Perceptual Motor training Approach versus
Computer-Assisted Practice on perceptual function in
children with slow hand writing speed
Ruby Suk Yee, Liu; Clare Tin Yan, Shum; Charis Chi Hang, Wong
(Occupational Therapists of Hong Kong Sheng Kung Hui Welfare Council)
Handwriting proficiency is essential for students to achieve an acceptable
amount of work in school and meet curriculum standards Elementary
school children typically spend up to 50% of the school day engaged in
paper-and-pencil tasks (McHale & Cermak, 1992). Although a traditional
instructional approach is sufficient for many children to become competent
handwriters, handwriting difficulties are common among children in regular
and special education classes. (Bergman & McLaugh-lin, 1988).
Remediation of handwriting difficulties is an important areas of school
occupational therapy. (Tseng & Chow, 1999).
Competent hhandwriting is a complex perceptual-motor skill dependent
upon the maturation and integration of several cognitive, perceptual and motor
skills, and is developed through instruction (Hamstra-Bletz and Blote, 1993;
Maeland, 1992). Fluent writing is produced by an integrated pattern of
coordinated movements subject to visual monitoring and sensorimotor
feedback (Sovik & Arntzen, 1991). In support of this range of requirements,
visual motor integration was reported to be the best predictor of legibility in
American, Norwegian (Sovik, 1971) and Chinese children (Tseng& Murray,
1994). Visual perceptual skill, including visual spatial perception, visual size
discrimination, visual retrieval and left-right orientation, enable children to
distinguish visually among graphic forms and to judge their correctness. (Sovik,
1975; Thomassen & Teulings, 1983). Fine motor skills are also essential
because accurately formed letters can only be produced by proper timing and
force control of coordinated arm, hand and finger movements (Alston & Taylor,
1987; Thomassen & Teulings, 1983). (will explain why we chose Reduced
Motor Perception subtests)
Handwriting can be deficient in terms of legibility or speed. Children with
dyslexia were found to write more slowly than children without reading
disabilities. (Lam, 1999). Common handwriting problems such as incorrect
letter formation, poor alignment, reversals, uneven size of letters, irregular
spacing between letters and words, and slow motor speed sually arise from
deficiency in visual perceptual skills (Alston & Taylor, 1987; Johnson & Carlisle,
1996). Most studies have focused on the relationship between illegibility and
various visual perception skills, fine motor skills and visual motor integration.
(Cornhill & Case-Smith, 1996; Johnson & Carlisle, 1996; Maeland, 1992;
Tseng & Murray, 1994).
Chinese children with dyslexia report that the majority have difficulties in
the visual processing required to interpret the images of Chinese script, and in
the process of relating sounds to words, phonology. (Tan, 2009). The
majority of Chinese dyslexic children have rapid naming and orthographic
deficits, and a relatively small proportion have phonological deficits (Ho, 2004).
This finding suggests that orthographic-related difficulties may be central to
Chinese developmental dyslexia. Visual perception and cognitive skills also
affect handwriting speed (Martlew, 1992). Intervention for slow hand writers
should focus on facilitating visual processing, including memory and visual
motor integration, rather than the fine motor training that is often emphasized
in occupational therapy programs. (Tseng & Chow, 1999).
Computer assisted practice improves cognitive and perceptual skills,
hand-eye coordination and social skills. (Jones, 1987). The process of
hand-eye coordination occurs when the eyes receive information and sends it
to the brain which uses it to coordinate with the hands to perform an activity.
Hand-eye coordination skills can be improved by practicing and exercising.
Video games can have advantageous effects, improving gamers' skillfulness
and their ability to solve problems. Most research identifies how perceptual
motor skills affect handwriting speed. Perceptual Motor Training and
Computer-Assisted Practice are linked to perceptual motor function in children
with slow hand writing speed, but few studies have compared the effects of
these interventions in the same study. In this research, we compared the
effect of perceptual Motor Training versus Computer-Assisted Practice on
perceptual motor function in children with slow hand writing speed.
This study was a quasi-experimental clinical with a pretest-posttest
design. 26 children aged 7-8 were selected by convenience sampling from
four mainstream primary schools in Hong Kong. Participants were defined as
slow hand writers from results on Tseng’s Chinese Handwriting Speed Test
(CHAST; Tseng & Hsueh, 1997). Children who have neurological problems,
attention deficit disorder, attention deficit hyperactivity disorder, orthopaedic
problems and IQ below 90 were excluded.
The DTVP-2 is a battery of eight subtests that measure different but
interrelated visual perceptual and visual-motor abilities. The battery, which is
designed for use with children aged 4-10 through 10, has empirically
established reliability and validity. The DTVP-2 is the latest version of Frostig et
al.’s (1961, 1966) and Frostig et al.’s (1964) popular milestone test battery. The
battery can be administered by psychologists, occupational therapists,
educators, diagnosticians, and others who are interested in examining the
visual perceptual status of children. The subtests of the DTVP-2 were built to
conform with the visual perception constructs espoused by Frostig et al. (1961,
1964, & 1966). Each of the eight subtests of the DTVP-2 measures a type of
visual perceptual ability that is easily classified as position in space, form
constancy, spatial relations, or figure-ground. In addition, each subtest is
classified as either motor-reduced or motor-enhanced. In our study, we chose
Subtests 2, 4, 6 and 8 which are the motor-reduced subtests:
Subtest 2 (position in space): Children are shown a stimulus figure and asked
to select the exact figure from a series of similar but different figures. This is
strictly a matching task.
Subtest 4 (figure-ground): Children are shown stimulus figures and asked to
find as many of the figures as they can on a page where the figures are hidden
in a complex, confusing background.
Subtest 6 (visual closure): Children are shown a stimulus figure and asked to
select the exact figure from a series of figures that have been incompletely
drawn. In order to complete the match, children have to mentally supply the
missing parts of the figures in the series.
Subtest 8 (form constancy): Children are shown a stimulus figure and asked to
find it in a series of figures. In the series, the targeted figure will have a
different size, position, and/or shade, and it may be hidden in a distracting
The study had three phases. All phases were administered by an
Occupational Therapist (OT). In the first phase, after parents’ written consent
for participating in the study, all participants attended assessment sessions on
an individual basis to obtain baseline measurement of their DTVP-2 scores.
The motor-reduced subtests in the aspects of visual position in space, form
constancy, figure-ground and visual closure were measured. In the second
phase, the schools were evenly assigned to either Perceptual Motor Training
(PMT) or Computer-Assisted Practice (CAP). There were 16 children in PMT
group and 10 children in CAP group. Participants who were allocated to PMT
then completed one hour group training sessions led by a registered OT for 8
weeks. The training included various activity games and writing activities
such as stacking cubes and puzzles, copying shapes and rhythmic body
exercises. Participants allocated to CAP completed one hour training
sessions with a personal computer on an individual basis under the
supervision of a program assistant for 8 weeks. The training included web
games and offered visual feedback for visual perception such as figure-ground
and visual closure.
The outcome of interest was participants' DTVP-2 scores, assessed at
baseline and post intervention. Using an Independent Samples t test with an
alpha level set at p< 0.05, reporting t values, and 95% Confidence Intervals,
the researchers compared the statistical and clinical significance of differences
in DTVP-2 scores between participants receiving PMT or CAP.
Between group differences in DTVP-2 scores
The mean of the Perceptual Motor Training group (PMT) (n=16) scored
higher than the Computer-Assisted Practice group (CAP) (n=10) on all
measures. Results shown that the mean score for PMT groups for four
subtests of DTVP respectively is higher than the CAP group. (see Table 1).
Independent sample t test revealed a significant difference between the two
groups for the subtests of position in space, figure ground and form constancy.
From the data, it is illustrated that there is a finding of significance at the 0.043,
which is less than 0.05 (p< 0.05). Significant difference between two groups is
indicated. (see Table 2).
Within group differences in DTVP-2 scores
Analysis of variance (independent sample t test) was performed on the
visual perception which includes four domains: position in space, figure ground,
visual closure and form constancy. Table 1 reports means and standard
deviations for the PMT groups and CAP groups on each of the pretest-posttest
Position in Space
There are differences between pretest and posttest scores in the PMT
and CAP groups. Improvement in mean scores for both groups are indicated.
The mean score of PMT equals to 19.25 which is higher than CAP (mean=8.1).
Also, it revealed a significant difference between two groups, p=0.002
Differences between pretest and posttest scores in the PMT and CAP
groups. Improvement in mean scores for both groups are indicated. The mean
score of PMT equals to 18.43 which is higher than CAP (mean=9.1). Also, it
revealed a significant difference between two groups, p=0.12
Pretest and posttest scores in the PMT and CAP groups shows
differences. Improvement in mean scores for both groups are indicated. The
mean score of PMT equals to 10.43 which is higher than CAP (mean=7.4).
However, it does not revealed a significant difference between two groups,
p=0.135, which is greater than 0.005
There are differences between pretest and posttest scores in the PMT
and CAP groups. Improvement in mean scores for both groups are indicated.
The mean score of PMT equals to 12.81 which is higher than CAP (mean=8.5).
It revealed a significant difference between two groups, p=0.022
Fig. 1 Pre-and post training mean scores of Perceptual Motor Training group
mean score 12
p o sitio n fig u r e v isu al fo rm
in sp ace ground clo su r e co n stan cy
Fig.2 Pre-and post training mean scores of Computer Assisted Practice group
mean score 8
position figure visual form
in space ground closure constancy
Independent t test
Levene’s Test for t-test for Equality of Means
Equality of Variances
F Sig. t df. sig.(2 mean Std.error Interval of the
tailed) differenc differenc diffrence
e e lower uppe
Equal variance 3.887 0.043 4.040 .116 .045 .396 .098 4.819E02 .2571
4.084 2.53 0.45 .382 .097 4.816E01 .2381
Equal variance not
Table 1. Means, standard deviation and results of DTVP tests of computer assisted
practice (CAP) and Perceptual Motor training(PMT) group
TRAINING N Mean Std. Std. Error
Subtest 2 (Pre-test) CAP 10 7.9000 2.9981 .981
Position in space PMT 16 8.1250 1.7078 .4270
Subtest 2 (Post-test) CAP 10 8.1000 3.8715 1.2243
Position in space PMT 16 19.2500 4.6458 8.2001.
Subtest 4 (Pre-test) CAP 10 9.0000 3.1972 1.0111
Figure-ground PMT 16 6.5000 2.8752 .7188
Subtest 4 (Post-test) CAP 10 9.1000 3.1218 1.3034
Figure-ground PMT 16 18.4375 4.9821 8.1073
Subtest 6 (Pre-test) CAP 10 7.0000 4.6667 1.4757
Visual closure PMT 16 8.3750 3.5000 .8750
Subtest 6 (Post-test) CAP 10 7.4000 4.8351 1.5290
Visual closure PMT 16 10.437 3.3260 .8315
Subtest 8 (Pre-test) CAP 10 9.7000 1.8886 .5972
Form constancy PMT 16 11.687 3.4587 .8647
Subtest 8 (Post-test) CAP 10 10.1000 3.5668 1.1279
Form constancy PMT 16 12.8125 5.2908 7.1287
Total tests (Pre-test) CAP 10 3.29 1.0328 .3266
PMT 16 2.1679 1.8165 .2041
Total Test (Post-test) CAP 10 3.31 1.8056 .4761
PMT 16 3.996 2.7746 8.1936
Table 2. Significance difference between computer assisted practice (CAP) and
Perceptual Motor training(PMT) group
Independent t test
t-test for Equality of Means
sig.(2 mean Std.error Interval of the
F Sig. t df tailed differenc differenc difference
) e e
Subtest Equal variance .39 2.863
4.589 .025 29 .037 -.8727 .9733 1.1180
2(Pre-test) assumed 7 4
Position in Equal variance .24 17.71 3.035
space .007 -.8727 1.0280 1.2896
not assumed 9 8 0
Equal variance 1.1 5.225
Subtest 6.338 .002 29 .047 7.1636 6.0575 19.5526
assumed 83 4
Position in space Equal variance .87 10.12 11.13
.004 7.1636 8.2249 25.4601
not assumed 1 2 29
Subtest Equal variance 1.7
5.254 .029 29 .090 2.0773 1.1845 3452 4.4998
4(Pre-test) assumed 54
Figure ground Equal variance 1.7 20.64
.035 2.0773 1.1861 3921 4.5466
not assumed 51 0
Subtest4(Post-t Equal variance 1.7 2.052
est) 8.521 .012 29 .009 10.2727 6.0263 22.5979
assumed 05 5
Equal variance 1.2 10.19 7.832
.024 10.2727 8.1468 28.3779
not assumed 61 6 4
Subtest Equal variance 1.6 5.489
7.355 .062 29 .073 -2.4136 1.5039 .6623
6(Pre-test) assumed 05 5
Visual Closure Equal variance 1.5 17.13 5.803
.022 -2.4136 1.6078 .9765
not assumed 01 1 8
Equal variance 1.0 4.600
6(Post-test) 8.652 .135 28 .045 -1.6000 1.4646 1.4001
assumed 92 1
Equal variance .99 14.42 5.033
.067 -1.6000 1.6052 1.8333
not assumed 7 5 3
Subtest Equal variance 1.7 4.137
8(Pre-test) 8.544 .0387 29 .034 -1.9318 1.0785 .2740
assumed 91 6
Equal variance 2.0 28.96 3.814 -4.9188
Constancy .045 -1.9318 .9205
not assumed 99 7 4 E-02
Equal variance .84 7.224
Subtest 8.353 .022 29 .002 5.1182 6.0350 17.4612
assumed 8 9
Form Constancy Equal variance .62 10.16 13.05
.015 5.1182 8.1739 23.2909
not assumed 6 4 45
Table 3. Significance difference between computer assisted practice (CAP) and
Perceptual Motor training (PMT) group
This study showed that PMT approach resulted in significant improvement
in various domains of visual perception such as position in space, figure
ground and form constancy Participants in PMT groups were engaged in
various activities which required children to perform bilateral body coordination
and eye hand coordination tasks. These activities provided an integrated
pattern of coordinated movements subjected to visual monitoring and
sensorimotor feedback, rather than merely visual feedbacks from the computer
monitor. To achieve functional competence for slow handwriters, it has been
investigated in connection with visual spatial perception, visual retrieval,
left-right orientation and visual motor integration. (Sovik, 1975; Thomassen,
In this study, the PMT group had a higher within group mean on visual
closure but not statistically significant. This can be explained by the similarity
of the training contents between the two groups. Participants of PMT
received paper and pencil exercises which were similar with the web games.
The findings that handwriting speed was strongly correlated with age for
both PMT and CAP slow speed writers is consistent with previous studies.
(Hanmstra-Bletz & Blote, 1990; Sovik, 1975; Tseng & Hsueh, 1997; Ziviani &
Elkins, 1984). Increased handwriting speed follows naturally from the
empirically observed fact that coordinated handwriting movements improve
with age and schooling. (Meulenbroek & van Galen, 1986; Sovik, 1993)
Limitation of the study
The preliminary result for the slow handwriters were mainly based on the
primary school students drawn from four primary schools. Future studies
may need to expand the sample size to incorporate participants from different
primary schools in Hong Kong in order to be reflective of the entire population
of primary school students.
Due to the fixed the school schedule, for example, busy study week,
examination period and extra-curriculum activities, the frequency for the
application of the training sessions was inconsistent. The discrepancy of the
intensity of training between PMT and CAP groups might affect the
effectiveness of the visual perceptual training.
Some of the participants had poor sustained attention in both PMT and
CAP group training. Although children with attention deficits or attention
deficit hyperactivity disorder were intentionally excluded from the study, those
pending for diagnosing might still have been included in the training, which
might affect the outcomes of the study.
Preliminary findings in this study demonstrated that the PMT approach
was more effective than CAP approach in improving perception function of
slow handwriters. Our findings suggested that visual perception activities,
such as bilateral body coordination and eye hand coordination exercises, had
a positive impact for improving the perception motor skills of slow handwriters.
Future studies to examine the effectiveness on improving the handwriting
speed and legibility in slow-handwriters is suggested.
We thank those participating teachers and children from SKH St.
Michael’s Primary School, SKH Wing Chun Primary School, SKH Mung Yan
Primary School and SKH Yat Sau Primary School for their generous support in
recruiting participants and providing resources.
Alston, J., & Taylor, J. (1987). Handwriting: Theory, research, and practice.
New York: Croom Helm.
Bergman, K.E., & McLaughlin, T.F. (1988). Remediation handwriting
difficulties with learning disabled students: A review. B.C. Journal of Special
CCC Lam. (1999). Developmental Dyslexia and Other Specific Learning
Disabilities. The State of Practice: International and Hong Kong Perspectives.
Journal of Hong Kong Paediatric, 4, 145-150
Cornhill, H., & case-Smith, J. (1996). Factors that relate to good and poor
handwriting. American Journal of Occupational Therapy, 50, 732-739.
Hammstra-Bletz,L., & Blote, A. W. (1993). A longitudinal study on dysgraphic
handwriting in primary school. Journal of Learning Disabilities, 26, 689-699
Ho S.H., Wong W.L. & Chan W.S. (1999). The use of Orthographic Analogies
in Learning to Read Chinese. Journal of Child Psychology Psychiatry., 40,
Juan E. & Maria R.O. (2003). Do the Effects of Computer-Assisted Practice
Differ for Children with Reading Disabilities With and Without IQ-Achievement
Discrepancy? Journal of Learning Disabilities, 36, 34-47
Martlew, M. (1992). Handwriting and spelling: Dyslexic children’s abilities
compared with children of the same chronological age and younger children of
the same spelling level. British Journal of Educational Psychology, 62,
Mchale, K.& Cermak, S. (1992). Fine motor activities in elementary school:
Preliminary findings and provisional implications for children with fine motor
problems. American Journal of Occupational Therapy, 46, 898-903.
Sovik, N., Arntzen, O. (1991). A developmental study of the relation between
the movement patterns in letter combinations(words) and writin. In J. Wann,
A.M.Wing, & N.Sovik (Eds.). Development of graphic skills: Research
perspective and educational implications (pp.77-89). New York: Academic
Sovik, N. (1975). Developmental cybernetics of handwriting and graphic
behavior. Olso, Norway: Universitetsforlaget.
Sovik, N., Arntzen, O., & Teulings, H.L. (1982). Interactions among overt
process parameters in handwriting motion and related graphic production.
Journal of Human Movement Studies, 8, 102-122.
Tseng M.E., & Susanna M.K.(1999). Perceptual-Motor Function of School-Age
Children with Slow Handwriting speed. The American Journal of Occupational
Therapy, 54, 83-88
Tseng, M.H.& Hsueh,I.P.(1997). Performance of school-aged children on a
Chinese Handwriting Speed Test. Occupational Therapy International, 4, 294