EBP Question: Do computer programs affect the written work of children with learning disabilities?
Table 5 Author: Chasity Asher
Author,
Year
Study
Objectives
Study
Level of
Design/Participants evidence
Sample Size
Interventions &
Outcome Measures
Summary of
Results
Borgh, K. &
Dickson, P.
W. (1992).
Hypothesize
that stories
produced in
spoken
feedback
condition
would be
longer, edited
more, and of
higher quality
than written
without spoken
feedback.
Also
hypothesized
that spoken
feedback
would be
related to
increased
motivation and
audience
awareness.
Cross-over design
with two
experimental
groups.
Randomized
sample from 2nd
and 5th grade
classrooms from
two schools.
48 students
(24 female,
24 male and
24 2nd grade,
24, 5th
grade)
At each school, 12
students (1/2 2nd
grade & ½ 5th
grade) wrote two
stories under
spoken feedback
condition & then
two stories under
nonspoken
condition. The
other 12 students
wrote two stories
under nonspoken
condition, and then
two under spoken
feedback condition.
Interview
completed
afterwards.
Outcome
Measure: Length,
editing, quality,
motivation, and
audience awareness
Length measures:
Means for all
length measures
tended to be
higher for stories
written under
spoken feedback.
Editing: More
editing found at
sentence level
with spoken
feedback, but
more editing at
story level with
nonspoken.
Quality: No
statistically
significant effect.
Audience
Awareness: No
significant effect.
II
Study
Limitatio
ns
Small
sample
size
limited to
only two
schools
and two
grades.
Dalton, D.
W. &
Hannafin,
M. J.
(1987).
Study the
effects of a
year-long word
processing
program on
holistic writing
skills.
A 2x2 completely
crossed treatment
by-achievement
factorial design.
Nonrandomization
drawing from four
remedial language
arts courses, which
were placed in
courses based on
below-average
scores on
Comprehensive
Test of Basic
Skills.
II
80 seventh
grade
students
Students were split
into two groups
using different
programs: Word
processing
treatment (WPT)
and Conventional
writing program
(CWP), with both
higher and lower
achievers. WPT
completed written
assignments on an
Apple equipped
with FreeWriter
and CWP used pen
and pencil. Both
groups completed
two weekly writing
exercises and four
additional major
papers. Lastly
completed a writing
sample end of
research.
Outcome
measures: Posttest
writing sample
evaluated by
“blind” examiners
High achievers
essay scores were
significantly
higher than low
achievers. Mean
scores of WPT
group were
significantly
higher than the
CWP group. Low
achieving learners
benefited more
from WPT than
high achieving
learners.
Interview
suggested that
word processor
improves revision
in written
assignments.
Not
randomiz
ed and
limited to
certain
age
group.
Goldberg,
A., Russell,
M., & Cook,
A. (2003).
A study on the
impact of
computer
processing on
K-12 students’
writing.
Meta analysis
including 26
studies between
1992-2002, K-12
students.
I
according to
structure and
organization,
correct usage of
parts of speech,
punctuation,
capitalization, and
spelling subtracting
points from 100 for
mistakes to find
scores. Interviews
also conducted.
26 studies,
From review of
approximatel literature, a coding
y 1320
system was used to
students.
examine results.
Coding included:
publication type,
research
methodology,
student
characteristics,
technology related
factors, writing
environment
factors,
instructional
support factors, and
outcome measures.
Outcome
measures: Quality,
Quantity: Across
14 studies,
students who
write with word
processors tend to
produce longer
passages than
students who
write with paper
and pencil.
Quality: 15
studies indicate
that students who
write with word
processor tend to
produce higher
quality passages
than students who
write with pencil
HandleyMore, D.,
Deitz, J.,
Billingsley,
F. F., &
Coggins, T.
E. (2003).
Investigation
of whether
occupational
therapy
intervention
that focused on
teaching
children to use
word
processing,
either alone or
with word
prediction, was
effective in
improving the
written
communication
skills of
children with
learning
Single-subject
alternating
treatment design.
Participants were
identified by OT,
school pathologist,
or special
education teacher.
They were
diagnosed with a
learning disability
and in grades 4 and
5.
IV
3 students
quantity, and
revision.
and paper.
Revision: 6
studies show that
students who
write with word
processor made
more revisions
than those who
write with pencil
and paper.
Prior to phase one:
Each student preselected 36 pictures
they could write
about.
Phase
One/Baseline:
completed 6
handwritten stories.
Prior to phase two
keyboard training.
Phase two:
Completed 18-29
stories using
handwriting, word
processing, and
word processing
with word
prediction.
Outcome
Two children
demonstrated
clear
improvement in
legibility with use
of word processor
alone or with
word prediction.
These same
students also
demonstrated
clear
improvements in
spelling using
word prediction.
Rate of writing
was best for two
children using
handwriting,
however quantity
Small
sample
size, nonrandomiz
ation in
participan
ts. Study
also
restricted
to one
school
district.
disabilities and
handwriting
problems.
MacArthur,
C. A. &
Cavalier, A.
R. (2004).
Investigate the
feasibility and
validity of
dictation using
speech
recognition
software and
dictation to a
scribe as
accommodatio
n for test
involving
extended
writing for
children with
and without
learning
disabilities.
Experimental
design, repeated
measures group
design
High school
students with and
without Learning
Disabilities.
II
measures:
Legibility, spelling,
and total amount
written.
31 high
In initial 8 sessions,
school
students received
students: 21 training on speech
students with recognition
LD and 10
program and essay
students
writing. Students
without LD. wrote three essays
on certain topics in
three sessions using
all three conditions:
Handwriting,
Speech
Recognition, and
dictation with
scribe. Random
assignment was
used for order.
Outcome
measures:
Accuracy, quality,
length, vocabulary,
and errors.
did not have a
preferable
method.
Significant
difference was
found for students
with learning
disabilities
between
handwriting
(HW) and speech
recognition (SR).
SR scores were
higher in quality,
length,
vocabulary, and
had less errors
than HW scores
for students with
learning
disabilities.
There was no
significant
difference in HW
and SR scores for
students without
learning
disabilities.
Small
sample
size and
restricted
to one
school
district.
Students
were
handpick
ed by
teachers.
MacArthur,
C. A. &
Graham, S.
(1987)
Investigate
how different
methods of
text production
affect the
writing
processes and
products of
Learning
Disabled (LD)
students.
QuasiExperimental study
with multiple
measures.
Fifth and sixth
grade students with
Learning Disabily.
III
11 students
The students
completed initial
interview about
their writing, (“do
you like to write,
what do you like
about writing, and
what do you find
difficult”). Each
student composed
three stories about
response to pictures
provided using each
of the three
methods:
Handwriting (HW),
word processing
(WP), and dictation
(D).
Measure
outcomes: length,
errors, revisions,
quality, and time.
Quinlan, T.
(2004).
Investigate
how
composing
with Speech
Recognition
Quasiexperimental
study, repeated
measure design.
11 to 14 years
III
41 children
The 41 children
were split into
groups: Fluent
writers and nonfluent writers
Dictated stories
were significantly
longer, were of
higher quality,
and had fewer
grammatical
errors than HW
and WP stories.
HW and WP
stories did not
differ on any of
the product
measures,
including length,
quality, story
structure,
mechanical or
grammatical
errors, or
vocabulary.
However,
revisions and
composing rate
were better with
WP than HW.
Less fluent
children’s
narratives were
inferior to fluent
children’s
Small
sample
size and
limited to
one
school
district.
Restricte
d to fifth
and sixth
grade
students.
No
randomiz
ation.
Length of
study
included
only one
session
(SR), in
old, both fluent and
combination
less fluent writers.
with advanced
planning,
affect the
writing
performance of
less fluent
writers.
Wetzel, K.
(1996).
Answer
questions:
“Can
elementary
students learn
Qualitative,
Exploratory study.
Case study with a
6th grade student
diagnosed with a
V
One student
according to pretest scores.
Children from both
groups attended one
6-hour writing
class, which
included instruction
on use of SR and
four written
narratives. The
narratives were
written using
handwriting method
and speech
recognition method,
both with and
without advanced
planning.
Outcomes
measures:
Narratives were
analyzed for
number of words,
holistic quality,
surface errors, and
t-unit length.
Met with student 30
minutes per week
for 14 weeks. First,
the student was
given lessons using
narratives.
with
Speech
children.
recognition
significantly
increased length
of written work,
as well as
decreased the
amount of errors
in writing.
However, quality
of writing was not
significantly
increased by SR.
Advanced
planning also
assisted in
children in
developing
stories.
The student
learned how to
use the Voice
Type Speech
Recognition
Limited
to one
student.
Outcome
measures
to use
learning disability
VoiceType?”,
“Is the
technology
powerful
enough to
support the
kinds of tasks
students are
assigned?”,
and “Does the
entire process
result in
students’
improved
communication
?”
William, S.
C. (2002).
Examine the
experience of a
single student
with learning
Qualitative, Case
study
One student in
grade K-8 with a
V
One student
VoiceType speech
recognition
program and
prewriting skills.
Each session
included a review
of VoiceType
commands and
procedures,
teaching of new
procedures, and a
writing segment.
He completed
seven short
personal narratives
throughout the
study.
Outcomes
Measures:
Examination of
student’s mastery
with program,
adequacy of
system’s response,
and potential for
improvement in
writing.
The student
completed a 20minute journal
entry session in
program and
worked well with
it although he did
have some
troubles.
VoiceType
recognized 74%
of his words.
Student
completed 6
narratives, in
which teacher
recognized as an
improvement.
She stated that
prior to study, he
usually did not
finish narratives
on his own.
were not
precise.
Student’s word
count in journal
entries increased
with computer
Limited
to one
student.
Research
disabilities in a learning disability.
written
expression and
his use of word
prediction and
speech
feedback
software
during journal
writing.
Outhred, L.
(1989).
Study effect of
word processor
on written work
of children with
learning
disabilities.
Quasi-Experimental
design, purposive
sample.
Students were 812 years old and
diagnosed with
learning disability.
class daily using
word processor,
word prediction,
and speech
feedback.
Outcome
measures: Word
count, quality, and
attitude.
III
15 students
Students’ session
attendance ranged
from 12-21 school
weeks. Each week,
students wrote two
stories, one in
handwriting and
one with word
processor. The
teacher assigned a
topic each time and
allowed 30 minutes
for writing.
Outcome
Measures: Fluency
(word count) and
misspellings.
software and his
holistic quality
increased almost
a full point, which
to someone with
writing difficulty
is a significant
increase. His
attitude toward
writing also
increased.
Half of the
children who had
longer
handwritten
stories had on
average 19 more
word in length
than stories
written with word
processor.
However, the
other half of
children whose
stories were
shorter had an
increase in word
count using word
processor than
handwriting.
There was a
questions
were
broad.
Small
sample
size and
sample
was not
random.
Limited
to one
school
district.
significant
decrease in
spelling errors
using word
processor with
most of the
children.
One article found that speech feedback resulted in an increase in children’s written work along with more revisions made at sentence
level. However, quality and audience awareness did not show a significant change. Five of the studies, mostly level I and II studies,
using word processor and/or word prediction as an intervention found that the students’ writing increased in quality and length, and
errors decreased. However, one study (Level III) found that written work using the word processor program did not differ from
handwritten work in length, quality, story structure, mechanical or grammatical errors, or vocabulary, while revisions and composing
rate did increase with word processor. As for intervention using speech recognition, three studies found the program to be effective.
Two of these studies found improvement in the length, quality, vocabulary, and revisions in the children’s written work. The other
study, which is a level III evidence, found an increase in length, and revisions, but did not see a significant increase in the quality of
written work. Most studies found that the computer programs allowed for an increase in motivation for children when writing.