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Links between Motor Skills and Indicators of School Readiness at Kindergarten Entry in Urban Disadvantaged Children

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Abstract and Figures

School readiness represents a kindergarten characteristic which ultimately contributes to academic and personal success. This literature has traditionally focused on cognitive and behavioral characteristics. However, clinicians underscore the critical importance of motor skills to kindergarten preparedness. This study, using data from the Montreal Longitudinal Preschool Study, examines concurrent links between motor skills and other indicators of school readiness in typically developing children attending regular kindergarten classrooms in disadvantaged environments. Participants include a sample of 522 children from the Montreal Longitudinal Preschool Study with individual assessments of receptive vocabulary and number knowledge and teacher ratings of gross, fine, and perceptual-motor skills and classroom behaviors. The link between motor skills and early math skills completely explained any influence attributed to verbal skills. Developing a better understanding of how the distinct key elements of school readiness relate to each other will help teachers devise more comprehensive strategies in helping children become prepared for the first grade transition, especially in urban, disadvantaged settings.
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Published by Canadian Center of Science and Education 95
Links between Motor Skills and Indicators of School Readiness at
Kindergarten Entry in Urban Disadvantaged Children
Linda S. Pagani (Corresponding author)
École de psychoéducation and Centre Hospitalier Universitaire Sainte-Justine
Université de Montréal
C.P. 6128, succursale Centre-ville, Montréal, Québec, H3C 3J7, Canada
Tel: 1-514-343-6111 ext 2524 E-mail: Linda.S.Pagani@umontreal.ca
Sylvie Messier
Centre de Réadaptation Marie Enfant
Université de Montréal
5200, rue Bélanger, Montreal, Quebec, H1T 1C9, Canada
Tel: 1-514-374-1710 E-mail: sylvie.messier@umontreal.ca
Received: November 26, 2011 Accepted: December 22, 2011 Published: May 1, 2012
doi:10.5539/jedp.v2n1p95 URL: http://dx.doi.org/10.5539/jedp.v2n1p95
This IRB approved research was funded by the Social Science and Humanities Research Council of Canada
(International Opportunities Fund: Grant #861-2007-1005).
Abstract
School readiness represents a kindergarten characteristic which ultimately contributes to academic and personal
success. This literature has traditionally focused on cognitive and behavioral characteristics. However, clinicians
underscore the critical importance of motor skills to kindergarten preparedness. This study, using data from the
Montreal Longitudinal Preschool Study, examines concurrent links between motor skills and other indicators of
school readiness in typically developing children attending regular kindergarten classrooms in disadvantaged
environments. Participants include a sample of 522 children from the Montreal Longitudinal Preschool Study
with individual assessments of receptive vocabulary and number knowledge and teacher ratings of gross, fine,
and perceptual-motor skills and classroom behaviors. The link between motor skills and early math skills
completely explained any influence attributed to verbal skills. Developing a better understanding of how the
distinct key elements of school readiness relate to each other will help teachers devise more comprehensive
strategies in helping children become prepared for the first grade transition, especially in urban, disadvantaged
settings.
Keywords: Motor skills, Cognitive skills, Behavioral skills, Child, School readiness
1. Introduction
School entry characteristics are important for later academic achievement and attainment (Entwisle, Alexander,
& Olson, 2005). To enhance school success with the primary curriculum, children need to begin kindergarten on
solid ground with essential precursors for reading, writing, and arithmetic (High & Committee on Early
Childhood Adoption, and Dependent Care and Council on School Health, 2008). Thus, characteristics conducive
to learning are a functional vocabulary, informal knowledge of the number line and its properties, and adequate
behavioral self-control characteristics (La Paro & Pianta, 2000).
Clinicians and researchers working in the area of cognitive development have long known of a critical shift in
children’s developmental skills between ages five and seven which helps them process information, use logic to
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understand mathematical and scientific operations, and allows them to pay closer attention and transact with
their environment (Piaget & Inhelder, 1956). These observations are most remarked in Piagetian theory. The
addition of enhancements in cortical regions of the brain which manage executive functions (Kerr & Zelazo,
2004) and emotional regulation (Blair, 2002) produces a child that is “school ready.”
The need for requisite skills at school entry is dramatic for children living in disadvantaged environments
(Pagani et al., 1997; 1999; United Nations Children's Fund, 2005). Young children living in persistent poverty
generally score lower on cognitive tests and general academic performance (NICHD Early Child Care Research
Network, 2005). Such income gradients can be traced to kindergarten (Entwisle et al., 2005; Pagani et al. 1999;
2001). Children from low-income families experience more at-risk parenting and cognitive environments at
home. Parents living in poverty often also report experiencing more stress, family discord and disruption, and
less school success themselves (Pagani et al., 1997). They often rate themselves as having less time to read with
their children and participate in cognitively stimulating activities at home, which results in a less enriching early
childhood environment (Brooks-Gunn, Berlin, & Fuligni, 2000).
School readiness has traditionally defined itself by school entry cognitive and behavioral characteristics which
predict later achievement (La Paro & Pianta, 2000; Vitaro, Brendgen, Larose, & Tremblay, 2005). In the first
comprehensive approach aimed at estimating the impact of school-entry skills on later academic performance in
reading and math, Duncan and colleagues (2007) integrated and analyzed six international longitudinal data sets
while holding constant children’s preschool cognitive ability, behavior, and other important background
characteristics. Their results indicate that early informal math skills, such as knowledge of the number line and
ordinality, were the most powerful predictors of later learning. Early language and reading skills also predicted
later academic performance, although they were relatively less powerful than early math skills. Finally, of all the
behavioral characteristics examined, only attention skills predicted later achievement outcomes.
Much like attention, motor skills have been generally neglected in conceptualizations and investigations of
school readiness, despite the link between motor skills and achievement in the clinical literature (Sandler et al.,
1992; Sortor & Kulp, 2003). During early childhood, cognitive and motor skills recruit common sensory systems
and cortical structures in the brain (Marsh, Gerber, & Peterson, 2008). Brain development occurs through a
sequence of major events, beginning with the formation of the neural tube gestation and intense myelination
during the first two years of life. Anatomical development typically in sensorimotor areas first, subsequently
expanding progressively into dorsal and parietal, superior temporal, and dorsolateral prefrontal cortices. This
expansion, driven by a hierarchical principle (in which development proceeds from undifferentiated to
increasingly differentiated skills) brings with it more specific cognitive and behavioral skills. For example, less
specific infant motricity becomes increasingly defined by its fine, gross, and perceptual motor characteristics by
preschool. Cognitive, fine motor, and attention milestones are interdependent, recruiting each other toward
higher-order cognitive functions, and are mostly driven by the frontal cortices (Marsh et al., 2008), especially
during Piaget’s sensorimotor period (Piaget & Inhelder, 1956). In fact, given the well documented overlapping
recruitment, one could argue that motor skills fall within the important constellation of cognitive skills. Although
it figures most prominently in Piagetian theory, it is also noteworthy that movement plays an important role
among the list of preschool key experiences in the Perry Preschool High/Scope Program (Hohmann & Weikart,
2002) and other preschool enrichment programs that favor cognitive control (Diamond, Barnett, Thomas, &
Munro, 2007; Lillard & Else-Quest, 2006). The results of a study conducted by Schweinhart and colleagues
(1993) indicate that the Perry Preschool Program increased children’s later school success and improved the
quality of their contributions to society as a whole.
Interestingly, motor skills are one important aspect of school readiness not examined in the Duncan et al. (2007)
consortium study. In recent replications and extensions, fine motor skills in kindergarten were found to make
their own unique contribution to reading and math skills and productive classroom learning behavior by the end
of second grade (Pagani, Fitzpatrick, Archambault, & Janosz, 2010; Grissmer, Grimm, Aiyer, Murrah, & Steele,
2010). Although these replication studies establish motor skills as an important element of school readiness,
neither describes how motor skills relate to other key components of school readiness during kindergarten. In
other words, are motor skills independently linked with the key kindergarten elements, such as math, verbal, and
attention skills?
A first step in understanding motricity as a school readiness indicator might be to assess its relationship with
cognitive and behavioral characteristics which have been traditionally used to estimate school readiness, prior to
formal school entry (grade 1). There are good reasons to consider motor skills in the conceptualization and
assessment of school readiness. Foremost is the clinically remarked link between learning and motor skill
problems (Geuze, Jongmans, Schoemaker, & Smits-Engelsman, 2001; Missiuna, Moll, King, & Law, 2007).
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There is also evidence of an overlap between behavioral and motor disorders (Kadesjö & Gillberg, 2001; Kaplan,
Wilson, Dewey, & Crawford, 1998; Harvey & Reid, 2003). It is noteworthy than motor deficits are also
associated with specific language impairments in school-aged children (Hill, 2001; Webster, Majnemer, Platt, &
Shevell, 2005; Gaines & Missiuna, 2006). Previous research has estimated that among children attending regular
elementary school classroom, half will exhibit deficits in motor skills (Gubbay, 1975) such as low sporting
ability, clumsiness, and poor handwriting. This study found a higher incidence of reading difficulties in children
rated as clumsy, which is consistent with more recent clinical studies.
In elementary school, children spend 31% to 60% of their academic day in fine motor activities (McHale &
Cermak, 1992) including handwriting tasks and manipulative tasks with school material or tools (e.g., books,
rulers, scissors, glue, etc.). A clinical study conducted by Sandler and colleagues (1992) compared two groups of
children with developmental and learning problems. One group had writing disorders and another one had no
writing problems. Children with writing disorders showed a tendency toward lower mathematics and verbal
competence and more attention problems compared to children with no writing problems.
In a sample selected from three elementary schools, Tseng & Murray (1994) reported that perceptual-motor
measures of visual motor integration and eye-hand coordination are two significant predictors for handwriting
skills. These perceptual-motor skills were measured from standardized tests, including the Developmental Test of
Visual-Motor Integration (VMI, which comprises 24 geometric forms for children to copy, Beery, 1989) and the
Motor Accuracy Test of the Sensory Integration and Praxis Test (which represents a measure of eye-hand
coordination, Ayres, 1989). In addition to gross and fine motor skills (Grissmer et al., 2010; Pagani et al., 2010),
visual perceptual skill should be regarded to be among the most significant factors related to math and reading
achievement. Sortor and Kulp, 2003 (2003) measured visual perception in 155 children in second through fourth
grade classes from primarily white, middle-class, suburban backgrounds. From a subtest of the VMI (Beery &
Buktenica, 1997), they asked to children to identify each matching form. Their results suggest that children with
poor achievement in math and reading should be tested for deficits in visual perceptual skill.
Motor difficulties are associated to speech and language disorders (Iverson & Thelen, 1999; Gaines & Missiuna,
2006). A recent comprehensive review of the literature of well-designed studies investigating children with
specific language impairment found that 40-90% of such children also exhibit motor impairments (Hill, 2001).
Webster and colleagues (2005) conducted a 4-year follow up of children initially diagnosed at pre-school age
(3-4 years) with developmental language impairment and found a relationship between subsequent motor,
language, and cognitive impairments. More specifically, gross and fine motor were highly correlated with
communication scores. However, only fine motor scores showed a significant correlation with cognitive scores.
Using a convenience sample children who had been identified with speech-language delays as toddlers, Gaines
& Missiuna (2006) found that such children may have significant coordination difficulties and are at risk of
experiencing more problems by kindergarten.
Given the above findings, we can derive several conclusions. First, motor skills represent easily assessed
characteristics of kindergarten readiness. Second, studies showing their association with traditionally assessed
indicators of school readiness originate mainly from clinically-based samples of children with motor difficulties.
Third, many clinical studies use individual assessments of motor skills, which are more expensive for larger
scale studies and real world applications associated with public policy. Studies with larger numbers of students
are able to statistically adjust for possible confounds. Finally, very little research has investigated typically
developing children in regular kindergarten classrooms.
It would be helpful to teachers and school professionals to better understand how the different key elements of
school readiness relate to each other prior to formal school entry. This is especially true for teachers working in
urban, disadvantaged settings where children experience cumulative psychosocial risks. Of course, a true
examination such relationships must control for any other competing or confounding factors which, if not
controlled, could inflate or reduce the concurrent links we wish to examine in kindergarten. For example,
cognitive and behavioral characteristics should be controlled when examining the unique association between
motor skills and other school readiness characteristics. Moreover, apart from individual child characteristics,
family background can represent an important predictor of academic achievement. More specifically, family
configuration and income, and parental education and aspirations are all factors that should be considered as
potential confounds in studies of children’s school readiness and achievement (Al-Yagon, 2003; Pagani et al.,
2010; Vitaro et al., 2005). Hence, the objective of this study is to estimate the concurrent links between motor
skills and cognitive and behavioral characteristics at kindergarten entry, above and beyond other competing
explanations. In light of their common brain recruitment features and overlapping roles in Piagetian theory, we
expect significant associations between motor, cognitive, and behavioral skills above and beyond potential
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confounding child and family characteristics.
2. Method
2.1 Participants
Participating children were from the first cohort of the Montreal Longitudinal Preschool Study (MLEPS, N =
522) who attended kindergarten during the 1998/99 school year (Duncan et al., 2007; Pagani et al., 2010).
Participants were recruited after a multilevel consent process involving school board officials, local school
committees, parents, and teachers. Data were collected from multiple sources, including direct individual
cognitive (verbal and math) assessments of children, and teachers and parents (child academic/social functioning
and family characteristics, respectively).
Seventy-five percent of children in this study lived with both parents. Average total family income was equal or
less than 23,600$ CAN (+16,000$ CAN), which represents the poverty line. Less than half of mothers (46.3%)
had finished high school or high school level trade school. An important proportion of the mothers (66.5%)
hoped that her child would complete university-level studies.
2.2 Measure: Independent Variable
Motor skills. Assessed by teachers at the end of kindergarten, motor skills are divided into three conceptual
scales: (1) Gross Motor (3 items: is well coordinated; moves without running into or tripping over things; ability
to climb stairs, Cronbach alpha = 0.74); (2) Fine Motor (2 items: proficiency at holding a pen, crayons, or a
brush; and ability to manipulate objects, Cronbach alpha = 0.86); (3) Perceptual-motor (8 items: is aware of
writing direction (left to right, top to bottom); is interested in copying teacher’s print; is interested in writing
voluntarily (and not only under the teacher’s direction); is able to write his/her own name; is able to write simple
words; is able to write simple sentences; is able to sort and classify objects by a common characteristics (e.g.,
shape, colour, size); and is able to make 1 to 1 correspondence, Cronbach alpha = 0.71). The items were rated by
teachers on a Likert scale with response options ranging from 1 (never or not true), 2 (sometimes or somewhat
true), to 3 (often or very true). Higher values indicate a higher degree of the factor.
2.3 Measures: Dependent Variables: Cognitive and Behavioral Skills
The Peabody Picture Vocabulary Test (PPVT, Forms A and B, French adaptation: Échelle de vocabulaire en
images Peabody) was assessed at the end of kindergarten. Administered by trained examiners, the French-version
of the PPVT has been standardized by Dunn and colleagues (1993) with a sample of 2,038 French-Canadian
children (from ages 2 to 18) using the same images, procedures, and scoring as in the English version. Reliability
was established using the split-half method with Spearman-Brown correction for each age group and for both
Forms A and B (r = 0.66 and 0.85, respectively). Test-retest reliability of the parallel forms was 0.72 at a one
week interval. As with the original version, correlations with other French vocabulary tests and other intelligence
tests are high (Dunn et al., 1993).
The Number Knowledge Test (NKT, abridged version) was administered at the end of kindergarten. From ages 4
through 6, the NKT represents an individually administered assessment of children's informal knowledge of
numbers and conceptual prerequisites of arithmetic operations (Okamoto & Case, 1996). Administered by
trained examiners, the test for the 5-year-old children measures the following conceptual prerequisites: (1)
knowledge of the number sequence from one to ten; (2) knowledge of the one to one correspondence in which a
sequence is mapped onto objects being counted; (3) understanding the cardinal value of each number; (4)
understanding the generative rule which relates adjacent cardinal values; and (5) understanding that each
successive number represents a set which contains more objects. In a recent psychometric study, the test was
shown to have a higher mathematics factor loading than other available preschool tests (Robinson et al., 1996).
The kindergarten version comprises 19 items that assess more advanced informal number knowledge regarding
knowledge of shapes, colors, counting, and basic concept of addition.
The Social Behavior Questionnaire (SBQ, Pagani et al., 1997; 2001) was completed by teachers at the end of
kindergarten. This measure assesses children's behavioral adjustment. The items on the questionnaire can be
divided into the following conceptual scales: Hyperactive-inattentive (7 items: seems agitated and has difficulty
staying in one place; keeps moving; seems impulsive; has difficulty waiting his/her turn; difficulty staying calm;
inattentive; does not listen attentively, Cronbach alpha = 0.91); Physical Aggression (7 items: physical fight at
least once a day; threatens others; bullies or is cruel toward others; bites, kicks, and hits; gets into many fights; if
accidentally hurt, assumes it was intentional; physically attacks people, Cronbach alpha = 0.72); Emotional
distress (5 items: seems unhappy, sad, or depressed; cries a lot; seems worried or fearful; seems anxious; is
nervous or tense, Cronbach alpha = 0.81); Prosocial behavior (9 items: shows sympathy toward others; tries to
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help someone who is hurt; offers to help clean up somebody else’s accidental mess; tries to make peace if there is
a conflict; offers to help someone perceived as weaker or less able; consoles a crying or upset peer; helps
spontaneously to clean or pick things up; invites others to take part in play; comes to the aid of others, Cronbach
alpha = 0.92); and Classroom Engagement (8 items: plays and works cooperatively with other children at the
level appropriate for age; demonstrates self-control; shows self-confidence; follows directions; completes work
on time; works independently; is capable of making decisions; follows rules and instructions, Cronbach alpha =
0.80). Hyperactive-inattentive and physical aggression represent two kinds of externalized behavior, emotional
distress represents an internalized behavior, and prosocial behavior and classroom engagement represent two
positive behaviors. The SBQ is a good predictor of later psycho-social adjustment and academic failure (Dobkin
et al., 1995). National Longitudinal Study of Children and Youth norms are available from early childhood
through age 12. All SBQ items were rated on a Likert scale with response options ranging from 1 (never or not
true), 2 (sometimes or somewhat true), to 3 (often or very true). Higher values indicate a higher degree of the
factor.
2.4 Measures: Control Variables
Family Characteristics. (1) Maternal education (mothers not finishing high school versus completion, mother
reports); (2) Family configuration (early childhood single-parent family status versus intact, mother reports); (3)
Total family income (sections of 5000 on 13 levels); and (4) Parents’aspirations regarding the child’s future level
of academic attainment.
Child characteristics. Academic and behavioral difficulties are more often observed in boys. Sex, cognitive
characteristics were controlled when examining behavioral outcomes, and behavioral characteristics were
controlled when examining children’s cognitive outcomes. Additionally, children’s other behavioral
characteristics were controlled when looking at a specific behavioral outcome.
2.5 Procedure: Data Analytic Strategy
A series of multiple regressions were computed to examine the relationship between kindergarten motor skills
and concurrently measured cognitive/behavioral skills and modelled as follows:
COG/BEHiK = a1 + ß1 MOTiK + γ1 FAMi + γ2 CHILDi + eit.
In this estimation equation, COG/BEHiK represents performance on the PPVT and NKT individual assessments
and teacher-rated behavior for the individual child during kindergarten. MOTiK refers to kindergarten
teacher-rated motor indices for each child at kindergarten; FAMi and CHILDi are sets of family background and
child characteristics that, if left uncontrolled, are likely to exert enduring influences on children’s characteristics
up to and beyond the end of the kindergarten school year; a1 and eit represent the constant and stochastic
(patterns resulting from random effects) error term, respectively.
Our objective is to reliably estimate the relationship between kindergarten motor skills and other concurrently
measured school readiness skills. For an unbiased estimation of our predictor (MOTiK), we adopt and estimate an
equation that includes measures of FAM and CHILD for the individuali that could theoretically have a direct or
indirect influence on motor skills. We have chosen maternal education, family configuration, total family income,
and parents’ aspirations of their children’s school success as family level control variables. Child level control
variables include sex and concurrent behavior and cognitive skills that might influence estimates of ß1.
3. Results
Table 1 reports descriptive statistics of children’s characteristics which serve as independent and dependent
variables in this study. A correlation matrix of the relationship of cognitive/behavior characteristics and motor
skills is reported in Table 2. All Pearson correlation coefficients were significant yet below to 0.70, indicating
less concern for multicolinearity between variables. Although the results addressing cognitive skills and
behavioral skills as dependent variables are reported in stepwise detail, Tables 3 and 4 only report the results for
the fully controlled model, respectively.
3.1 Cognitive Variables
Verbal Competence and Motor Skills. In the initial (uncontrolled) model, gross motor (β = .12, p < .05) and
perceptual-motor (β = .16, p < .01) factors were significantly related to verbal competence, as measured by
PPVT. When family controls were added, family configuration and income also were significantly associated
with verbal competence (family configuration: β = -.21, p < .001; family income: β =.31, p < .001). Adding the
family controls did not alter the relationship between verbal and motor skills. However, in the fully controlled
model, reported in Table 3, where child factors are added, the relationship between motor skills and verbal
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competence becomes mediated by child characteristics, especially by number knowledge, as measured by NKT
[β =.38, t(13,446) = 8.45; p < .001] and to a lesser extent, by prosocial behavior [β =.11, t(13,446) = 2.30; p
< .05]. The fully controlled model explained 26% of the variance in the verbal competence [F(13, 446) = 12.09;
p < .001], compared with 4% and 13% with the uncontrolled and family controlled model, respectively.
Number Knowledge and Motor Skills. The initial model revealed that fine motor (β = 0.17, p < .01) and
perceptual-motor (β = .22, p < .001) factors were significantly associated with number knowledge, as measured
by NKT. When family controls were added, maternal education, family configuration and income also were
significantly related to number knowledge (maternal education: β = .11, p < .01; family configuration: β = -.09, p
< .05; family income: β = .24, p < .001). Adding family characteristics as controls did not alter the relationship
between number knowledge and motor skills. In the fully controlled model, the relationship between motor skills
and number knowledge remained significant once child characteristics were added to the equation (Table 3) [fine
motor: β = .16, t(13,446) = -2.85; p < .01 and perceptual-motor: β = .14, t(13,446) = -3.09; p < .01]. Verbal
competence was significantly related to number knowledge [β = .36, t(13,446) = 8.45; p< .001].
Hyperactive-inattentive behavior [β = -.16, t(13,446) = 2.81; p < .01] also was significantly associated with
number knowledge; however, to a lesser extent. The fully controlled model explained 31% of the variance in the
number knowledge [F(13, 446) = 15.49; p < .001], compared with 12% and 19% for the uncontrolled) and
family controlled models, respectively.
3.2 Behavioral Variables
Hyperactive-Inattentive Behavior and Motor Skills. The uncontrolled model revealed that fine motor (β = -.34, p
< .001) and perceptual-motor skills (β = -.19, p < .001) were each associated with hyperactive-inattentive
behavior, as measured by SBQ. Then, adding family controls did not alter the relationship between motor skills
and hyperactive-inattentive behavior. However, only fine motor remained a significantly associated once child
characteristics were added to the equation [β = -.23, t(13,446) = 4.76; p < .001] in the fully controlled model
which includes child controls, reported in Table 4,. Specifically, physical aggression, as measured by SBQ,
explained the link between perceptual-motor skills and hyperactive-inattentive behavior [physical aggression: β
= -.42; t(13,446) = 11.48; p < .001]. The other child characteristics, with the exception of verbal competence,
also significantly influenced hyperactive-inattentive behavior; however, to a lesser extent [emotional distress: β
=.12, t(13,446) = 3.32; p < .001; number knowledge: β = -.11, t(13,446) = -2.81; p < .01; sex: β = .11, t(13,446)
= -3.00; p < .01; prosocial behavior: β = -.08, t(13,446) = -2.15; p < .05;]. The fully controlled model explained
50% of the variance in the hyperactive-inattentive behavior [F(13, 446) = 34.71; p < .001], compared with 22%
and 23% for the uncontrolled and family controlled models, respectively.
Physical Aggression and Motor Skills. Initial results revealed that perceptual-motor (β = -.12, p < .05) was
significantly associated with physical aggression behavior, as measured by SBQ. Next, adding family
characteristics as controls did not alter the relationship between motor skills and physical aggression, even
though family configuration also was significantly linked with physical aggression (β = -.10, p < .05). However,
in the fully controlled model, three child characteristics mediated the relationship between physical aggression
and perceptual-motor skills. Hyperactive-inattentive made the largest unique contribution in the link between
physical aggression and perceptual-motor skills [β = .54, t(13,446) =11.48; p < .001]. Specifically, prosocial [β =
-.15, t(13,446) =-3.35; p < .001] and emotional distress [β = .08, t(13,446) =1.99; p < .05] were significantly
associated with physical aggression. The fully controlled model explained 37% of the variance in the physical
aggression [F(13, 446) = 19.94; p < .001], compared with 4% and 6% for the uncontrolled and family controlled
models, respectively.
Emotional Distress and Motor Skills. Gross motor skills were significantly associated (β = -.21, p < .001) with
emotional distress in the initial uncontrolled model. Next, parental aspirations also were significantly related to
emotional distress (β = .18, p < .001). Adding family characteristics as controls did not alter the relationship
between gross motor and child emotional distress. The relationship between gross motor skills and emotional
distress remained significant after adding child characteristics in the fully controlled model [β = -.16, t(13,446) =
2.86; p < .01]. Hyperactive-inattentive, prosocial, and physical aggression also were significantly linked with
emotional distress [hyperactive-inattentive: β = .20, t(13,446) = 3.32; p < .001; prosocial: β = -.13, t(13,446) =
-2.71; p < .01; physical aggression: β =.11, t(13,446) = 1.99; p < .05 ]. The fully controlled model explained 22%
of the variance in the emotional distress behavior [F(13, 446) = 9.41; p < .001], compared with 8% and 12% for
the uncontrolled and family controlled models, respectively.
Prosocial Behavior and Motor Skills. Initially, gross motor (β = .18, p < .001) and perceptual-motor (β = .25, p
< .001) were significantly associated with prosocial behavior. Then, adding family characteristics did not alter
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the relationship between motor skills and prosocial behavior. Once child characteristics were added to the
equation in the fully controlled model, the relationship between prosocial behavior and motor skills remained
significant [gross motor: (β = .19, t(13,446) = -3.49; p < .001); perceptual-motor: (β = .16, t(13,446) = -3.36; p
< .001)]. Many child characteristics were significantly related to prosocial behavior, including: verbal
competence (β = .11, t(13,446) = 2.30; p < .05); sex (β = -.18, t(13,446) = 4.00; p < .001); physical aggression (β
= -.17, t(13,446) = -3.35; p < .001); emotional distress (β = -.12, t(13,446) = -2.71; p < .01); and
hyperactive-inattentive behavior (β = -.12, t(13,446) = -2.15; p < .05). The fully controlled model explained 27%
of the variance in the equation addressing the prosocial variable [F(13, 446) = 12.22; p < .001], compared with
12% for uncontrooled and family control models.
Classroom Engagement and Motor Skills. All motor variables (gross motor: β = .15, p < .01; fine motor: β = .29,
p < .001; perceptual-motor: β = .22, p < .001) were initially significantly associated with the SBQ classroom
engagement scale. Next, family characteristics were not significant as controls and thus did not alter the
relationship between motor skills and classroom engagement. In the fully controlled model, many child
characteristics were significantly related to classroom engagement, including hyperactive-inattentive (β = -.49,
t(14,445) = -12.91; p < .001), emotional distress (β = -.20, t(14,445) = -6.65; p < .001), physical aggression (β =
-.15, t(14,445) = -4.57; p < .001), and prosocial behavior (β = .08, t(14,445) = 2.57; p < .01). The relationship
between classroom engagement behavior and motor skills remained significant once child characteristics were
added to the equation [gross motor: (β = .07, t(14,445) = -2.08; p < .05), fine motor: (β = .10, t(14,445) = -2.56; p
< .01), and perceptual-motor: (β = .08, t(14,445) = -2.54; p < .01)]. The fully controlled model explained 68%
of the variance of the classroom engagement [F(14, 445) = 67.92; p < .001], compared with 27% and 28% for
the uncontrolled and family controlled models, respectively.
4. Discussion
Children enter kindergarten with skills and characteristics that either facilitate or hinder learning. The last forty
years have focused on cognitive and behavioral indicators of school readiness. Well controlled, empirical studies
tell us that cognitive characteristics, especially early math, reading, and attention skills, are especially important
(Duncan et al., 2007). Practitioners in the field suggest that being cooperative and able to sit still are also
pertinent (Hohmann & Weikart, 2002; Entwisle et al., 2005). Nevertheless, many requisite skills for first formal
learning of reading, writing, and arithmetic involve specific motor abilities (Henderson & Pehosk, 1995). This
study sought to examine and describe the concurrent relationship between kindergarten motor skills and such
cognitive and behavioral characteristics.
With respect to cognitive school readiness indicators, early math skills were strongly related to both fine motor
and perceptual-motor abilities. The relationship with fine motor ability is likely influenced by the fact that early
informal knowledge of numbers is generated by manipulating objects and exploring their properties. This
overlap is likely attributable to the fact that much of early and informal knowledge of mathematics involves rules
that require perceptual-motor knowledge in terms of spatial relations (Okamoto & Case, 1996; Cirino, 2011)
such as: (1) relative magnitude; (2) incrementing and decrementing tasks, as when addition or subtraction of one
element to a set alters the number of elements in a set by one unit up or down on the number line; (3) knowledge
of relative position on the number line, which is useful for determining the relative quantities in real world
situations; and (4) the features of objects such as shape, color, dimension, and other perceptual features for
selective grouping, matching, and classification tasks. The perceptual-motor skills evaluated in this study include
being able to sort and classify objects by a common characteristics (e g., shape, colour, size) and understanding
one-to-one object correspondence both overlap with early number knowledge. Moreover, other perceptual-motor
skills measured such as being able to write his/her own name and being able to write simple words require
spatial knowledge and directional orientation (Henderson & Pehoski, 1995). These represent mathemathical
reasoning and knowledge (Cirino, 2011; Newcombe & Huttenlocher, 2000).
The relationship between early math skills and motor skills was so strong that it completely explained the
relationship between motor skills and verbal competence. Its power is not surprising, given that there is much
overlap in brain recruitment of areas responsible for motor, math, and attention skills (Grissmer et al. 2011,
Cirino, 2011). On some significant level, even if the effect size is modest, motor skills develop in tandem with
other school readiness skills that are honed between birth and school entry. If a child falls behind on one
essential skill, it is likely to have a negative influence on other related skills, thus calling for comprehensive
intervention strategies.
This study examined relationship between three different categories of behaviors and motor skills. These
correspond to externalizing, internalizing, and positive classroom behaviors. Some clinical studies suggest a
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relationship (Kaplan et al., 1998; Kadesjö & Gillberg, 2001; Harvey & Reid, 2003). However, these results,
using very controlled models, break new ground by informing us about the relationship between motor and
psychosocial characteristics in typically developing children.
With respect to externalizing behaviors, only hyperactive-inattentive behavior was significantly related to fine
motor skills. Specifically, children showing greater levels of hyperactive-inattentive behavior were more likely to
show deficits with fine motor skills. In fact, this unique association completely accounted for relationship
between fine motor skills and physical aggression. It is noteworthy that previous work suggests that strength and
weakness in attention represent the only behavioral factors that influence later achievement outcomes (Duncan et
al., 2007; Pagani et al., 2011). This link, which reflects the overlap between executive function and motor
circuitry in the brain during early childhood development, suggests the mutual importance of attention to fine
motor skills and assessing both skills when one deficit is noted in a young child. The other deficit may be present
or may become more evident over time. Consequently, focused intervention strategies can be made to
circumvent the co-occurring deficits.
The only result that highlighted gross motor skills is in its association with emotional distress. Children showing
depressed, worried, or anxious classroom behavior showed a greater propensity toward difficulty with gross
motor skills. A study with overweight children reported an inverse association between depressive symptoms and
physical activity in children, reminding us that fatigue and loss of energy represent robust symptoms of
dysphoria across human development (Gray et al., 2008).
All three motor skills were associated with positive classroom behaviors represented by prosocial behavior and
classroom engagement. Helping others and remaining oriented to classroom activities and exhibiting productive
classroom behavior not only involves good cognitive control skills which are governed by executive functions,
they also involve some level of self-regulation in overall motor abilities. Our main conclusion here is that good
motor abilities co-occur with better social skills and task-oriented behaviors in class. It is not unexpected that
both gross motor movement (Hohmann & Weikart, 2002) and fine and perceptual-motor movement (Diamond et
al., 2006; Lillard et al., 2008) figure prominently among the list of key early childhood experiences in
enrichment programs that favour positive development and school readiness.
Surprisingly, our results found more associations between motor skills and positive behaviors, compared to
negative behaviors. Most problem behaviors which involve aggression and oppositional behavior are strongly
associated with inattentive-hyperactive behavior (Dobkin et al., 1995). We controlled for these symptoms when
examining the relationships between behavior and motor skills in this study. The results are quite compelling
because the relationships remained significant despite the adjustments made for family and child factors that
could have confounded this relationship. The most remarkable feature of the results is the robustness of positive
social skills and task oriented behaviors (represented by the prosocial and classroom engagement variables,
respectively). It could also be said that, much like all three specific motor skills examined in this study, positive
behaviors require more effortful control than negative behaviors (Blair & Diamond, 2008) and most learning
tasks and activities involve some degree of effort in motor abilities.
Several observations are worthy of note: Child characteristics such as sex and behavioral skills showed no
influence on the relationship between motor and cognitive skills. However, it seemed important to control for
family characteristics. A possible explanation is that cognitive skills and their correlates, fine motor and
perceptual-motor skills, are often linked with family characteristics. In other words, family characteristics can be
viewed as a support mechanism for learning, especially in low-income settings (Pagani et al., 2001). This is
much in line with findings that parents who provide a stimulating home environment (La Paro & Pianta, 2000)
and participate in children’s learning (Entwisle et al., 2005) tend to promote school success.
Inversely, we noted that, in general, family characteristics do not play a significant role in the relationship
between the motor and behavioral skills, as measured in this study. Yet, child characteristics such as verbal
competence, sex, and behavioral skills must be controlled when examining this relationship. Motor skills might
be inherent to child behavior. This could explain why it is important to control for child characteristics in its
relationship with behavioral more than cognitive characteristics.
We can conclude that, generally, kindergarten entry motor skills are independently related with a number of
important psychosocial characteristics. Both are expected to have an impact on later learning (Entwisle, 2005).
Self-regulation of effortful control (measured by attention in this study), regulated by executive functions,
overlaps with learning fine motor skills, and together provide the prerequisites for later learning. Because
impaired gross motor skills are often accompanied by emotional distress, it likely affects one’s overall physical
disposition toward learning.
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This study is not without limitations. First, we cannot be certain of the true validity of our teacher-rated motor
assessment. For purposes of secondary analysis of already existing longitudinal data, this scale was created by a
clinical content expert from occupational therapy department at the University of Montreal. Its construct and
predictive validity has been established through a principal components analysis which suggests a very good fit
between its items and factors (Pagani et al., 2010). Second, although our work establishes link between motor
skills and cognitive and behavioral characteristics have been traditionally used to estimate school readiness, we
cannot know if motor skills in kindergarten predict later cognitive and behavioral characteristics later. A
longitudinal study would be required to assess the impact of motor development on school readiness. While we
offer a cost-effective alternative for assessing motor skills by using teacher reports, this approach is not as
profound a measure as would be derived using observational data and more rigorous testing of motor skills.
Screening instruments using teacher reports of motor and behavioral skills can flag the need for more in-depth
assessment for children showing atypical development.
These results offer a better understanding of how cognitive and behavioral development co-occur with motor
skills. Preventive intervention treatment of children who show less preparedness in cognitive skills may also
require enrichment of motor skills and vice-versa. Developing a better understanding of how the distinct key
elements of school readiness relate to each other prior to formal school entry will help teachers and school
professionals devise more comprehensive strategies in helping children become prepared for the first grade
transition, especially in urban, disadvantaged settings.
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Table 1. Descriptive statistics of the child characteristics which represent the independent and dependent
variables in the study
N Minimum Maximum Mean (sd)
Cognitive skills
Verbal competence (PPVT) 471 3 133 63.15 (23.2)
Number Knowledge (NKT) 463 0 19 13.07 (4.0)
Behavioral skills
Hyperactive-inattentive 470 9 27 13.25 (4.7)
Physical aggression 470 7 21 8.24 (2.7)
Emotional Distress 468 5 15 6.44 (1.9)
Prosocial behavior 471 9 27 19.80 (5.1)
Classroom engagement 471 12 23 20.67 (2.7)
Motor skills
Gross motor 471 -0.69 2.35 0.08 (0.88)
Fine motor 471 0.71 2.55 1.15 (0.49)
Perceptual motor 471 0.71 2.92 1.21 (0.50)
Table 2. Correlation matrix depicting the relationship between motor skills and cognitive and behavioural
characteristics in kindergarten
Variables VC NK ME FC FI PA Sex HI PAG ED PRO CE GM FM
Gross
motor
0.12** 0.20*** 0.008 -0.09 0.09 0.11** 0.05 -0.28*** -0.09 -0.26*** 0.25*** 0.38***
Fine
motor
0.08 0.29*** 0.04 -0.05 0.04 0.06 -0.28*** -0.44*** -0.16*** -0.22*** 0.22*** 0.47*** 0.60***
Perceptual
motor
0.16*** 0.31*** 0.05 -0.07 0.11* 0.006 -0.29*** -0.35*** -0.16*** -0.16*** 0.30*** 0.38*** 0.27*** 0.45***
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Published by Canadian Center of Science and Education 107
Table 3. Relationship between motor skills and cognitive skills
Fully controlled model
Verbal
competence
Number
knowledge
Independent variable: Motor skills
Gross motor 0.09 0.002
Fine motor 0.10 0.16**
Perceptual motor 0.05 0.14**
Control variables: family characteristics
Maternal education 0.02 0.10**
Family configuration (single-parent)
-0.16***
-0.03
Family income
0.22***
0.12**
Parents’ aspirations 0.02 -0.003
Control variables: child characteristics
Number knowledge
0.38***
Verbal competence 0.36***
Sex (boys) 0.03 0.03
Hyperactive-inattentive -0.08 -0.16**
Physical aggression -0.02 -0.05
Prosocial behavior 0.11* 0.06
Emotional distress -0.04 -0.04
Note. *p < 0.05; **p < 0. 01; ***p < 0.001
Table 4. Relationship between motor skills and behavioral skills
Fully controlled model
Hyperactive
inattentive
Physical
aggression
Emotiona
l distress
Prosocial
behaviour
Classroom
engagement
Independent variable: Motor skills
Gross motor 0.01 -0.07 -0.16** 0.19*** 0.07*
Fine motor -0.23*** -0.07 0.002 0.10 0.10**
Perceptual motor 0.07 0.03 0.01 0.16*** 0.08**
Control variables: family characteristics
Maternal education -0.001 -0.05 -0.03 0.02 0.004
Family configuration (single-parent) -0.03 -0.05 -0.03 -0.04 -0.01
Family income -0.02 -0.05 -0.03 -0.04 0.004
Parents’ aspirations 0.01 -0.02 0.18*** 0.04 -0.01
Control variables: child characteristics
Verbal competence 0.05 0.02 0.04 0.11* -0.01
Number knowledge -0.11** 0.05 0.05 -0.06 -0.01
Sex (boys) 0.11** 0.005 0.01 -0.18*** -0.04
Hyperactive-inattentive 0.54*** 0.20*** -0.12* -0.49***
Physical aggression 0.42*** 0.11* -0.17*** -0.15***
Prosocial behavior -0.08* -0.15*** -0.13** 0.08**
Emotional distress 0.12*** 0.08* -0.12** -0.20***
Note. *p < 0.05; **p < 0. 01; ***p < 0.001
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El objetivo del estudio fue evaluar el desarrollo motor y asociar sus áreas específicas con dispraxias. La muestra fue compuesta por 436 preescolares entre 2 a 5 años. El desarrollo motor fue evaluado en las áreas de Coordinación, Propiocepción y Percepción y los resultados presentados en forma de edad motora y cocientes motores. Los resultados muestran que 57 (13,7%) niños presentaron cociente motor general ? 89, siendo clasificados con dispraxia. La Percepción (orientación espacial y temporal) fue el área con más retrasos (edad motora negativa) y con valores de cociente motor general más bajos. Esta área también presentó correlación positiva con el grupo de riesgo para dispraxia. Estos resultados son relevantes para establecer el perfil de desarrollo motor de los preescolares y así, auxiliar profesores y profesionales en intervenciones y en la prevención de problemas futuros del aprendizaje asociados a los retrasos observados.
... Furthermore, it is revealed that encouraging participation in physical activities can stimulate readiness for school (Becker, Grist, Caudle & Watson, 2018), and that motor skills are a powerful support for school readiness (Grissmer, Grimm, Aiyer, Murrah & Steele, 2010;Pagani & Messier, 2012;Sherry & Draper, 2013). These findings are such as to support the findings made in the current study. ...
... Findings have been mixed, on one hand, with some studies insinuating that cognitive aspects of school readiness (such as basic language and reasoning abilities) are most decisive for later learning (La Paro and Pianta, 2000;Duncan et al., 2007). On the other hand, studies have shown that a broader constellation of early child capacities, including non-cognitive abilities such as motor skills and social competence, is predictive of later school achievement (Denham, 2006;Pagani et al., 2010;Pagani and Messier, 2012). However divergent, most findings corroborate the notion of school readiness as constituting the cornerstone of a child's positive school adaptation. ...
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A promising approach for studying school readiness involves a person-centered approach, aimed at exploring how functioning in diverse developmental domains conjointly affects children’s school outcomes. Currently, however, a systematic understanding lacks of how motor skills, in conjunction with other school readiness skills, affect a child’s school outcomes. Additionally, little is known about longitudinal associations of school readiness with non-academic (e.g., socioemotional) school outcomes. Therefore, we examined the school readiness skills of a sample of Dutch children (N = 91) with a mean age of 3 years and 4 months (46% girls). We used a multi-informant test battery to assess children’s school readiness in terms of executive functions (EFs), language and emergent literacy, motor skills, and socioemotional behavior. During the spring term of a child’s first grade year, we collected academic and non-academic (i.e., EFs, motor skills, socioemotional- and classroom behavior, and creative thinking) school outcomes. A latent profile analysis revealed four distinct profiles. Children in the “Parent Positive” (29%) profile were rated positively by their parents, and performed variably on motor and language/emergent literacy skills tests. The second profile–“Multiple Strengths” (13%)–consisted of children showing strengths in multiple domains, especially with respect to motor skills. Children from the third profile–“Average Performers” (50%)–did not show any distinct strengths or weaknesses, rather displayed school readiness skill levels close to, or just below the sample mean. Finally, the “Parental Concern” (8%) profile was characterized by high levels of parental concerns, while displaying slightly above average performance on specific motor and language skills. Motor skills clearly distinguished between profiles, next to parent-rated EFs and socioemotional behavior, and to a lesser extent emergent literacy skills. School readiness profiles were found to differ in mean scores on first grade academic achievement, parent- and teacher-rated EFs, motor skills, parent-rated socioemotional functioning, and pre-requisite learning skills. The pattern of mean differences was complex, suggesting that profiles could not be ranked from low to high in terms of school outcomes. Longitudinal studies are needed to disentangle the interaction between emerging school readiness of the child and the surrounding context.
... Other studies have also demonstrated an association between motor skills and academic achievement [12,[17][18][19], as well as with cognitive abilities [20]. Additionally, gross motor skills have been longitudinally associated with social behaviour [21], self-control, cooperation and a decrease in hyperactivity in young children [22], while fine motor skills have been associated with academic achievement [23,24], attention [25] and executive function [26]. Similarly, intervention studies of preschool children show that school PA promotion [27] and activity breaks [28] can increase educational scores. ...
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The benefits of being physically active, possessing good motor skills and being school-ready are well documented in early years. Nevertheless, the association between physical activity and motor skills with school readiness remains unknown. Therefore, the aim of this cross-sectional study was to explore the relationship between these variables. We collected data on 326 four to five-year-old children from the northeast of England. Children’s PA (ActiGraph GT1M accelerometers), motor skills (MABC-2 and the locomotor section of the TGMD-2) and school readiness (EYFSP) were measured, and associations between these variables were examined. This study found that, on average, children engaged in more MVPA (99.6 min/day) and less sedentary behaviour (261 min/day) than documented in previous research. Motor-skill scores were consistent with existing literature in early years. A higher percentage of children in the sample (79.6%) achieved school readiness than the average for England. Regression analyses found that motor-skill variables and sedentary behaviour were significantly predictive of school readiness, whereas physical activity was not. Motor skills and sedentary behaviour significantly predict school readiness. Therefore, promoting motor skills and developmentally appropriate sedentary behaviour activities may increase the number of children achieving school readiness.
... This may have a direct effect, whereby fine motor coordination supports the use of mathematical manipulations often applied for teaching mathematics to pre-school children, but it may also have an indirect effect, whereby motor coordination skills improve the function of realization, which is correlated with fitness for school and pre-academic skills [96]. It is therefore of utmost importance that children who have shown difficulties in mastering motor skills during kindergarten are fully supported by teachers in order to adequately prepare for first grade [97]. ...
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Motor skill competence of children is one of the important predictors of health because if a child is physically active during early childhood, the possibility of occurrence of many chronic diseases in adulthood will be reduced. The aim of this study was to systematically review the studies conducted in healthy children using the shorter form of the Bruininks-Oseretsky (BOT-2) and to determine the applicability in cross-sectional studies and pre-post designs. The search and analysis of the studies were done in accordance with the PRISMA guidelines. An electronic databases search (Google Scholar, PubMed, Mendeley, Science Direct, and Scopus) yielded 250 relevant studies conducted from 2011 to 2020. A total of 21 studies were included in quantitative synthesis, with a total of 3893 participants, both male and female. Through this study, the BOT-2 test proved its broad applicability, so it can be concluded that this test can be used to improve motor proficiency in a healthy population of children. Hence, it is necessary to invest a lot of time during the implementation of various programs so that children would adequately develop their basic motor skills so they broaden their own repertoire of movements.
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The difficulty in maintaining attention can interfere with the acquisition of critical academic skills. Recently, researchers have used embodied and game-based learning to support skill acquisition for children with learning difficulties. In this context, robots can be an interesting asset to foster engagement and investigate game dynamics. However, it is still an open question of how to develop adaptive learning environments for children with learning difficulties. Before one can provide effective adaptation, a first step is needed to understand the differentiating behaviors during the activity for children with attention difficulties. Three such differentiating behaviors are how a child divides his or her attention during the learning activity, the child’s level of cognitive load, and the child’s physiological fatigue, which are the focus of our study Using a robot assisted, gamified activity, we conducted a user study with 18 children having difficulty in maintaining attention. Using process mining techniques and eye-tracking data, we found the importance of integrating the autonomous robots into the attention patterns to successfully complete a game and the influence their behaviors can have on the participant’s attention. This importance was supported by the cognitive load of participants decreasing the more they focused on the autonomous robots in successful games. This work contributes to the understanding of children’s behaviors during tangible game-based activities and can be used to build effective adaptation for children with attention difficulties.
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Aim: To examine whether executive functions, and gross motor skills were predictors for school performance in children with DCD, with risk for DCD (r-DCD), and with typical development (TD). Methods: Participants were 63 children with DCD (Mage = 8.70, SDage = .64), 31 children with r-DCD (Mage = 8.90, SDage = 0.74), and 63 typical development children (Mage = 8.74, SDage = .63). Wechsler Abbreviated Scale of Intelligence, Movement Assessment Battery for Children-2, Test of Gross Motor Development-3, Oral Word Span in Sentences, Odd-One-Out, Go/No-Go, Hayling Test, Trail Making Test, Five Digits Test, and the Test of School Performance-II were utilized. Results: In DCD, processing speed (β = −.42, p = .005), and auditory-motor inhibition (β = −.36, p = .009), and auditory-verbal inhibition (β = −.38, p = .023) predicted math performance; and auditory-motor (β = −.40, p = .38) and visuospatial working memory (β = −.33 p = .011) predicted writing performance. In r-DCD, auditory-motor (β = − .67; p = .002) and visual-motor (β = −.40; p = .040) inhibition predicted math performance; visual-motor inhibition predicted writing performance (β = −.47; p = .015). Conclusion: Lower inhibitory control and visuospatial working memory scores affect children with DCD and r-DCD’ school performance.
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It has been found that motor ability and motor play in early childhood are associated with the development of social skills. However, the relationships among these three factors have not yet been clarified. In this study dealt with motor skills, cooperative physical play, and social skills in early childhood and examined whether motor skills or cooperative physical play was more predictive of social skills at age 6. A short‒term longitudinal study of 31 kindergarteners (15 male and 16 female) in Chiba Prefecture was conducted, including children between the ages of 5 and 6 years. Motor ability was measured and motor play was observed at 5 years of age, and social skills were assessed at 6 years of age. The results of this study showed that children with high motor ability frequently engage in motor play during the year, but do not necessarily participate actively in cooperative physical play with their peers. Furthermore, participation in cooperative physical play during at 5 years of age, rather than high motor ability at 5 years of age, predicts social skills at 6 years of age. Thus, the results of this study indicate that active participation in cooperative physical play in daily life is important for the development of social skills in young children.
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We examine the embodiment of one foundational aspect of human cognition, language, through its bodily association with the gestures that accompany its expression in speech. Gesture is a universal feature of human communication. Gestures are produced by all speakers in every culture (although the extent and typology of gesturing may differ). They are tightly timed with speech (McNeill, 1992). Gestures convey important communicative information to the listener, but even blind speakers gesture while talking to blind listeners (Iverson and Goldin-Meadow, 1998), so the mutual co-occurrence of speech and gesture reflects a deep association between the two modes that transcends the intentions of the speaker to communicate. Indeed, we believe that this linkage of the vocal expression of language and the arm movements produced with it are a manifestation of the embodiment of thought: that human mental activities arise through bodily interactions with the world and remain linked with them throughout the lifespan. In particular, we propose that speech and gesture have their developmental origins in early hand-mouth linkages, such that as oral activities become gradually used for meaningful speech, these linkages are maintained and strengthened. Both hand and mouth are tightly coupled in the mutual cognitive activity of language. In short, it is the initial sensorimotor linkages of these systems that form the bases for their later cognitive interdependence.
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