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Early Education and Development
ISSN: 1040-9289 (Print) 1556-6935 (Online) Journal homepage: http://www.tandfonline.com/loi/heed20
Motor Skills and Executive Function Contribute to
Early Achievement in East Asia and the Pacific
Li Zhang, Jin Sun, Ben Richards, Kevin Davidson & Nirmala Rao
To cite this article: Li Zhang, Jin Sun, Ben Richards, Kevin Davidson & Nirmala Rao (2018) Motor
Skills and Executive Function Contribute to Early Achievement in East Asia and the Pacific, Early
Education and Development, 29:8, 1061-1080, DOI: 10.1080/10409289.2018.1510204
To link to this article: https://doi.org/10.1080/10409289.2018.1510204
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Published online: 06 Sep 2018.
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Motor Skills and Executive Function Contribute to Early
Achievement in East Asia and the Pacific
, Jin Sun
, Ben Richards
, Kevin Davidson
, and Nirmala Rao
Department of Preschool Education, Faculty of Education, East China Normal University;
Department of Early
Childhood Education, Faculty of Education and Human Development, The Education University of Hong Kong;
Department of Division of Learning, Development and Diversity, Faculty of Education, The University of Hong Kong;
Research Findings: This study examined the contributions of motor skills and
executive function (EF) to early achievement. Participants were 7,797 children
(3,889 girls) between 36 and 72 months of age from 6 countries in East Asia and
the Pacific. Fine and gross motor skills, EF, language and literacy achievement,
and mathematics achievement were evaluated using the East Asia-Pacific Early
Child Development Scales, a tool that assesses child development in 7
domains. Children’s caregivers provided demographic information. There
were 3 salient findings. First, gross and fine motor skills predicted both
language and literacy and mathematics achievement. Second, in general,
fine motor skills contributed more to the prediction of early achievement
than gross motor skills. However, there were no differences between the
contributions of fine and gross motor skills to the prediction of early language
and literacy in Papua New Guinea or early mathematics in Timor-Leste. Third,
EF partially mediated the relation between both early achievement and gross
and fine motor skills in the overall sample, Cambodia, and Timor-Leste and
fully mediated the association of gross motor skills and early achievement in
China, Mongolia, Papua New Guinea, and Vanuatu. Practice or Policy:
Implications of the findings for early childhood education are discussed.
Children’s early achievement depends on a combination of multifaceted competencies (Abenavoli,
Greenberg, & Bierman, 2017; G. J. Duncan et al., 2007). Recently, increased attention has been
accorded to understanding the role of motor skills and executive function (EF) in academic
achievement (Cameron, Cottone, Murrah, & Grissmer, 2016; Davies, Janus, Duku, & Gaskin,
2016). Motor skills are closely associated with both language and mathematics achievement
(Cameron et al., 2016; Carlson, Rowe, & Curby, 2013; Luo, Jose, Huntsinger, & Pigott, 2007). The
core components of EF skills, including attention, working memory, and inhibitory control, have
also been found to predict children’s learning outcomes (Duncan et al., 2007; Duncan, McClelland,
& Acock, 2017). Against the background of these findings, more recent research has examined the
role of EF as a potential mediator in the relation between motor development and academic
achievement and found that EF is a mediator in this relation (Chang & Gu, 2018; Oberer, Gashaj,
& Roebers, 2018; Schmidt et al., 2017). However, these studies have mainly focused on young
children in Europe or in the United States.
CONTACT Nirmala Rao firstname.lastname@example.org Department of Division of Learning, Development and Diversity, Faculty of
Education, Room 510, Meng Wah Complex, Pokfulam, Hong Kong.
Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/heed.
Supplemental data for this article can be accessed here.
© 2018 Taylor & Francis
EARLY EDUCATION AND DEVELOPMENT
2018, VOL. 29, NO. 8, 1061–1080
Stunting and early achievement
Stunting (a low height-for-age zscore) is an indicator of chronic malnutrition. It has a negative
impact on neuronal growth, pruning, and connectivity in regions of the brain that are involved in
motor and cognitive functioning (Sudfeld et al., 2015). Malnourished children are also likely to
experience other disadvantages associated with poverty, including low levels of stimulation at home
and limited access to early childhood programs, two factors that are also associated with poor
developmental outcomes (Prado & Dewey, 2014). Data from UNICEF’s Multiple Indicator Cluster
Survey showed that stunting was negatively related to children’s physical development and early
achievement in literacy and numeracy in 15 low- and middle-income countries (LMICs; Miller,
Murray, Thomson, & Arbour, 2016). Furthermore, stunted children have shown delays in cognitive
abilities and motor scores both concurrently and longitudinally in 29 LMICs (Sudfeld et al., 2015).
East Asia and the Pacific includes about 25% of the world’s children younger than 5 years. In
2010, it was estimated that 20% of children younger than 5 years in East Asia and the Pacific were
stunted and 29% (nearly 42 million) were at risk for not reaching their full developmental potential
(Black et al., 2017). Many children are not ready to learn when they enter school and have low levels
of reading, comprehension, and mathematics skills during the early primary school years (World
Bank, 2018). Despite great efforts in the past decades, the stunting rate in one third of the region’s
countries remains high, which will impede children’s early learning and achievement (World Bank,
2018). Although China is regarded as one of the top performers in early achievement in this region,
more than 30% of children from Cambodia, Timor-Leste, and Vanuatu were not able to read a single
word in Grade 2 (World Bank, 2018). Low levels of early achievement, if unaddressed, will linger and
affect later school achievement and future life success (Duncan et al., 2007).
Findings from high-income countries suggest that EF mediates the relation between motor skills and
early achievement (e.g., Chang & Gu, 2018). However, it is not clear whether EF also mediates the
relation between motor skills and early achievement in LMICs where a large number of children are
stunted. Against this background, the present study considered the contributions of motor skills and EF
to early achievement in Cambodia, China, Mongolia, Papua New Guinea, Timor-Leste, and Vanuatu.
Motor skills and academic achievement
The term motor skills describes a broad range of physical competencies, including balance and stability,
coordinated movement, and the manipulation of objects (Griggs, 2012;Lawrence,2012). A distinction is
made between gross and fine motor skills. Gross motor skills require coordination of the body’slarger
muscles in balance,posture, orientation, andmovement of the trunk and limbs, whereas fine motor skills
integrate the smaller muscles for activities such as drawing, writing, reading, and speaking and usually
include manual dexterity and visuomotor integration (Cameron et al., 2016).
Studies have uncovered relations between motor skills and academic achievement. Children with
higher levels of motor skills at the beginning of school tend to achieve higher academic performance
than those with lower levels (Cameron et al., 2016). Motor control, balancing abilities, and the
capability to explore the surrounding environment in 5-month-olds indirectly predicted their
academic achievement at 10 and 14 years via cognitive abilities at 4 and 10 years (Bornstein,
Hahn, & Suwalsky, 2013). However, when different components of motor skills are examined
separately, different patterns of correlations between motor skills and academic achievement emerge.
The extant research yields inconsistent findings regarding the associations between gross motor skills
and both reading and mathematics achievement. When gross motor skills have been considered
along with fine motor skills, they have not typically contributed to predicting academic achievement
(Grissmer, Grimm, Aiyer, Murrah, & Steele, 2010; Kim et al., 2015; Pagani & Messier, 2012),
although there have been exceptions (Son & Meisels, 2006). However, studies have consistently
found that fine motor skills are strong predictors of academic achievement, even after gross motor
skills are controlled for (Cameron et al., 2012; Grissmer et al., 2010; Kim et al., 2015; Pagani &
1062 L. ZHANG ET AL.
Messier, 2012). Researchers have further pointed out that fine motor skills underpin the relation
between motor development and cognitive abilities, including academic performance, across a wide
age span (Davis, Pitchford, & Limback, 2011; van der Fels et al., 2015). In addition, fine motor skills
have been found to be more closely linked with mathematics achievement than with literacy
achievement (Murrah, Chen, & Cameron, 2013; Pitchford, Papini, Outhwaite, & Gulliford, 2016).
Researchers have articulated the potential mechanism linking motor skills with academic achieve-
ment. First, early mastery of numeracy and mathematics largely depends on the manipulation of
objects that require fine motor skills (Pagani & Messier, 2012) and therefore may be more closely
linked with fine motor skills than early literacy skills. Second, when children have a good mastery of
fine motor skills, they are able to allocate attention to more complex academic skills that in turn
contribute to higher levels of early achievement (Cameron et al., 2012,2016; Pitchford et al., 2016).
Third, higher levels of gross motor skills may reduce emotional distress and social difficulties in the
classroom, help children to concentrate more on learning, and thus promote early achievement
(Pagani & Messier, 2012; Pitchford et al., 2016). Despite the evidence, studies have not adequately
examined the relation between motor skills and academic achievement (Cadoret et al., 2018;
Cameron et al., 2016), especially in LMICs. Hence, it is not clear whether the same relation between
motor skills and achievement will be found among children in LMICs as those living in Western
Motor skills, EF, and academic achievement
An increasing number of studies are probing the nature of the relations among EF, motor skills, and
academic achievement (Sulik, Haft, & Obradović,2018). In general, these studies have explored the
simultaneous prediction of academic achievement from motor skills and EF or the mediating role of
EF in the motor–academic performance link. Findings show that both motor skills and EF are strong
predictors of reading and/or mathematics achievement and growth in academic performance
between kindergarten and the middle school years (Brock, Kim, & Grissmer, 2018; Cameron et al.,
2012; Carlson, 2014). The significant contributions of both early fine motor skills and EF to later
school achievement were also detected in a cross-cultural study conducted in the United States and
the United Kingdom (Grissmer et al., 2010). However, when analyzed together with fine motor skills
and EF, gross motor skills did not contribute to the development of school outcomes (Cameron
et al., 2012). Furthermore, visuomotor skills, an important component of fine motor skills, were
correlated with different aspects of academic achievement when considered together with behavioral
self-regulation and EF (Becker, Miao, Duncan, & McClelland, 2014). Although behavioral self-
regulation, visuomotor skills, and EF were significantly associated with emergent literacy, EF was
not related to mathematics achievement, and visuomotor skills were not related to vocabulary scores
(Becker et al., 2014).
Several other studies have reported that EF mediates the relation between academic achievement
and motor skills in terms of fine motor skills (Cadoret et al., 2018; Roebers et al., 2014), visuomotor
integration skills (Chang & Gu, 2018), and physical activity or active play (Becker, McClelland,
Loprinzi, & Trost, 2014; Cadoret et al., 2018; Chang & Gu, 2018; Oberer et al., 2018). Few have
examined whether EF mediates the relation between gross motor skills and academic achievement. A
large-scale longitudinal study of early primary school children in Norway demonstrated that physical
activity involving gross motor skills did not predict EF or academic performance in numeracy,
reading, and English, and EF was not a mediator in the relation between gross motor skills and
school achievement (Aadland et al., 2017).
Neuroimaging studies indicate that the rostral premotor cortex serves as a link between motor
and cognitive networks and that brain regions previously thought to be involved only in motor
activities (the cerebellum and basal ganglia) or cognitive activities (the prefrontal cortex) are
coactivated during certain motor or cognitive tasks (Diamond, 2000; Hanakawa, 2011). Findings
from longitudinal studies also show that early motor development predicts adult EF (Carlson,
EARLY EDUCATION AND DEVELOPMENT 1063
Zelazo, & Faja, 2013). This may explain the close relation between motor skills and EF, the higher
order cognitive skill (Ackerman & Friedman-Krauss, 2017; Blair & Razza, 2007; Diamond, 2000;
McClelland et al., 2007). At the same time, findings from studies with children and adolescents
suggest that EF is a domain-general skill that facilitates both reading/language and mathematics
achievement (Best, Miller, & Naglieri, 2012; Bull, Espy, & Wiebe, 2008). The findings have been
replicated in the United States, Europe, and Asia (G. J. Duncan et al., 2007; Lan, Legare, Cameron,
Li, & Morrison, 2011; Thorell, Veleiro, Siu, & Mohammadi, 2013). Therefore, it is likely that EF plays
a mediating role between motor skills and academic achievement.
The present study
Previous studies have shown that motor skills are closely related to academic achievement and
suggest that EF is a promising mediator in the relation between motor skills and academic achieve-
ment. However, to date, much of this research has been conducted in rich Western countries
(Nielsen, Haun, Kaertner, & Legare, 2017), and it is not clear whether the findings are equally
valid in LMICs. Using data from the validation sample of the East Asia-Pacific Early Child
Development Scales (EAP-ECDS), the current study explored whether EF mediates the relation
between motor skills and early achievement in Cambodia, China, Mongolia, Papua New Guinea,
Timor-Leste, and Vanuatu.
We considered the relations between early achievement and both gross motor skills and fine
motor skills and additionally examined the role of EF in these relations. Analyses were conducted
both for a sample of all countries together and also separately for each of the six countries. This
allowed further investigation of commonalities and differences in the relation among motor skills,
EF, and early achievement in countries that vary markedly in economic development as well as in
early childhood education (ECE).
The present study addressed two research questions: (a) Do fine motor skills and gross motor
skills predict early language and literacy and early mathematics achievement across the six countries?
(b) Does EF mediate the relation between motor skills and early achievement across the six
countries? We hypothesized that both gross and fine motor skills would contribute to achievement
in mathematics and language and literacy in all six countries. We expected that fine motor skills
would have larger associations with achievement than gross motor skills, based on earlier research
(Grissmer et al., 2010). Furthermore, based on Becker et al. (2014), we anticipated that EF would
mediate the relation between fine and gross motor skills and early achievement in language and
literacy and mathematics. We had no empirical basis to expect that there would be differences across
the six countries.
Data for the present study were from the validation study of the EAP-ECDS conducted between 2013
and 2014. Participants were 8,439 children from six countries: Cambodia, China, Mongolia, Papua
New Guinea, Timor-Leste, and Vanuatu. The final analytic sample excluded children who were
initially sampled but were outside the intended age range of 36 to 72 months and also excluded
ethnic minority children, as sampling of ethnic minorities was insufficiently representative. After
these exclusions, the present study included 7,797 children ages 36 to 72 months (3,889 girls) and
their parents from the six countries.
The sampling plan in five countries was developed in conjunction with the country’s national
census department or statistics institute. The objective was to obtain a nationally representative
sample using multistage sampling with the last stage at the community level. Stratified random
sampling by urban/rural location, gender, and age in years (3, 4, and 5) was conducted to achieve a
1064 L. ZHANG ET AL.
minimum sample of 100 children in each of the 12 categories. This was considered sufficient to
detect a difference between subgroups of 0.25–0.3 SD with 0.80 power, α= .05, and 24 children per
community, unadjusted for covariates. The exception was the sample from China, which was drawn
from four provinces and a municipality chosen for their divergent levels of economic development.
Furthermore, in China, an additional stage was added to sample kindergartens within communities.
There are great variations in contexts and in ECE among the six countries. For example, country
population ranged from 1.4 billion in China to 0.27 million in Vanuatu, gross domestic product per
capita income in 2014 ranged from USD $1,094.60 in Cambodia to USD $7,590 in China, stunting
rates ranged from 9% in China to 58% in Timor-Leste, and the gross enrollment ratio for preprimary
education in 2012 ranged from 15% in Cambodia to 85% in Mongolia (see Rao et al., 2018, for
Of the six countries, China has been acknowledged as the world leader in educational achieve-
ment because of distinguished performance on international achievement tests (Organisation for
Economic Co-operation and Development, 2014,2016). The Chinese culture stresses the importance
of propriety, discipline, self-control, and the exertion of effort, and parents emphasize school
learning (Rao, Sun, & Zhang, 2014). Mongolian people also highly value education and prioritize
children’s education (Gundenbal & Salmon, 2011). In Vanuatu, because of financial constraints,
parents tend to defer children’s enrollment in formal education until primary school (Ministry of
Education, Government of Vanuatu, 2013). There is a low quality of ECE due to a lack of
educational resources and qualified teachers in centers and Kindys (kindergartens in Vanuatu;
Ministry of Education, Government of Vanuatu, 2013). In Papua New Guinea, the quality of
preprimary education is not deemed to be high because of low levels of teacher qualifications, a
low teacher–child ratio (about 1:47 in 2013), and the lack of a national early childhood care and
education curriculum (Department of Education, Papua New Guinea, 2015). Cambodia is expanding
preschool access but has significant urban/rural disparities. Children from poor families, those with
less educated mothers, and those from ethnic minority groups in rural areas have very limited access
to preschool (Rao, Sun, Ng, et al., 2014). In Timor-Leste, challenges to providing ECE include the
concern that some parents may not be aware of the importance of early learning and education
(Democratic Republic of Timor-Leste, 2015).
The present study used data from the validation study of the EAP-ECDS. In the initial stage, core
members of research teams from the six countries received training from a university-based
technical support group in the region. During training, items requiring country adaption and
culturally specific adaption were discussed. After training, each research team followed standard
translation and back-translation procedures to ensure the equivalence of the English and local
versions of the EAP-ECDS. In each country, two local persons who were bilingual (in the local
language and English) and who had expertise in the area of ECE but were not familiar with the scales
were invited to translate the assessment and questionnaire forms. The first person translated the
original English version to the local language, and the second person translated the local version
back to English. Each country team discussed with the technical support group any differences or
revisions for the measures. In addition, each country research team recruited assessors who were
university faculty members, local officers, and graduate students in the area of ECE. All assessors
received in-country training from the university-based technical support group and several rounds
of training from core members of the country team. After that, the assessors conducted pilot
assessments, videotaped the assessment process, and sent the videos to the technical support
EARLY EDUCATION AND DEVELOPMENT 1065
group for feedback. These procedures were followed to ensure standardized administration and
scoring procedures (Rao et al., 2018).
Trained assessors in each country team administered the EAP-ECDS to children in individual
sessions after obtaining consent from parents. To ensure reliability in data collection each assessor
conducted tests together with a supervisor. The interrater reliability was at least 85% between the
assessor and supervisor before the commencement of formal assessment, and regular monitoring of
interrater reliability was undertaken (Rao, Sun, Ng, et al., 2014,2018).
Parents provided standard demographic information through individual interviews in five coun-
tries. The exception was China, where parents completed questionnaires in small groups under the
supervision of a research assistant, who was also able to answer any queries. This was done because
of the relatively high literacy rate in China compared to the other countries.
All measures of gross and fine motor skills, EF, and achievement in early language and literacy and
early mathematics were from the EAP-ECDS. The EAP-ECDS is an 85-item psychometrically robust
tool that assesses child development in the following seven domains: cognitive development;
language and emergent literacy; socioemotional development; motor development; cultural knowl-
edge and participation; health, hygiene, and safety; and approaches to learning (Rao, Sun, Ng, et al.,
2014). All items were developed based on the Early Learning and Development Standards from seven
countries in East Asia and the Pacific (Rao, Sun, Ng, et al., 2014). The selected items for each
measure have been commonly used in prior studies and were agreed on by the technical support
group as typical tasks addressing each developmental domain. More details on the scales can be
found in the technical report on the validation study (Rao, Sun, Ng, et al., 2014).
Motor skills assessment
A total of 10 items were selected from the EAP-ECDS subscales of Motor Development and
Language and Emergent Literacy to assess motor skills. These included five items on fine motor
skills and five items on gross motor skills. Cronbach’s alpha was calculated to assess the reliability of
each measure, and, because of clustering in the sample design, intracluster correlations (ICCs) were
calculated to compare the within-province and between-province variance. The fine motor assess-
ment (α= .88, ICC = .10) included folding a paper plane following a demonstration, using a pencil to
copy three shapes, drawing a person, stringing beads, and buttoning and unbuttoning a vest. The
gross motor assessment (α= .75, ICC = .08) included walking forward and backward on a narrow
strip, pouring water into a cup and laying down the cup in a designated place, throwing a ball to a
target, and catching a ball. Some items are composed of several subitems. All subitems and items
with no subitems were scored 0 or 1 (see the Appendix).
Early achievement measures
The language and literacy test contained 12 items from the domain of language and emergent
literacy (α= .92, ICC = .14) in the EAP-ECDS. The test examined children’s receptive and expressive
language (e.g., recognizing and naming actions and telling a story according to pictures), prereading
skills (e.g., recognizing simple written information and reading a book), and prewriting skills (e.g.,
writing their own names). The mathematics test comprised 11 items from the cognitive development
domain of the EAP-ECDS (α= .93, ICC = .10). These items assessed children’s command of
concepts of time, quantity, numeracy and counting, simple computation, shape, pattern, and
classification (see the Appendix).
All five items tapping three components of EF—working memory, inhibitory control, and attention
skills—were selected from the EAP-ECDS subscales of Cognitive Development, Language and
1066 L. ZHANG ET AL.
Emergent Literacy, and Approaches to Learning (α= .88, ICC = .10). Two items requiring children
to repeat multiword sentences (from five words to seven words) and act according to a three-step
instruction examined children’s working memory. The basic version of the Dimensional Change
Card Sort (Zelazo, 2006) is commonly used as a measure of cognitive flexibility or set shifting
(Doebel & Zelazo, 2015) and was used to assess attentional skills in the present study. In the task,
children were presented with two target cards (e.g., a blue rabbit and a red boat) and a series of test
cards (e.g., red rabbits and blue boats). They were instructed to sort the test cards according to one
dimension (e.g., by color) and then according to another dimension (e.g., by shape) without any
pause in between. The tapping game (Diamond & Taylor, 1996) and the gift delay task (Carlson &
Wang, 2007) explored children’s inhibitory control. The tapping game included six trials and
required children to tap once when the assessor tapped twice and vice versa. The gift delay task
was conducted at the end, and children were told that they would be given a surprise gift but would
have to wait for a moment (a minute). Children received a score of 1 if they gave a correct response
in each step or trial or were able to wait for a minute (see the Appendix).
A variable for maternal education was constructed using the mother’shighest qualification across
nine levels from no formal education to postgraduate and was operationalized as a continuous
variable. An indicator of household wealth was constructed based on standard questions about
household asset ownership from the Multiple Indicator Cluster Survey (UNICEF, 2005), and,
following Filmer and Pritchett (2001), a composite variable was created using principal component
analysis. Similar techniques have been used extensively elsewhere to represent household wealth
(Schady et al., 2015). A country-specific standardized variable was created such that a score of 0
indicated mean wealth compared to other within-country households, and a score of 1 indicated
wealth 1 SD above the average for that country.
The following steps were taken to deal with missing values. Dummy variables for missingness were
created for each of the variables used in the analysis. Country, age, household wealth, and gender
had no missing values. Missing values were found for language and literacy (seven cases), mathe-
matics (two cases), gross motor skills (12 cases), fine motor skills (seven cases), EF (three cases),
maternal education (170 cases), and urban/rural residence (13 cases).
For these variables, associations were examined between missingness and scores in language and
literacy, mathematics, gross motor skills, fine motor skills, EF, maternal education, and household
wealth. Missingness in mathematics, maternal education, and urban/rural residence was not asso-
ciated with scores for any of the key variables, so we imputed missing values for mathematics and
maternal education using the province means. When urban/rural residence was missing cases were
randomly allocated either urban or rural residence weighted by the proportion of urban or rural
cases in that province.
Missingness in language and literacy was associated with fine motor scores and with EF scores;
missingness in gross motor skills was associated with language and literacy, fine motor, and EF
scores; missingness in fine motor skills was associated with early literacy, gross motor, and EF scores;
and missingness in EF was associated with mathematics scores. For these variables, where necessary,
we imputed scores using means that were specific to the province, maternal education level, house-
hold wealth quintile, and gender of each missing case. We did not use more computationally
demanding methods such as multiple imputation to deal with missing values. This was because
the advantages of such methods would have been small given that our data met the criteria of (a)
having a large sample size (>1,000 cases overall and in five of six countries individually) and (b)
having a low proportion of missing values (less than 5% for all variables; Cheema, 2014).
EARLY EDUCATION AND DEVELOPMENT 1067
A series of descriptive, regression, and structural equation modeling (SEM) analyses were conducted
using Stata Version 13.1. In the regression and SEM analyses, all original total scores for motor skills,
EF, and early achievement were transformed to country-specific, month-of-age-adjusted zscores so
that children’s scores could be compared with those of their within-country same-age peers.
Means and standard deviations were calculated for key variables for each of the six countries.
Demographic statistics were also generated for the control variables, including child age, gender,
urban/rural residence, maternal education, and country-specific household wealth.
Motor skills, EF, and early achievement
Hierarchical linear modeling (HLM) considers and explores the structure of hierarchical populations
(Bartholomew, Steele, Galbraith, & Moustaki, 2008). It is appropriate for analyzing data from
clustered samples, as it accounts for potential similarities between children residing in the same
area. Given the clustered sampling design in our study, we used HLM to examine associations
between gross and fine motor skills and early achievement in both language and literacy and
mathematics by including either gross motor or fine motor skills as an independent variable and
either early language and literacy or early mathematics as a dependent variable in separate regression
models. We then used HLM to analyze associations between motor skills and early achievement by
including fine and gross motor skills as two independent variables in the same regression model.
Differences in the magnitudes of associations between gross motor skills and early achievement and
those between fine motor skills and early achievement were then tested for statistical significance. In
each case, regressions were run once for the overall sample and again for each country separately,
and control variables were included for child age, gender, urban/rural residence, maternal education,
country-specific household wealth, and country (for the overall sample regressions only). The
clustering variable used was an indicator of the province in which assessments were conducted. In
all HLM regressions, province was used as the Level 2 variable.
SEM was used to examine whether EF mediated the association between gross and fine motor
skills and early language and literacy and mathematics scores after we controlled for the same
variables used in the HLM analyses. Two sets of SEM models were constructed, analyzing the
mediating effect of EF for (a) the relations between fine and gross motor skills and early language
and literacy and (b) the relations between fine and gross motor skills and early mathematics. In both
sets of SEM analyses province was used as the variable that adjusted the robust standard errors for
clustering. Our approach to mediation analysis followed that outlined by Hayes (2009), whereby it
was not necessary for a total effect to be statistically significant in order to conclude that a significant
indirect effect could be considered evidence of mediation.
Demographic information and descriptive statistics for each of the six countries are presented in
Table 1. Means and standard deviations are shown for gross motor skills, fine motor skills, EF, early
language and literacy, and early mathematics. That stated, the focus of our analyses was not to make
comparisons between countries in early achievement. We wished to identify similarities and differ-
ences across countries in terms of relations among motor skills, EF, and early achievement.
Motor skills and early achievement
Four series of HLM regressions were performed with gross motor skills or fine motor skills as separate
independent variables and early language and literacy or early mathematics achievement as a dependent
variable after we controlled for the aforementioned variables for the overall sample and for each country
1068 L. ZHANG ET AL.
Table 1. Developmental scores and demographic statistics.
Cambodia China Mongolia Papua New Guinea Timor-Leste Vanuatu
Variable N M SD N M SD N M SD N M SD N M SD N M SD
Fine motor skills 1,198 6.9 3.5 1,621 7.6 3.5 1,232 8.9 3.2 1,778 4.2 3.1 1,182 5.0 3.0 779 5.7 3.6
Gross motor skills 1,198 6.7 2.0 1,617 6.2 2.1 1,232 6.3 2.4 1,777 6.8 2.8 1,183 6.4 2.5 778 7.8 3.0
Executive function 1,198 10.4 4.0 1,622 12.9 3.5 1,232 9.4 4.2 1,778 7.6 4.1 1,185 7.7 3.9 779 9.2 4.2
Early language and literacy 1,198 22.7 7.8 1,622 31.7 7.0 1,232 27.0 5.9 1,778 18.4 8.4 1,181 17.9 6.1 779 22.4 9.0
Early mathematics 1,198 9.3 6.4 1,623 17.0 7.3 1,232 9.3 6.3 1,778 6.0 4.8 1,185 6.7 4.5 779 9.2 7.1
Wealth SD (country specific) 1,198 0.0 1.0 1,623 0.0 1.0 1,232 0.0 1.0 1,778 0.0 1.0 1,185 0.0 1.0 781 0.0 1.0
Maternal education (nine levels) 1,182 3.4 1.2 1,592 5.7 1.2 1,228 5.7 1.2 1,752 3.2 1.2 1,148 3.4 1.6 725 3.4 1.0
Age in months 1,198 53.8 10.4 1,623 54.6 10.2 1,232 53.7 9.9 1,778 52.9 10.1 1,185 53.2 10.2 781 54.6 9.7
Percent girls 49.9% 49.7% 49.8% 50.7% 50.0% 48.4%
Percent urban 54.1% 49.3% 50.7% 33.6% 50.3% 11.2%
Note. Descriptive statistics are shown prior to the imputation of missing values.
EARLY EDUCATION AND DEVELOPMENT 1069
individually. For the overall sample, gross motor skills (β
language and literacy
= .27, p< .01; β
p< .01) and fine motor skills (β
language and literacy
=.43,p< .01; β
= .37, p<.01)wereboth
significantly associated withearlyachievement in both early language and literacy and early mathematics
(see Supplementary Figure 1a and 1b). Significant associations between gross motor skills (β
< .01) or fine motor skills (β
language and literacy
< .01) and early achievement were found across all six countries
individually (see Supplementary Figure 1a and 1b).
Furthermore, another two separate series of HLM regressions, one with early language and literacy
and the other with early mathematics as the dependent variable, with both gross motor skills and fine
motor skills included as independent variables, were run for the overall sample and for each country to
show the relative magnitudes of the gross motor skills and fine motor skills coefficients. Table 2
indicates that for the overall sample, gross motor skills (β
language and literacy
= .16, p< .01;
= .14, p< .01) and fine motor skills (β
language and literacy
= .38, p< .01; β
p< .01) were significantly associated with both language and literacy and mathematics. Both fine
motor skills (β
language and literacy
= .28–.55, p
< .01; β
= .23–.44, p
< .01) and gross motor skills
language and literacy
= .09–.26, p
< .05; β
= .07–.19, p
< .05) were also significant predictors of
early achievement across the six countries individually (see Table 2). As shown in Figures 1 and 2, after
the fine motor skills variable was included in the regression models, the magnitude of the relation
between gross motor skills and early achievement in both language and literacy and mathematics
decreased to a large extent for the overall sample and for each country individually.
Further analyses showed that fine motor skills had larger associations than gross motor skills with
early language and literacy (β= .22, p< .01) and with early mathematics (β= .19, p< .01) for the
overall sample (see Table 2). Fine motor skills had a larger association than gross motor skills with
early language and literacy in Cambodia (β= .19, p< .01), China (β= .19, p< .01), Mongolia
(β= .25, p< .01), Timor-Leste (β= .28, p< .01), and Vanuatu (β= .40, p< .01), but no significant
difference was found in Papua New Guinea (p> .05; see Table 2). The finding that fine motor skills
had a larger association than gross motor skills with early mathematics was replicated in Cambodia
(β= .13, p< .05), China (β= .15, p< .01), Mongolia (β= .21, p< .01), Papua New Guinea (β= .26,
p< .01), and Vanuatu (β= .30, p< .01). However, for children from Timor-Leste there was no
significant difference (p> .05).
Motor skills, EF, and early achievement
To investigate whether EF mediates the relation between motor skills and early language and literacy
and mathematics, two sets of SEM analyses were constructed, with one set including the early
Table 2. Differences between fine and gross motor skills in associations with early achievement, overall and for each country.
Early Language and Literacy Early Mathematics
Fine Motor Gross Motor Difference Fine Motor Gross Motor Difference
Country N βSE p βSE p βSE p βSE p βSE p βSE p
Overall 7,797 .38 .02 .00 .16 .02 .00 .22 .03 .00 .33 .02 .00 .14 .02 .00 .19 .02 .00
Cambodia 1,198 .36 .04 .00 .17 .03 .00 .19 .05 .00 .33 .05 .00 .19 .05 .00 .13 .07 .05
China 1,623 .28 .04 .00 .09 .04 .02 .19 .07 .00 .23 .03 .00 .07 .03 .02 .15 .02 .00
Mongolia 1,232 .34 .04 .00 .09 .03 .00 .25 .06 .00 .34 .02 .00 .13 .02 .00 .21 .04 .00
Papua New Guinea 1,778 .36 .06 .00 .26 .05 .00 .10 .09 .27 .40 .03 .00 .14 .03 .00 .26 .05 .00
Timor-Leste 1,185 .44 .03 .00 .16 .04 .00 .28 .05 .00 .30 .05 .00 .18 .04 .00 .12 .07 .08
Vanuatu 781 .55 .03 .00 .15 .03 .00 .40 .05 .00 .44 .06 .00 .14 .03 .00 .30 .08 .00
Note. The table shows the results of several hierarchical linear modeling regressions examining associations between motor skills
and early achievement controlling for age, sex, urbanicity, wealth, maternal education, and country (for the overall sample
regressions only). Regressions were run for the sample overall and also for each country individually. Fine and gross motor skills
were both included as independent variables in the same regression model, and differences between their coefficient
magnitudes were tested for statistical significance. The difference in coefficient magnitudes for early mathematics in
Cambodia was significant at the 5% level, but the pvalue was rounded up to .05.
1070 L. ZHANG ET AL.
language and literacy variable and the other set including the early mathematics variable. Each set of
SEM analyses was run for the overall sample and for each country individually. Table 3 shows total
effects between motor skills and early achievement and splits these total effects into direct effects
between motor skills and early achievement and indirect effects via EF. Two sets of results are shown
Coefficient size (SD units)
Overall Cambodia China Mongolia PNG Timor-Leste Vanuatu
Without fine motor control With fine motor control
Figure 2. Associations between gross motor skills and early mathematics achievement, before and after controlling for fine motor
skills. The chart shows the results of several hierarchical linear modeling regressions examining associations between gross motor
skills and early achievement, before and after controlling for fine motor skills and also controlling for age, sex, urbanicity, country,
wealth, and maternal education. Regressions were run for the sample overall and also for each country individually. Error bars
show 95% confidence intervals. PNG = Papua New Guinea.
Overall Cambodia China Mongolia PNG Timor-Leste Vanuatu
Coefficient size (SD units)
Without fine motor control With fine motor control
Figure 1. Associations between gross motor skills and early language and literacy achievement, before and after controlling for
fine motor skills. The chart shows the results of several hierarchical linear modeling regressions examining associations between
gross motor skills and early achievement, before and after controlling for fine motor skills and also controlling for age, sex,
urbanicity, country, wealth, and maternal education. Regressions were run for the sample overall and also for each country
individually. Error bars show 95% confidence intervals. PNG = Papua New Guinea.
EARLY EDUCATION AND DEVELOPMENT 1071
for early language and literacy and early mathematics separately. Results are also presented for the
six countries together and for each country individually.
In general, EF mediated the relation between motor skills and early achievement both for the
overall sample and for each country (see Table 3). All direct, indirect, and total effects between fine
motor skills and early achievement via EF were statistically significant in every model (p
Table 3). EF mediated the relation between fine motor skills and early achievement in both language
and literacy and mathematics for the six countries as a whole and for each country individually.
Across the six countries combined, EF accounted for 27.2% of the total effect of fine motor skills on
early language and literacy and 37.7% of the total effect of fine motor skills on mathematics.
The indirect effects between gross motor skills and early achievement via EF were significant in every
model. Across the six countries combined, EF accounted for 41.5% of the total effect of gross motor
skills on early language and literacy and 53.8% of the total effect of gross motor skills on early
mathematics. However, the direct effects of gross motor skills on early language and literacy and
early mathematics were not significant in China (β
early language and literacy
= .08, p>.05;β
= .02, p> .05), Mongolia (β
early language and literacy
= .04, p>.05),
Papua New Guinea (β
early language and literacy
=.09,p> .05; β
=.02,p> .05), or Vanuatu
early language and literacy
=.10,p> .05), which suggests that for children in
these four countries, EF played a full mediating role between gross motor skills and early achievement.
For the overall sample, Cambodia, and Timor-Leste, the direct effects remained statistically significant,
which suggests that in these cases, EF mediated only part of the relation between motor skills and early
achievement. The magnitudes of the coefficients are illustrated in Supplementary Figure 2a and 2b.
Table 3. Direct effects, and indirect effects via EF, of fine and gross motor skills on achievement in early language and literacy and
Fine Motor Skills Gross Motor Skills
Early language and literacy
Overall .11*** 27.2 .30*** 72.8 .42*** .06*** 41.5 .09*** 58.5 .15***
Cambodia .10** 29.6 .23*** 70.4 .33*** .05*** 26.9 .14*** 73.1 .19***
China .05*** 18.4 .24*** 81.6 .30*** .04** 31.8 .08 68.2 .11*
Mongolia .10*** 29.7 .25*** 70.3 .35*** .04*** 100.0 −.01 0.0 .03
.15** 29.1 .36*** 70.9 .51*** .07*** 45.5 .09 54.5 .16
Timor-Leste .12*** 25.4 .34*** 74.6 .46*** .05*** 27.6 .12* 72.4 .17**
Vanuatu .15*** 25.9 .42*** 74.1 .57*** .11*** 68.4 .05 31.6 .15***
Overall .14*** 37.7 .23*** 62.3 .37*** .07*** 53.8 .06** 46.2 .14***
Cambodia .12*** 36.8 .21*** 63.2 .33*** .06*** 33.2 .13** 66.8 .19***
China .08*** 34.7 .16*** 65.3 .24*** .05*** 69.4 .02 30.6 .08*
Mongolia .13*** 39.6 .20*** 60.4 .33*** .05*** 54.2 .04 45.8 .09*
.14*** 29.2 .35*** 70.8 .49*** .07*** 81.4 .02 18.6 .09
Timor-Leste .15*** 47.1 .17*** 52.9 .32*** .06*** 32.9 .12*** 67.1 .18***
Vanuatu .12*** 26.5 .34*** 73.5 .46*** .09*** 47.8 .10 52.2 .18**
Note. Results are from two series of structural equation models, one with early mathematics as the dependent variable and the
other with early language and literacy as the dependent variable, each run once for the whole sample and then again for each
country separately. Fine motor and gross motor skills were both included as independent variables in each model. Results show
total, direct, and indirect (through EF) effects of fine and gross motor skills on language and literacy and mathematics
achievement. The proportions of the total effect attributable to direct and indirect effects are shown as percentages. EF =
*p< .05. **p< .01. ***p< .001.
1072 L. ZHANG ET AL.
This study examined (a) associations between motor skills and early academic achievement and (b)
whether EF mediates relations between motor skills and early academic achievement in young children
from six developing countries inEast Asia and the Pacific. A burgeoning literature has shown that motor
skills, and fine motor skills in particular, are strong predictors of academic attainment (Cameron et al.,
2016; Grissmer et al., 2010; Murrah et al., 2013; Pagani & Messier, 2012; Pitchford et al., 2016). However,
little is known about the interplay among motor skills, EF, and academic achievement in LMICs. The
present study contributes to the emerging evidence from LMICs.
The prediction of early achievement from motor skills
Associations between motor skills and academic achievement were examined using a series of HLM
regressions. The findings upheld the expectation that motor skills are strong predictors of early achieve-
ment in early language and literacy and mathematics. Comparatively speaking, motor skills are usually
neglected in studies of early learning (Pagani & Messier, 2012). The current study found that both gross
and fine motor skills were significantly related to early achievement in both language and literacy and
mathematics. This finding corroborates studies indicating that motor skills are an important contributor
to school outcomes (Becker et al., 2014; Cameron et al., 2012,2016; Luo et al., 2007; Murrah et al., 2013;
Pagani & Messier, 2012). Specifically, researchers consider fine motor skills an important indicator of
school readiness and early achievement and advocate the promotion of these skills in the early years
(Carlson, 2014; Grissmer et al., 2010). Gross motor skills are generally thought to be related to social skills
or physical well-being and to have a weaker association with academic achievement than fine motor skills
(Cameron et al., 2016;Grissmeretal.,2010; Kim et al., 2015). However, our study found that even after
we controlled for fine motor skills, associations between gross motor skills and early academic achieve-
ment remained significant. The notable associations of early achievement to fine motor skills and gross
motor skills were not only evident for the large, combined sample but also robust in each individual
country. This implies that both fine motor skills and gross motor skills are closely related to early
achievement and that the finding is consistent across countries.
Furthermore, we found that in comparison with gross motor skills, fine motor skills were a better
predictor of both early language and literacy and mathematics achievement in the overall sample and
in individual countries, except for Timor-Leste and Papua New Guinea. Researchers have pointed
out that in education settings that include ECE programs, children spend a considerable amount of
time in fine motor activities including drawing, cutting, folding, stringing beads, and manipulating
objects (Cameron et al., 2012; Pitchford et al., 2016). Such activities require visuomotor integration
and mapping of visual representations to concepts, which are important for early learning and
cognitive processes (Cameron et al., 2016; MacDonald et al., 2016). When children are skilled
enough to evidence automaticity in these activities, they will be capable of higher levels of conceptual
processing, including connecting symbols with meaning, and this in turn promotes early achieve-
ment (Cameron et al., 2012; Pitchford et al., 2016). Gross motor skills require relatively less
involvement of cognitive processes and may not contribute to early achievement as much as fine
motor skills (Westendorp, Hartman, Houwen, Smith, & Visscher, 2011).
It is notable that there was no significant difference in the associations of gross motor skills and
fine motor skills with early language and literacy in Papua New Guinea and with early mathematics
in Timor-Leste. These two countries are among those with the lowest levels of economic develop-
ment among the six countries studied (Rao, Sun, Ng, et al., 2014). The finding could be related to
limited preschool opportunities for children in these two countries, in terms of both participation
and quality. Furthermore, children in these two countries may have many opportunities to engage in
gross motor activities but few opportunities to engage in fine motor activities. The descriptive
analyses further showed that children in these two countries had the lowest scores in fine motor
EARLY EDUCATION AND DEVELOPMENT 1073
skills. This may be why there were no significant differences between gross and fine motor skills in
contributing to the prediction of early academic achievement.
Mediation of EF in the relation between motor skills and early achievement
This study also examined the role of EF in the relation between motor skills and early achievement.
By extending the existing literature and including both gross and fine motor skills, our study showed
that EF mediates the association between early achievement and both gross and fine motor skills.
This finding was consistent across all six countries in East Asia and the Pacific. This result echoes
findings of similar studies of children from different cultural backgrounds (Becker et al., 2014;
Chang & Gu, 2018; MacDonald et al., 2016; Roebers et al., 2014). Relations between gross motor
skills and early achievement have received less attention in the existing research, and our study adds
to the extant literature by showing that EF also mediates the relation between gross motor skills and
academic achievement. Researchers suggest that the initiation of motor activities triggers the execu-
tion of EF skills and then affects children’s school performance (Becker et al., 2014; Cameron et al.,
2012; MacDonald et al., 2016).
The completion of both fine and gross motor skills assessment tasks in the current study required
children to focus their attention (e.g., walking on a thin strip without significant deviation), rely on
working memory (e.g., remembering the steps of folding a plane), and engage in inhibitory control
(e.g., in the tapping task). All of these three components of EF have been shown to predict school
performance both concurrently and longitudinally (G. J. Duncan et al., 2007; Jacob & Parkinson,
2015; Zhang & Rao, 2017). Our results show that motor skills contribute significantly to language
and literacy and mathematics achievement through EF. Therefore, it is possible that motor activities
augment the cognitive and learning process in young children and then enhance school achievement.
Although EF was a partial mediator between fine motor and gross motor skills and early
achievement in the overall sample and in Cambodia and Timor-Leste, it played a full mediating
role in the relation of gross motor skills with early achievement in language and literacy and
mathematics in China, Mongolia, Papua New Guinea, and Vanuatu. The finding for these four
countries is consistent with that in the United States showing that gross motor skills did not predict
academic achievement when fine motor skills and EF were considered (Cameron et al., 2012). This
also implies that when EF is included, fine motor skills make more of a contribution to early
achievement than gross motor skills. Both China and Mongolia place a high value on education
(Gundenbal & Salmon, 2011; Rao, Sun & Zhang, 2014). Parents and teachers may organize different
forms of activities in addition to gross motor activities to facilitate children’s early learning, such as
in-hand manipulation activities and early academic learning, and thus may reduce the effect of gross
motor skills on early achievement. Children from Papua New Guinea and Vanuatu achieved
relatively high gross motor scores but relatively low scores for fine motor skills, EF, and early
achievement. It is interesting that the relatively higher level of gross motor scores did not correspond
to benefits in early achievement for children in these two countries. Further studies are required to
explore the underlying mechanism.
Despite the fact that the six countries differed in gross and fine motor skills, EF, and early
achievement, this study consistently found that motor skills contribute to early achievement in
language and literacy and mathematics and that EF mediates the relation between both fine motor
skills and gross motor skills and early achievement. This means that the path of motor skills →EF →
early achievement is universal across different LMICs in East Asia and the Pacific.
This study is one of the few to focus on the relations between fine and gross motor skills, EF, and
early achievement in language and literacy and mathematics in developing countries. In general,
many studies in developmental psychology are conducted in Western contexts, and researchers have
1074 L. ZHANG ET AL.
called for more diverse samples to avoid biased conclusions (Nielsen et al., 2017). By drawing on a
large and representative sample from six different countries in East Asia and the Pacific, our study
sought to address this sampling gap. We found that both fine motor and gross motor skills and EF
were important for early achievement. Fine motor skills made a greater contribution to early
achievement than gross motor skills. Furthermore, EF fully or partially mediated the relation
between motor skills and early achievement. Although the countries differed in child outcomes,
the findings were generally consistent across East Asia and the Pacific.
Neuroimaging studies indicate that the brain regions mainly involved in motor activities or
cognitive activities are coactivated (Diamond, 2000; Grissmer et al., 2010), which suggests that
motor skills and cognitive skills develop together. Together with our study, these studies suggest
that the enhancement of motor skills might be a pathway to boosting school attainment for children
Physical activities provide children with abundant opportunities to learn and practice motor
skills. Studies have shown that physical activities such as aerobic exercise, martial arts, yoga, and
tennis are effective in enhancing EF (Davis et al., 2011; Diamond & Lee, 2011; Westendorp et al.,
2014). In addition, fine motor activities such as copying designs are likely to improve specific
components of EF (e.g., attention; Kim et al., 2015; van der Fels et al., 2015). Our findings support
the move to increase motor activities in ECE in East Asia and the Pacific. However, there is typically
relatively little time in the daily schedule of program activities in ECE for physical activities
(Cameron et al., 2016; Pagani & Messier, 2012). Therefore, it is recommended that teachers and
parents provide children with substantial opportunities to engage in physical games and motor
activities to facilitate their gross motor skills and to use manipulatives to promote fine motor skills.
In addition, although the present study did not primarily aim to address cultural differences in
exploring the relation among motor skills, EF, and early achievement, minor differences among the
countries are worth mentioning. For instance, although associations between fine motor skills and
early achievement were significantly larger than associations between gross motor skills and early
achievement in the majority of countries, for children in two lower income countries—Timor-Leste
and Papua New Guinea—there was no significant difference in coefficients for gross motor skills and
fine motor skills. This implies that particular importance should be placed on the development of
fine motor skills in children from more economically disadvantaged countries. At the same time,
although gross and fine motor skills significantly predicted early achievement even after we con-
trolled for EF in the overall sample and in Cambodia and Timor-Leste, the gross motor–achievement
link was not significant in China, Mongolia, Papua New Guinea, and Vanuatu. Gross motor scores
in China and Mongolia were relatively low. Therefore, both countries may provide children with
more gross motor activities to promote their early achievement. The provision of more gross motor
and physical activities may also prevent childhood obesity in both countries. Children from Papua
New Guinea and Vanuatu had relatively low scores in fine motor skills, and their development of
fine motor skills should be promoted. These cultural differences pose the need for further studies to
uncover the influences of culturally specific practices in ECE on the relation among motor skills, EF,
and academic achievement.
Furthermore, our study also revealed the mediating role of EF on the association between motor
skills and early achievement. In addition to enhancing motor skills, the facilitation of EF may also
promote children’s early academic learning. Research has indicated that education and schooling is
significantly associated with cognitive skills, especially at the earliest ages (Burrage et al., 2008;
Gurven et al., 2017). Classroom practices such as teachers’proactive regulatory instructions and
group work help to engage children in classroom activities; improve their attentional control, self-
regulation abilities, and EF; and bring about benefits to academic learning (Lan et al., 2009).
Furthermore, some curricula and activities that specifically focus on different or specific components
of EF have been shown to improve children’s EF skills and their academic performance (Diamond,
Barnett, Thomas, & Munro, 2007; Jacob & Parkinson, 2015; Tominey & McClelland, 2011).
EARLY EDUCATION AND DEVELOPMENT 1075
Therefore, experts should strengthen the quality of ECE and support EF skills in preschool programs
by embedding different components of EF into the curriculum.
Although this study extends the prior literature on the contribution of motor skills and EF to
early achievement, it has several limitations. First, all measures in the study were from one instru-
ment that is used to assess the holistic development of children instead of specific components of
child development. Although the scale is psychometrically robust, not all aspects of different
domains were included (Rao, Sun, Ng, et al., 2014). For instance, the gross motor items requiring
balancing and body orientation, such as hopping on each foot and skipping, were not included. In
addition, there are limited items in the early achievement tests of language and literacy and
mathematics. Second, although we found that EF mediated the relation between motor skills and
early achievement in language and literacy and mathematics, caution should be exercised in inter-
preting the findings given the cross-sectional design of the study; longitudinal studies are recom-
mended. Third, cultural differences in terms of child rearing and education may have an impact on
early learning and development in children from different countries. The current study found minor
differences among the countries. However, as we do not have data on relevant factors such as
parenting practices and educational practices in ECE programs, we are not able to explain the
reasons for the differences. Similarly, although malnutrition or stunting has a detrimental impact on
child development and its prevalence is high in LMICs, including some countries in East Asia and
the Pacific (Lu, Black, & Richter, 2016; Miller et al., 2016; Sudfeld et al., 2015), our study did not
include such data. The inclusion of data on malnutrition and stunting among the participant
children might have helped improve our understanding of the differences in child development
among the countries. Therefore, further studies may examine how factors such as parenting and
educational practices as well as child nutritional status influence the development of motor skills, EF,
and early achievement and the interplay among these three child outcomes among different
To conclude, we found that fine motor skills and gross motor skills are strong predictors of early
achievement in language and literacy and mathematics in young children in East Asia and the
Pacific. Fine motor skills are more important in facilitating early achievement than gross motor
skills. At the same time, gross motor skills contribute significantly to early achievement even after
fine motor skills are controlled for. Furthermore, EF mediates the links between motor skills and
academic achievement. There are minor differences among countries. By extending the sample and
adopting different measures, this study achieved findings that are generally consistent with the
existing literature. Findings suggest that experts should attach importance to children’s motor
development and provide them with adequate opportunities to engage in motor activities to promote
their EF and ensure a good start for school.
Li Zhang http://orcid.org/0000-0001-6272-3165
Jin Sun http://orcid.org/0000-0001-6707-3763
Ben Richards http://orcid.org/0000-0002-8809-9097
Nirmala Rao http://orcid.org/0000-0002-5695-3156
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Example Items for the Measures of Motor Skills, Executive Function, and Early
Table A-1. Example Items for the Measures of Motor Skills, Executive Function, and Early Achievement
0, 1, R
Fine motor skills
1 Correctly complete folding Steps 1–3
Correctly complete folding Steps 4–7
2 Be able to copy a circle/triangle/rectangle A score of 1 for each successful
Gross motor skills
3 Walk forward: deviation indications ≤3 times
Walk backward: deviation indications ≤3 times
4 Hit the target for each of the three trials A score of 1 for each successful
Early language and literacy
5 Point out a picture according to an instruction (e.g., jumping) A score of 1 for each correct trial
6 Be able to name the characters/objects in the pictures or referred to when telling
7 Be able to write a letter or symbol
Be able to write half of the name without a writing demonstration
Be able to write half of the family name without a writing demonstration
8 Put different numbers of blocks on the paper A score of 1 for each correct trial
9 Know the sum of one apple plus two apples and more computation
10 Point out a large white circle after reading a pattern in the picture book
11 Complete a three-step instruction A score of 1 for each correct step
12 Classify six cards according to color/shape A score of 1 for each correct step
13 Be able to tap correctly (e.g., tapping once when the assessor taps twice) A score of 1 for each correct trial
1080 L. ZHANG ET AL.