjusted mean
Chess 54.19 (9.76) 52.92 (8.86) 52.35
Checkers 54.51 (7.39) 55.07 (8.81) 53.86
Control 51.41 (9.09) 52.22 (9.71) 53.55
Note. Standard deviations are shown in brackets
Learn Behav
the cognitive link between chess instruction and mathematical
ability.
General discussion
The results of the two studies do not support the hypothesis
according to which chess instruction benefits pupilsmathe-
matical ability. The effects of chess, if any, appear to be min-
imal and certainly too limited to provide any educational ad-
vantage overthe traditional instructional methods. Thus, chess
instruction seems to align with the results obtained in the
fields of music instruction and WM training. In a broader
perspective, our findings are in line with Thorndike and
Wood wo r t h s(1901) common element theory and substantial
research on expertise (Gobet, 2016) and education (Donovan,
Bransford, & Pellegrino, 1999) in predicting no far-transfer
effects.
Recommendations for future research
Given the small number of studies controlling for placebo
effects, it is imperative to replicate and extend the experiments
reported in the present article. Compared to the design we
adopted, examples of possible ameliorations include full ran-
dom assignment to the groups, measures of other cognitive
constructs (e.g., intelligence and spatial cognition), and the
manipulation of the duration of the chess interventions.
In addition, an interesting way to make chess instruction
more effective could be to make links between mathematics
and chess explicit. Possible examples comprise introducing
the Cartesian graph to pupils with the chess board and illus-
trating the concept of block distanceas opposed to distance
in Euclidean spacewith the movement of the King (see
Fig. 2). The inclusion of domain-specific information (e.g.,
mathematical problems) into chess courses curricula may be
a simple way to get around the limits of far transfer to occur.
One variation of this approach is to use not only chess but also
other board games or even other types of games such as card
games to teach specific mathematical concepts. For example,
mancala games could be used for teaching the concept of
modular arithmetic, card games for teaching elements of prob-
ability, and Nim games to teach the binary system of Boolean
algebra (Rougetet, 2016).
Conclusion
Beyond chess, the results of the research on chess instruction
have profound implications for our understanding of learning
and transfer of skill. There is a stark contrast between the
enthusiasm displayed by the chess community and the sober-
ing results from research on transfer and expertise: While the
former heralds the positive benefits of chess instruction, the
latter consistently report data speaking against the occurrence
of far transfer. When critically evaluated, the literature on
chess instruction is consistent with other experimental studies
on transfer, indicating that far transfer is very unlikely. The
results of the two experiments presented in this paper are
consistent with these conclusions.
Extrapolating from the research on chess and activities
such as music and video-game playing, it is likely that the
same difficulties in far transfer will be found with other kinds
of games and play. To make the use of didactical games more
effective, and given the difficulty of far transfer to occur,
teachers and researchers should seriously consider the
Fig. 2 Using chess to illustrate block-city distance and Euclidean dis-
tance. White draws the game by moving the King along the blue line,
which allows him both to approach his Pawn (threatening promotion) and
to catch the black Pawn. In chess, block city and Euclidean distances are
equivalent (in this examples, six moves in both cases to reach the square
where the two arrows meet). This position was composed by Richard Réti
in 1921
Tabl e 3 Mathematical ability scores in the three groups (Experiment 2)
Group Pretest Posttest Adjusted mean
Chess 2.13 (1.26) 2.50 (1.41) 2.30
Go 1.81 (1.08) 1.62 (1.20) 1.63
Control 1.53 (1.13) 2.40 (1.55) 2.60
Note. Standard deviations are shown in brackets
Tabl e 4 Metacognitive skill scores in the three groups (Experiment 2)
Group Pretest Posttest Adjusted mean
Chess 55.2 (11.0) 57.0 (10.5) 56.3
Go 52.7 (9.2) 54.8 (8.6) 55.8
Control 55.3 (6.5) 58.3 (6.0) 57.6
Note. Standard deviations are shown in brackets
Learn Behav
possibility of making explicit the link between playing games
and the mathematical abilities the game is supposed to foster.
Even so, it is worth reminding ourselves of French sociologist
Roger Cailloiss(1957) discussion of the role of play in his
article on the unity of play and diversity of games: BFaculties
thus developed certainly profit by this supplementary training
which is free, intense, pleasurable, inventive, and secure. But
it is never the function of play itself to develop these faculties.
The purpose of play is play^(p. 105).
Acknowledgments The authors gratefully thank all the principals and
teachers involved in the studies. The authors also thank Daniele Berté,
Alessandro Dominici, Sebastiano Paulesu, and Gionata Soletti for the
valuable assistance in all the organizational aspects of the interventions.
Open Access This article is distributed under the terms of the Creative
Commons Attribution 4.0 International License (http://
creativecommons.org/licenses/by/4.0/), which permits unrestricted use,
distribution, and reproduction in any medium, provided you give appro-
priate credit to the original author(s) and the source, provide a link to the
Creative Commons license, and indicate if changes were made.
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... 45 Examining the effects of chess training on mathematical problem-solving and metacognitive abilities in school children, no significant effects were observed compared with an active control group playing checkers and a passive control group. 46 Besides the known effects of CRT on metacognition, the beneficial effect of chess-based CRT (CB-CRT) still remains unclear. However, present findings suggest that CB-CRT might be able to improve cognitive functioning in domains which can be improved by classical CRT, while simultaneously potentially improving specific domains modulated by chess-based interventions. ...
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Background Alcohol and tobacco use disorders (AUD, TUD) are frequent, both worldwide and in the German population, and cognitive impairments are known to facilitate instances of relapse. Cognitive training has been proposed for enhancing cognitive functioning and possibly improving treatment outcome in mental disorders. However, these effects and underlying neurobiological mechanisms are not yet fully understood regarding AUD and TUD. Examining the effect of chess-based cognitive remediation training (CB-CRT) on neurobiological, neuropsychological and psychosocial aspects as well as treatment outcomes will provide insights into mechanisms underlying relapse and abstinence and might help to improve health behaviour in affected individuals if used as therapy add-on. Methods and analysis N=96 individuals with either AUD (N=48) or TUD (N=48) between 18 and 65 years of age will participate in a randomised, controlled clinical functional MRI (fMRI) trial. Two control groups will receive treatment as usual, that is, AUD treatment in a clinic, TUD outpatient treatment. Two therapy add-on groups will receive a 6-week CB-CRT as a therapy add-on. FMRI tasks, neurocognitive tests will be administered before and afterwards. All individuals will be followed up on monthly for 3 months. Endpoints include alterations in neural activation and neuropsychological task performance, psychosocial functioning, and relapse or substance intake. Regarding fMRI analyses, a general linear model will be applied, and t-tests, full factorial models and regression analyses will be conducted on the second level. Behavioural and psychometric data will be analysed using t-tests, regression analyses, repeated measures and one-way analyses of variance. Ethics and dissemination This study has been approved by the ethics committee of the medical faculty Mannheim of the University of Heidelberg (2017-647N-MA). The findings of this study will be presented at conferences and published in peer-reviewed journals. Trial registration The study was registered in the Clinical Trials Register (trial identifier: NCT04057534 at clinicaltrials.gov).
... But findings to date suggest methods with more in-depth analyses of strategies and reasoning may be required to understand how board games can foster these skills. For example, when an intervention with elementary school-aged children has simply consisted of learning to play a game such as chess, findings are mixed: one study found a subsequent effect on mathematical problem-solving scores (Sala, Gorini, and Prevettoni 2015), and another suggested no such effect (Sala and Gobet 2017), both with few further conclusions possible. Other sources describe how board games can be used by teachers in a math class. ...
... Thus, the data seem very promising, given how difficult it has been historically to raise intelligence, IQ, or cognitive ability scores with generally null to minimal effects in many heavily promoted intervention methods such as chess (Sala & Gobet, 2016;2017a), music (Sala & Gobet, 2017b), video games (Sala et al., 2018), and working memory training (Melby-Lervag & Hulme, 2013Sala & Gobet, 2017c). ...
... This outcome has been found for working memory training , video-game playing (Sala et al., 2018), exergames (Sala, Tatlidil, et al., 2021), and music training (Sala & Gobet, 2017c;. The exception is chess (Sala & Gobet, 2016), where too few studies with an active control group have been carried out; however, the few available studies with an active control group suggest a lack of far transfer (e.g., Sala & Gobet, 2017a). These meta-analyses were carried out with different methods. ...
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... This integrative basis promotes the interaction, mutual influence, mutual enrichment of areas knowledge and will need to contribute to school student's functional (mathematical) literacy formation [17]. The mathematical education synergy in the context of cultures dialogue and modern achievements in science adaptation (chess instruction improve mathematical problem-solving ability is presented in [21]), whether it is inclusive (inclusive) education, distance learning or integrated courses, allows the creating conditions for improving the mathematical education quality, school student's educational and professional motivation with their individual characteristics disclosure. ...
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Chess instruction has been claimed to enhance primary and middle school students’ mathematical abilities. The “Chess Effect” hypothesis has received some scientific support but it is yet to be convincingly demonstrated. This note briefly reviews the prevailing research, identifies some common pitfalls, and recommends directions for future research. Mathematics proficiency is seen as a necessary prerequisite for gaining jobs in the Science, Technology, Engineering and Mathematics (STEM) disciplines, which underpin our technological future. While the level of the required mathematical skills is increasing, the global educational surveys PISA and TIMSS have documented striking differences in proficiency levels between countries, which have created concern in several countries on their relative performance in mathematics. For example, from the USA perspective, researchers have conducted comparative analyses of performance trends (Hanushek et al., 2012) and also of mathematics pedagogy (Richland et al., 2012). There is a general feeling that novel methods of teaching have to be developed to make mathematics instruction more effective. Chess instruction in school has been proposed as an intervention to address this objective. The conventional wisdom that chess instruction may enhance pupils’ academic performance has stimulated numerous research projects worldwide over the last two decades. Most of the studies have focused on the putative benefits of chess instruction on achievement in mathematics.
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Music training has been recently claimed to enhance children and young adolescents' cognitive and academic skills. However, substantive research on transfer of skills suggests that far-transfer - i.e., the transfer of skills between two areas only loosely related to each other - occurs rarely. In this meta-analysis, we examined the available experimental evidence regarding the impact of music training on children and young adolescents' cognitive and academic skills. The results of the random-effects models showed (a) a small overall effect size ; (b) slightly greater effect sizes with regard to intelligence and memory-related outcomes ; and (c) an inverse relation between the size of the effects and the methodological quality of the study design. These results suggest that music training does not reliably enhance children and young adolescents' cognitive or academic skills, and that previous positive findings were probably due to confounding variables.
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Experts’ remarkable ability to recall meaningful domain-specific material is a classic result in cognitive psychology. Influential explanations for this ability have focused on the acquisition of high-level structures (e.g., schemata) or experts’ capability to process information holistically. However, research on chess players suggests that experts maintain some reliable memory advantage over novices when random stimuli (e.g., shuffled chess positions) are presented. This skill effect cannot be explained by theories emphasizing high-level memory structures or holistic processing of stimuli, because random material does not contain large structures nor wholes. By contrast, theories hypothesizing the presence of small memory structures—such as chunks—predict this outcome, because some chunks still occur by chance in the stimuli, even after randomization. The current meta-analysis assessed the correlation between level of expertise and recall of random material in diverse domains. The overall correlation was moderate but statistically significant (r = .41; p < .001 ), and the effect was observed in nearly every study. This outcome suggests that experts partly base their superiority on a vaster amount of small memory structures, in addition to high-level structures or holistic processing.
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It has been claimed that working memory training programs produce diverse beneficial effects. This article presents a meta-analysis of working memory training studies (with a pretest-posttest design and a control group) that have examined transfer to other measures (nonverbal ability, verbal ability, word decoding, reading comprehension, or arithmetic; 87 publications with 145 experimental comparisons). Immediately following training there were reliable improvements on measures of intermediate transfer (verbal and visuospatial working memory). For measures of far transfer (nonverbal ability, verbal ability, word decoding, reading comprehension, arithmetic) there was no convincing evidence of any reliable improvements when working memory training was compared with a treated control condition. Furthermore, mediation analyses indicated that across studies, the degree of improvement on working memory measures was not related to the magnitude of far-transfer effects found. Finally, analysis of publication bias shows that there is no evidential value from the studies of working memory training using treated controls. The authors conclude that working memory training programs appear to produce short-term, specific training effects that do not generalize to measures of “real-world” cognitive skills. These results seriously question the practical and theoretical importance of current computerized working memory programs as methods of training working memory skills.
Book
What does a chess master think when he prepares his next move? How are his thoughts organized? Which methods and strategies does he use by solving his problem of choice? To answer these questions, the author did a study, to which famous chess masters participated (Alekhine, Max Euwe, Reuben Fine, Tartakower and Flohr). This book is still useful for everybody who studies cognition and artificial intelligence. The studies involve participants of all chess backgrounds, from amateurs to masters. They investigate the cognitive requirements and the thought processes involved in moving a chess piece. The participants were usually required to solve a given chess problem correctly under the supervision of an experimenter and represent their thought-processes vocally so that they could be recorded. De Groot found that much of what is important in choosing a move occurs during the first few seconds of exposure to a new position. Four stages in the task of choosing the next move were noted. The first stage was the 'orientation phase', in which the subject assessed the situation and determined a general idea of what to do next. The second stage, the 'exploration phase' was manifested by looking at some branches of the game tree. The third stage, or 'investigation phase' resulted in the subject choosing a probable best move. Finally, in the fourth stage, the 'proof phase', saw the subject confirming with him/herself that the results of the investigation were valid. De Groot concurred with Alfred Binet that visual memory and visual perception are important and that problem-solving ability is of paramount importance. Memory is particularly important, according to de Groot (1965), in that there are no 'new' moves in chess and so those from personal experience or from the experience of others can be committed to memory. © 1965, Mouton Publishers, The Hague, The Netherlands. All right reserved.