The roles of handwriting and keyboarding in writing: a meta-analytic review

Abstract

According to the simple view of writing (Berninger, Abbott, Abbott, Graham, & Richards, 2002), the two important components of transcription in writing are handwriting and keyboarding, the third one being spelling. The purpose of this paper is to review the contribution of two writing modes—handwriting and keyboarding to writing performance. In the first section, the contribution of handwriting fluency to writing performance was explored through moderator analyses. We found that handwriting fluency contributes to writing significantly and consistently, and significantly contributes to specific writing measures (e.g., writing quality, writing fluency, substantive quality). We then explored the relationship between handwriting and keyboarding, and compared their contributions to writing. Results indicated that performance on fluency of handwriting and keyboarding were significantly related, particularly on speed. Writing qualities under each mode were relatively competitive; however, keyboarding allows for faster writing. The findings from the two sections emphasized the importance of handwriting on writing development even though keyboarding is accessible.

Full text

The roles of handwriting and keyboarding in writing:
a meta-analytic review
Luxi Feng
1
•Amanda Lindner
1
•Xuejun Ryan Ji
1
•
R. Malatesha Joshi
1
Springer Science+Business Media Dordrecht 2017
Abstract According to the simple view of writing (Berninger, Abbott, Abbott,
Graham, & Richards, 2002), the two important components of transcription in
writing are handwriting and keyboarding, the third one being spelling. The purpose
of this paper is to review the contribution of two writing modes—handwriting and
keyboarding to writing performance. In the first section, the contribution of hand-
writing fluency to writing performance was explored through moderator analyses.
We found that handwriting fluency contributes to writing significantly and consis-
tently, and significantly contributes to specific writing measures (e.g., writing
quality, writing fluency, substantive quality). We then explored the relationship
between handwriting and keyboarding, and compared their contributions to writing.
Results indicated that performance on fluency of handwriting and keyboarding were
significantly related, particularly on speed. Writing qualities under each mode were
relatively competitive; however, keyboarding allows for faster writing. The findings
from the two sections emphasized the importance of handwriting on writing
development even though keyboarding is accessible.
Keywords Handwriting Writing Keyboarding Meta-analysis
Introduction
According to the simple view of writing (Berninger, 2000; Berninger & Amtmann,
2003; Berninger & Graham, 1998), writing subsumes four components: text
generation, transcription, working memory, and executive functions. Among them,
transcription is a critical support to text generation. Transcription consists of
&Luxi Feng
luxifeng@tamu.edu
1
4232 Texas A&M University, College Station, TX 77843, USA
123
Read Writ
DOI 10.1007/s11145-017-9749-x

handwriting, keyboarding, which are both writing modes, and spelling. Confirma-
tory factor analyses have already shown that these two components have separate
but correlated loadings (Abbott & Berninger, 1993; Berninger, Abbott, Thomson, &
Raskind, 2001), and a direct path has been identified from handwriting to
composition (Graham, Berninger, Abbott, Abbott, & Whitaker, 1997). Santangelo
and Graham (2015) have suggested that instruction in handwriting could improve
children’s writing performance.
Handwriting is a complex task of forming letters, numbers, and other characters,
which requires the combination of cognitive functions, and fine and gross motor
skills (Dinehart, 2015). Children’s experimentation with handwriting begins around
two years of age, and continues to develop through the formation of geometric
shapes, horizontal and vertical lines, and crosses (Dinehart, 2015; Feder &
Majnemer, 2007). There are two major components of handwriting: fluency and
legibility (Graham, 1986; Graham & Miller, 1980; Graham, Berninger, Weintraub,
& Schafer, 1998). Handwriting fluency refers to the rate or speed at which the letters
or characters are accurately formed, while handwriting legibility refers to the
accurate formation of the letters or characters.
The association between handwriting (fluency and legibility) and writing
quality
A myriad of studies found that the handwriting proficiency is associated with
writing quality. For example, handwriting fluency has been shown to be positively
associated with the length and quality of written compositions by beginning writers
(Graham et al., 1997; Graham, Harris, & Fink, 2000). In other words, handwriting
fluency can facilitate children’s development of text generation and writing quality
(Graham, Harris, & Chorzempa, 2002; Jones & Chirstensen, 1999). Graham, Harris
and Hebert (2011) introduced the term as writer effect to honor the positive
relationship between handwriting and writing quality. In reading, fluency frees up
working memory space to involve in higher-level tasks, such as comprehension
(LaBerge & Samuels, 1974). Similarly, the writer effect serves as a parallel
relationship for writing, as handwriting fluency allows the writer to devote working
memory to higher-level writing tasks, such as composition (Graham et al., 2011).
McCutchen, Covill, Hoyne, and Mildes (1994) also highlight the ability for writers
to dedicate attentional resources to higher-level processes in writing when
handwriting becomes fluent and automatic. The presence of handwriting difficulties,
including a lack of handwriting fluency, has been found to be cognitively
demanding for young children so much so that they write more simply and do not
participate in writing processes such as planning and revising (Graham et al., 1998;
McCutchen, 1996). Furthermore, handwriting difficulties may lead to diminished
self-efficacy, further resulting in children avoiding writing (Berninger, Mizokawa,
& Bragg, 1991; Graham et al., 1998). Handwriting interventions have been shown
to improve writing quality (Berninger et al., 1997; Jones & Christensen, 1999), and
help alleviate these results.
In line with the writer effect and McCutchen’s (2000) explanation of fluent text
generation allowing writers to overcome the limitations of short term working
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memory, handwriting automaticity has been found to account for much of the
variance in written expression (Jones & Christensen, 1999). As the nature of
measurements of handwriting fluency are straight forward and objective, the impact
of handwriting fluency, or automaticity, on writing may be considered to be
trustworthy and reliable.
Measures of handwriting fluency consist mainly of two types of tasks: copying
tasks and retrieval tasks. Copying tasks relate to copying a word, sentence, or
paragraph of a given written text. In the copying tasks, children can have direct
visual access to the targeted items. For example, Olinghouse and Graham (2009)
instructed children to copy a sentence containing all of the letters as many times as
possible in 1 min. Similar methods include to ask children copy as much as possible
a short story in 90s (e.g., Berninger, Cartwright, Yates, Swanson, & Abbott, 1994;
Berninger et al., 1992; Swanson & Berninger, 1996). Retrieval tasks require writers
to access, retrieve, and then write letters or characters with automaticity and
accuracy based on prior knowledge, instead of visually accessing letters as in
copying tasks, which indicates the involvement of memory along with handwriting
practices. In the retrieval tasks, handwriting fluency is generally measured based on
the number of correct letters or handwriting outcomes produced in a given time
period. In English, such retrieval tasks typically include writing all the letters
following the alphabetic sequence within a given time period (e.g., Christensen,
2009; Hudson, Lane, & Mercer, 2005; Wagner et al., 2011).
The second aspect of handwriting is legibility, which is identified as correctly
forming letters or characters. Handwriting legibility impacts others’ perceptions of
the writer’s competence in composing (Graham et al., 1998). Neatly written papers
generally receive higher grades than papers of poor penmanship, regardless of
content (Santangelo & Graham, 2015). Graham et al. (2011) refer to this concept as
the presentation effect. In a meta-analysis investigating the presentation effect,
Graham et al. (2011) found that of the four presentation factors examined
(handwriting, spelling, grammar, and word-processing printed text), handwriting
legibility produced the largest weighted effect. That is, students’ handwriting
impacted the reader’s scoring of the written composition more than any other factor.
In addition, illegible handwriting can challenge the achievement of spelling and
composition (Mather & Roberts, 1995), which leads to further barriers on academic
progress.
To enhance students’ early writing skills and minimize those obstacles,
handwriting instruction with emphasis on fluency and legibility would play an
important role. For example, the extant studies found that handwriting interventions
which have led to improved handwriting skills and writing quality have included
instruction in legibility in addition to fluency (Graham et al., 2000; Jones &
Christensen, 1999). In a study of first grade students with and without disabilities,
Graham et al. (2000) found that children receiving handwriting intervention
including instruction in handwriting legibility showed both immediate and long-
term improvements in written composition. Such instruction in handwriting
legibility may include learning letter names, learning to form each letter of the
alphabet, copying letters with numbered arrows providing step-by-step guidelines,
and reproducing letters after watching another person write the letter (Graham et al.,
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2000). As handwriting legibility instruction may be straight forward, the evaluation
of handwriting legibility is more subjective and qualitative than the evaluation of
handwriting fluency, potentially leading to inaccurate measurements.
Legibility may be evaluated using dichotomous coding to indicate whether the
response was correct or incorrect. Graded credit may also be used to score
handwriting legibility. Puranik and AlOtaiba (2012) assigned a score range as
missing, incorrect, or non-recognizable letters scoring 0, recognizable but poorly
formed or reversed letters scoring 0.5, and well formed, recognizable letters a score
of 1. Evaluating handwriting legibility could be embedded within the handwriting
fluency evaluation simultaneously.
The importance of handwriting development
Handwriting is not only an important means to communicate, but also an essential
life skill for all people. Children rely on handwriting heavily, because the majority
of their school time could be related to performing handwriting tasks (McHale &
Cermak, 1992). However, a large amount of evidence has been provided for
children experiencing handwriting difficulties. The estimates of their handwriting
difficulties range from 5 to 44% (e.g., Barnett, Stainthorp, Henderson, & Scheib,
2006; Graham & Weintraub, 1996; Karlsdottir & Stefansson, 2002; Sudsawad,
1999). In addition, although Hamstra-Bletz and Blote (1993) suggested that more
boys were at risk of handwriting difficulties than girls, recent results by Weintraub
and Graham (2000) suggested that gender did not significantly contribute to the
prediction of handwriting abilities. Therefore, poor handwriting would be a major
concern for all the children, as those with handwriting problems could be easily and
negatively mislabeled (Sandler et al., 1992). The results of their poor handwriting
include lower academic achievement and self-esteem as well as behavioral
problems (Feder & Majnemer, 2007).
Alternative writing modes: keyboarding and handwriting
The alternative writing mode in the simple view of writing, keyboarding, is another
important component of the transcription and positively associated with text
generation. Similar to handwriting, keyboarding also carries the responsibility of
producing letters promptly and accurately. Along with the spread of technology and
financial supports, keyboarding has been increasingly implemented. Integrating
technology in instruction has raised up contradictory arguments. Some research
indicated the potential to attract more children to get involved in writing (Schwabe
&Go
¨th, 2005), while the others asserted that it interrupted class discussion and
student learning (Kay & Lauricella, 2011; Yamamato, 2007). However, through
using the computers with word-processing programs, children could experience the
substantial differences on learning attitudes, interactions, instructional strategies and
even written outcomes (Wood, 2000). Besides, research has already found
preference on keyboarding, rather than handwriting, especially among young
writers (e.g., Harrington, Shermis, & Rollins, 2000; King, Rohani, Sanfilippo, &
White, 2008; Lee, 2004).
L. Feng et al.
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The differences and similarities between handwriting and keyboarding
Both handwriting and keyboarding require the cognitive ability to retrieve the
appropriate letters and hold them in memory. During handwriting, the writer must
then access the appropriate motor functions necessary to form the letter, determine
the speed with which the letter should be written, and the size in which the letter
should be written. Finally, with all of this information, the writer must form the
letter (Graham et al., 2000).
In addition to the aforementioned retrieval skills, keyboarding requires the writer
to visually recognize and select the appropriate letters on the keyboard. Keyboarders
must cognitively learn the location of the keys and utilize movement patterns and
keystrokes (Perminger, Weiss, & Weintraub, 2004; Sormunen, 1993). These
movement patterns and keystrokes must be memorized so that the keyboarder may
begin to recognize accurate typing based on kinesthetic cues, rather than looking at
the keyboard to find each letter (Perminger et al., 2004).
While keyboarding requires the writer to memorize the associations between the
locations of letters on a keyboard and verbal codes (Gopher & Raij, 1988;
Perminger et al., 2004) along with correct positioning and timing (Perminger et al.,
2004), writers executing handwriting must accurately and efficiently form each
letter. The different physical requirements of handwriting and keyboarding may
have different effects on writing quality and fluency while using each method of
transcription.
Although keyboarding seems to assert some advantages over the traditional
writing mode, handwriting, Berninger (2000) proposed that it would not make
handwriting obsolete. However, little has been known about whether the attention
on the relationship of handwriting and writing is still necessary, when the appealing
alternative writing mode is available.
Research purposes
Several reviews regarding handwriting and writing have been completed in recent
years. Santangelo and Graham (2015) researched on the significance of handwriting
instruction for writing and writing development. Furthermore, Kent and Wanzek
(2016) examined the association of handwriting fluency and identified a positive
relationship. However, no investigation on keyboarding has been conducted. The
current paper consisted of two studies to extend the previous research scope as well
as fulfill this gap. In the first study, we aimed to directly examine the relationship
between handwriting fluency and compositional writing measures based on the
Simple View of Writing. Instead of simply averaging the effect sizes, we relied on
robust variance estimation to control the dependence of effect sizes from one
particular sample. Our research questions included:
1. How does handwriting fluency associate with writing?
2. Do any other factors constrain the concurrent relationship between handwriting
fluency to writing?
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Our second study explored the relationship between handwriting and keyboard-
ing, and compared their associations on students’ writing performances. A concern
on this comparison was that whether the possible difference was related to the
writing modes or extraneous factors, like rater scoring. Accumulative research
suggested no statistically significant rater bias, due to the writing and scoring modes
(Harrington et al., 2000; King et al., 2008; Zhu, Shum, Tse, & Liu, 2016). In other
words, the scoring on a particular composition would not be significantly different,
depending on whether the composition was provided and scored by a certain rater
through the written format or an online system. Since the studies that simultane-
ously included both handwriting and keyboarding measures often examined the
same group of participants, this study aimed on synthesizing the findings from
samples. Therefore, our research questions were:
1. How does handwriting performance associate with keyboarding?
2. Do handwriting and keyboarding differ on their relationships with writing
development?
Study 1
Method
Inclusion and exclusion criteria
Studies were searched based on the following criteria: (1) were conducted and
published by 2015; (2) implemented quantitative empirical research methods; (3)
included measures on both handwriting fluency and compositional writing
outcomes; (4) reported sample size and bivariate correlations between handwriting
and writing; (5) were printed in English; and (6) were from either peer-reviewed
journals or dissertation and thesis. Such searching constrain is used to maintain the
quality of the present review as well as public accessibility, either online or in
library archives. According to Garcı
´a and Cain (2014), studies regarding correlation
generally examined both flips of the coin: hypothesis which supports the
significance of the potential relationship among factors and that which yields
opposite voices. Therefore, the searching of studies would not be doubted due to
concerns on publication bias.
Studies were excluded if the results of the studies provided only means and
standard deviations, without any correlational information. Studies with adult
participants were excluded, since we focused on school-aged population, from
Kindergarten to high school level. Studies including participants with learning
disabilities were retained during the preliminary search.
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Literature search
Studies for this meta-analysis were identified mainly through electronic searches in
four databases: ERIC, PsycINFO, Web of Science, and ProQuest (including
dissertations and theses global). The primary search among titles, abstracts, and
keywords was conducted using Boolean combinations of terms including hand-
writing fluency,handwriting speed/rate,writing, and composition. We also searched
the reference lists of collected documents and other relevant reviews during the
coding procedure to identify additional qualified studies.
The initial search resulted in 93 documents, including journal articles,
dissertations and theses. Duplicated studies located from different databases were
excluded. Qualitative studies and book reviews were also excluded. Utilizing the
selection criteria mentioned above, a total of 16 documents were retained for further
consideration. Some documents included more than one group of participants and
reported their results individually. Therefore, our coding and final calculations
consisted of effect sizes from 19 studies.
Coding procedures
Each study was coded for study descriptors and variables which were related to
effect size calculation. Study descriptors included: author information, publication
year, publication type, participant feature (e.g., English language learner, students
with reading/writing difficulty), number of participants, and research design (e.g.,
longitudinal study). The following moderator variables were coded: type of writing
measures (i.e., writing quality, writing fluency, substantive quality, spelling
performance, and complexity), type of handwriting measures (i.e., measurement
on letter, word, or sentence level), grade level, genre of writing outcomes (i.e.,
narrative or expository text), and orthographies. We intended to examine the
variation of the relationship between handwriting and writing under different
circumstances.
All studies were coded by the first author and 60% of them were double coded by
the second author independently. The interrater reliability was 0.92, and disagree-
ments were resolved through discussion.
Analytic procedure
The computer program, comprehensive meta-analysis (CMA; Borenstein, Hedges,
Higgins, & Rothstein, 2005) was employed for the calculation procedure. Effect
sizes of each study were presented by the correlation coefficients (Pearson r)
between handwriting and writing measures. The 95% confidence interval (CI) for
each effect size was calculated to test whether the specific effect size was
statistically significantly different from zero.
We used a recently developed statistical technique, robust variance estimation
(RVE), to calculate the overall correlation and examine the impacts of moderator
variables in meta-regression analyses (Hedges, Tipton, & Johnson, 2010; Tanner-
Smith & Tipton, 2014). The majority of the studies included more than one
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measurement approach on writing quality (e.g., grammar, structure, ideas, and word
choice, in Kent, Wanzek, Petscher, Al Otaiba, & Kim, 2014). Some studies reported
results separately based on genres of writing outcomes (e.g., Graham et al., 1997).
Some studies also distinguished the correlation coefficients based on the methods of
handwriting measures (e.g., word and sentence, in Yan et al., 2012). The RVE
technique allows the inclusion of multiple effect sizes from the same study within a
given meta-analysis. Without violating the assumption of independence, this
approach avoids the loss of information by dropping certain effect sizes, and does
not require the covariance information of effect sizes, which would be necessary for
the application of other multivariate meta-analysis techniques.
We used a random effect model with two assumptions: the variation between
studies uses a random effect model, and the variation between studies relates to how
they are drawn from the population and includes random errors. Sensitivity analyses
were conducted based on different rho values (e.g., q=0.1, 0.2,…) used for
estimation in the model. In the current study, we generated the results from the rho
value as 0.5 if our estimations did not show much sensitivity along with the change
of qs. Lo
´pez-Lo
´pez, Viechtbauer, Sa
´nchez-Meca, and Marı
´n-Martı
´nez (2010) found
that the statistical power was influenced by the number of studies available, rather
than the total number of effect sizes. Therefore, they suggested using a ttest to
assess the statistical significance of the meta-regression coefficients. All RVE
analyses were run in SPSS 20 (SPSS, 2011), using macro downloaded from http://
peabody.vanderbilt.edu/research/pri/methods_resources.php (Tanner-Smith & Tip-
ton, 2014). According to Tanner-Smith and Tipton (2014), RVE is applicable when
the sample size is limited, but produces narrower CIs and smaller pvalues. In other
words, with a small sample size, a reported estimation, which is expected to be
statistically significant at a=0.05 level, is actually significant at a=0.10 level.
Therefore, a lower a-level should be applied to determine statistical significance
(e.g., a=0.01 or 0.001) when estimating a slope and having the number of studies
within the range of 10–40. Therefore, we used a=0.01 to determine the signifi-
cance of the estimation in the current study.
Finally, we conducted the examination of publication bias. Results were
displayed using funnel plots and results from Egger’s regression test (Egger, Davey
Smith, Schneider, & Minder, 1997) and Duval and Tweedie’s trim and fill analysis
(Duval & Tweedie, 2000) through the analyses using the CMA program.
Inclusion of moderators
As there are many different factors that contribute to overall handwriting skill and
writing quality, we coded multiple moderator variables included in this review
study. In our analyses, we tested the moderation of the following factors on the
relationship between handwriting and writing quality: handwriting measures,
writing measures, grade level, writing genre, and orthography.
Handwriting measures The handwriting measures that were included in our
analyses are measures on the letter, word, and sentence level. That is, whether the
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scorers in each study scored each individual letter for fluency or legibility, or
whether the scorers evaluated a word as a whole, or even an entire sentence.
Differences on the amount of handwriting that needed to be completed for each
score may have varying effects on the relationship between handwriting and writing.
For instance, Jones and Christensen (1999) found that orthographic-motor
integration, including handwriting, accounted for more than half of the variance
in written expression when assessing an entire written text which participants were
allotted 15 min to write. Connelly, Gee and Walsh (2007) also examined
handwriting based on a text produced by participants in a 15-min time period in
their second study. However, in their first study, they also examined handwriting
speed and legibility at the letter level, assessing each individual letter formed in a
2-min time period. The authors found that the number of correct letters produced
increased with age, and that students with more fluent handwriting produced better
quality written texts. As these studies show the use of different handwriting
measures, we included handwriting measures as a possible moderator of the
relationship between handwriting and writing.
Grade level Due to opposing findings in previous research, it is unclear whether
handwriting improves linearly with grade level, or if writers experience period of
developmental increases and plateaus (Graham et al., 1998). In a meta-analysis
examining the impact of component skills on writing quality, Kent and Wanzek
(2016) analyzed grade level as a possible moderator. Whereas the authors found that
grade level was not a statistically significant moderator between handwriting and
writing quality, the strength of this relationship was greater for younger students
(Grades K–3), emphasizing the importance of handwriting fluency for young
writers.
Writing genre Two writing genres were analyzed as possible moderators of the
relationship between handwriting and writing: narrative and expository. Graham
et al. (1997) examined the role of handwriting in relation to both compositional
fluency and compositional quality among primary and intermediate children. For
both primary and intermediate children, the handwriting copying task was more
highly correlated with narrative composition fluency, while for composition quality,
handwriting was more highly correlated with expository quality. This study
highlights the need to examine writing genres as a possible moderator.
Writing measures Types of writing measures included writing quality, writing
fluency, substantive quality, spelling performance, and complexity. Whereas writing
quality may refer to the written substance of the paper including factors such as
grammar, imagination, organization, and word choice, writing fluency may refer to
the generation of written text (Graham et al., 2000). In addition to writing genres,
Graham et al.’s (1997) study highlights the need to examine writing measures such
as writing quality, writing fluency, and spelling performance as possible moderators.
In addition to the finding that the correlation between handwriting and writing
quality was higher for expository texts, the correlation between handwriting and
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writing fluency was higher for narrative texts for both primary and intermediate
children, the authors also found that the correlation between handwriting and
spelling was statistically significant for both primary and intermediate children on
both the composition fluency and composition quality measures. These findings
highlight the need to examine different writing measures as possible moderators.
Orthography We ran moderator analyses to determine whether the orthography of
a study impacted the relationship between handwriting and writing. In a study
examining component processes of writing skills among Turkish-speaking children
in Grades 1 and 2, Babayigit and Stainthorp (2010) found that handwriting speed
reliably and significantly predicted writing fluency, or writing productivity
(b=.66). In a study of Dutch-speaking children, Drijbooms, Groen, and Verhoeven
(2015) also found that handwriting fluency predicted text length (i.e., writing
fluency; b=.24). Whereas the basis of these findings is similar, the strength of the
relationship between handwriting fluency and writing fluency may be different due
to different orthographies.
Results
Descriptive statistics
We included 19 studies in this meta-analysis and calculated 59 effect sizes.
Meanwhile, an additional 15 effect sizes based on spelling performance of the
compositions were identified separately, since some studies included spelling as one
of the indices to evaluate children’s writing. We separated the effect sizes on
spelling performance, because spelling is an independent component of the
transcription based on the Simple View of Writing and supports text generation
simultaneously. Such effect sizes were extracted from those on writing measures
and analyzed separately to avoid inflation of the overall estimation. Besides, some
studies also included additional particular spelling measures and reported their
correlations with handwriting. However, in the current analyses, we did not include
this kind of effect sizes for analysis. Only effect sizes of spelling performance which
were derived from the composition processing were included and coded for further
consideration. Table 1shows qualitative descriptions of all the included studies,
including the study ID, grade level of participants, total number of participants
involved, handwriting measures, writing measures, genres, orthography, and
unbiased effect size (correlation coefficient r) between handwriting and writing
measures. Table 2presents a summary of findings for the research questions.
As shown in Table 1, the publication years ranged from 1992 to 2015. Based on
information reported in the studies, we first examined whether gender could be an
influential factor among the samples. Only the study by Wagner et al. (2011) did not
include the gender distribution. For studies with the gender information, the
percentage of girls ranged from 13.3 to 59.5% (M=0.477, SD =0.099). The study
by Jalbert (2009) was an exception, since the study focused on students with specific
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Table 1 Qualitative descriptions of Study 1
Study NGrade HW
a
W
b
Genre Orthography r
Babayigit and Stainthorp (2010) 48 2 Copy Writing fluency N Turkish 0.630
Content 0.080
Structure 0.120
Spelling error -0.350
Berninger et al. (1992) 300 1, 2, and 3 Copy Writing fluency N English 0.790
Micro organization 0.720
E 0.690
0.590
Connelly et al. (2007) 48 5 and 6 Retrieval Writing quality N/A English 0.450
Drijbooms et al. (2015) 102 4 Copy Writing fluency N Dutch 0.300
Content 0.300
Syntactic complexity 0.220
Graham et al. (1997) 300 1, 2, and 3 Retrieval Writing fluency N English 0.601
Writing quality 0.320
Correct spelling 0.469
E 0.547
0.228
0.323
Copy Writing fluency N 0.743
Writing quality 0.386
Correct spelling 0.575
E 0.687
0.687
0.462
300 4, 5, and 6 Retrieval Writing fluency N English 0.224
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Table 1 continued
Study NGrade HW
a
W
b
Genre Orthography r
Writing quality 0.240
Correct spelling 0.213
E 0.222
0.200
0.240
Copy Writing fluency N 0.412
Writing quality 0.304
Correct spelling 0.161
E 0.343
0.357
0.172
Jalbert (2009) 15 Adolescent Retrieval Writing quality E English -0.230
Text generation -0.120
Spelling error -0.190
Jones and Christensen (1999) 114 2 Retrieval Writing quality N English 0.820
Kent et al. (2014) 265 K and 1 Retrieval Writing fluency E English 0.330
Grammar 0.280
Ideas 0.240
Structure 0.200
Word choice 0.210
Kim et al. (2011) 242 K Retrieval Writing quality N English 0.460
Kim et al. (2013) 156 5 Combined (Retrieval ?Copy) Writing fluency N/A Korean 0.570
Substantive quality 0.280
Medwell et al. (2009) 198 6 Retrieval Writing quality N/A English 0.464
Copy 0.321
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Table 1 continued
Study NGrade HW
a
W
b
Genre Orthography r
Medwell et al. (2013) 186 2 Retrieval Writing quality N/A English 0.581
Copy 0.440
198 6 Retrieval Writing quality N/A English 0.464
Copy 0.321
Olinghouse (2008) 120 3 Copy Writing fluency N English 0.640
Writing quality 0.420
Correct spelling 0.200
Olinghouse and Graham (2009) 64 2 and 4 Copy Writing fluency N English 0.630
Writing quality 0.620
Word choice 0.570
Wagner et al. (2011) 98 1 Combined (Retrieval ?Copy) Macro organization E English 0.320
Writing fluency 0.400
Complexity 0.270
Spelling error -0.150
88 4 Combined (Retrieval ?Copy) Macro organization E English 0.810
Writing fluency 0.720
Complexity 0.070
Spelling error -0.030
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123

Table 1 continued
Study NGrade HW
a
W
b
Genre Orthography r
Yan et al. (2012) 153 K, 1, 2, and 3 Copy (Word) Writing fluency N Chinese 0.340
Writing quality 0.240
Spelling error -0.110
Copy (Sentence) Writing fluency 0.120
Writing quality 0.340
Spelling error -0.060
a
Types of handwriting measures
b
Types of writing measures
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learning disabilities and recruited more males than females. After excluding this
sample, a balanced design on gender was found among all the other studies
(percentage of girls ranging from 41.9 to 59.5%, M=0.499, SD =0.045). We
further examined the participant features. Only the participants (n=15) in Jalbert’s
study (2009) reported specific learning disabilities. Therefore, the moderator
analyses did not consider the potential differences raised by either gender or special
needs of participants in the studies.
What is the relationship between handwriting fluency and writing?
Overall, the 19 studies included 3014 participants. According to the RVE method,
the effect size of the relationship between handwriting fluency and writing measures
was 0.431 (95% CI [0.345, 0.517]). We used a ttest to examine the significance and
found the effect size was statistically significant (t
18
=10.53, p\.001). The
between-study sampling variance (s
2
) was 0.049. The Q test was significant
(Q
e
=277.93, df =18) and I
2
indicated that 93.5% of variation across studies was
due to heterogeneity. Thus, the result suggested a positive and statistically
significant association between handwriting fluency and writing measures.
Table 2 Summary of findings in Study 1
Research question ES 95% CI ts
2
QI
2
What is the general contribution of
handwriting fluency on writing?
0.431** (0.345, 0.517) 10.53 0.049 277.93 0.935
Does the contribution of
handwriting vary across writing
performances?
-0.048 (-0.143, 0.047) -1.11 0.060 264.80 0.951
Writing quality (n=12) 0.399** (0.374, 0.424)
Writing fluency (n=12) 0.525** (0.502, 0.546)
Substantive quality (n=9) 0.408** (0.373, 0.442)
Complexity (n=3) 0.193* (0.077, 0.303)
Does the contribution of
handwriting vary across types of
handwriting measures?
0.003 (-0.242, 0.249) 0.03 0.055 237.86 0.945
Does the contribution of
handwriting vary across
participants’ grade levels?
-0.164 (-0.321, -0.007) -2.21 0.046 245.15 93.3
Does the contribution of
handwriting vary across types of
writing genres?
-0.114 (-0.331, 0.103) -1.14 0.057 227.38 0.943
Does the contribution of
handwriting vary across written
orthographies?
0.152 (0.023, 0.281) 2.48 0.046 249.89 0.928
What is the relationship between handwriting fluency and spelling in writing tasks?
Correctness (n=3) 0.290 (-0.093, 0.673)
Spelling errors (n=4) -0.147 (-0.343, 0.049)
*p\.01; ** p\.001
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Does the relationship vary across writing performances?
As each study reported a variety of writing measures, we investigated the effect of
writing measures on the relationship between handwriting fluency and writing.
Hypothetically, we expected to find handwriting fluency and writing measures are
consistently related. There are four categories of writing measures: writing quality
(n=12), writing fluency (n=12), substantive quality (n=9), and complexity
(n=3). Generally, writing quality was presented by overall compositional scores.
Writing fluency may also be referred to as writing productivity, which counted the
total number of words or characters. Substantive quality was a complex construct
suggested by Kim, Park, and Park (2013), which considered content measures (e.g.,
idea, word choice) as well as organization (e.g., number of key elements, sentence
structure). Finally, complexity was measured by T-units in the words and clause
density. Based on Borenstein, Gedges, Higgins and Rothstein (2009), the power
could be too low when fewer than five studies are included within one category in
moderator analyses. Therefore, our calculation only consisted of the first three
categories. Results suggested no statistical significance at a=0.01 level
(b=-0.048, 95% CI [-0.143, 0.047], t
12
=-1.11, p=0.290, s
2
=0.060,
Q
e
=264.80, df =12, I
2
=95.1%).
We further examined the association of handwriting fluency with each writing
measure individually. Although the relationship was consistent across types of
writing measures, we expected all the effect sizes should be statistically significant.
Results showed the relationship of handwriting fluency with writing quality was
0.399 (95% CI [0.374, 0.424], p\.001,); with writing fluency was 0.525 (95% CI
[0.502, 0.546], p\.001); with substantive quality was 0.408 (95% CI [0.373,
0.442], p\0.001); and with complexity was 0.193 (95% CI [0.077, 0.303],
p=0.001). All the relationships were significant at a=0.01 level.
Does the relationship vary across types of handwriting measures?
The purpose of the third meta-regression analysis was to determine whether the type
of handwriting measures influenced the relationship between handwriting and
writing. We expected to see differences between copying and retrieval measures,
since more cognitive demands were involved for retrieval measures. Studies in our
sample consisted of both copying and retrieval measures on handwriting fluency. In
English, the copying measure was related to sentence production (e.g., the sentence
containing all of the letters in the alphabet: ‘‘The quick brown fox jumps over the
lazy dog.’’). On the other hand, the copying measure was also given as writing the
given words as many times as possible during a limited time. This type of measure
was generally used for studies whose orthography was other than English. The
words usually carried a concrete meaning (e.g., numbers and weekdays) in the
specific orthography. Some studies used both approaches when measuring
handwriting fluency, but reported them as one construct in their correlation matrix.
Overall, we found effect sizes from nine studies on retrieval tasks, ten on copying
sentences and three on repeatedly writing words, and used the first two categories
for analysis. However, results indicated that retrieval tasks and copying sentences
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did not statistically significantly differentiate the relationship between handwriting
fluency and writing as the 95% confidence interval included zero point (b=0.003,
95% CI [-0.242, 0.249], t
12
=0.03, p=0.977, s
2
=0.055, Q
e
=237.86, df =12,
I
2
=94.5%). Therefore, it was concluded that the relationship between handwriting
and writing was not statistically significantly influenced by which type of
handwriting measures was implemented.
Does the relationship vary across participants’ grade levels?
We examined the influence of participants’ grade levels on the concurrent
relationship and expected that a stronger relationship could be found among
primary-level students. The grade level was identified by grouping participants’ age
or grade reported in the studies. We categorized participants aged from Kinder-
garten to Grade 3 (i.e., 0 =primary level) and from Grade 4 to adolescents (i.e.,
1=intermediate or upper level) as two groups. The studies were grouped based on
the experimental design (Graham et al., 1997; Medwell & Wray, 2014; Wagner
et al., 2011), and the differences of the contributors to writing fluency and quality
due to influences of grade levels (Abbott & Berninger, 1993). One study (i.e.,
Olinghouse & Graham, 2009) was excluded for this analysis since it combined
second and fourth graders for correlational calculation. However, we found that
participants’ grade levels did not statistically significantly explain the between-
study variance of the relationship between handwriting and writing at a=0.01
level (b=-0.164, 95% CI [-0.321, -0.007], t
16
=-2.21, p=0.042,
s
2
=0.046, Q
e
=254.15, df =16, I
2
=93.3%), which indicated that this
relationship was consistent across grade levels.
Does the relationship vary across types of writing genres?
As the writing prompts were given in different types, we examined whether the
genres of writing outcomes influenced the relationship between handwriting and
writing. Most of the studies reported whether their writing prompts expected a
narrative or expository composition as an outcome. However, some studies offered
no hints to identify this moderator. Therefore, our coding included the genres of
writing outcomes as binary (i.e., 1 =narrative, 2 =expository). Results suggested
that the genres of writing outcomes did not statistically significantly explain the
between-study variance of the relationship between handwriting and writing, and
the 95% confidence interval included the zero point (b=-0.114, 95% CI [-0.331,
0.103], t
12
=-1.14, p=0.275, s
2
=0.057, Q
e
=227.38, df =12, I
2
=94.3%).
Therefore, we concluded that the genres of writing outcomes did not significantly
impact the relationship between handwriting and writing.
Does the relationship vary across written orthographies?
We conducted a meta-regression analysis to examine whether handwriting in
different orthographies and writing measures influenced the relationship between
handwriting and writing. We generated two groups, English and non-English (i.e.,
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123

Chinese, Dutch, Korean, and Turkish). The majority of the studies (79%, 15 out of
19) were conducted in English. Results showed that the orthography did not
statistically significantly explain the between-study variance of the relationship
between handwriting and writing (b=0.152, 95% CI [0.023, 0.281], t
17
=2.48,
p=0.024, s
2
=0.046, Q
e
=249.89, df =17, I
2
=92.8%). However, since the
non-English group only consisted of four studies, more such research would be
needed to support the consistent correlation between handwriting fluency and
writing across orthographies.
What is the relationship between handwriting fluency and spelling
in writing tasks?
We investigated the relationship of the two transcription components. There were
seven studies reporting the relationship between handwriting and spelling perfor-
mance, and these spelling measures were conducted within the writing outcomes,
rather than individual assessments. The hypothesis was that handwriting fluency and
correct spelling should be positively associated, since reducing demands were
placed on letter and sound correspondences. Three of these studies reported spelling
accuracy, and the average correlation value was 0.290 (95% CI [-0.093, 0.673],
p=0.083). The other four studies reported the amount of spelling errors, and the
average correlation value was -0.147 (95% CI [-0.343, 0.049], p=0.097).
Overall, both 95% confidence intervals regarding the relationship between
handwriting and spelling performance included zero point and ttests indicated no
statistical significance, which suggested no significant correlation between the two
transcription components, when spelling was evaluated along with writing
outcomes.
Publication bias
We first explored the publication bias of the studies by the funnel plot of standard
error with 95% confidence limits using CMA. There was no obvious asymmetry in
the funnel plot while most studies were beyond the range of 95% confidence limits,
as is shown in Fig. 1. We also examined the results of Egger’s regression test and
did not find evidence of publication bias or small study effect (b=0.42, SE =2.63,
p=0.874). Furthermore, Duval and Tweedie’s trim and fill analyses did not
suggest any studies trimmed. Therefore, we concluded that the findings of the
studies were not constrained by publication bias.
Study 2
In the second study, we intended to gauge the magnitude of association between
handwriting and keyboarding via the meta-analytic review approach and examined
whether handwriting and keyboarding differed on their relationships with writing
and writing development.
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Method
Inclusion criteria
According to prior searching, studies on the comparison and/or relationship of
handwriting and keyboarding were limited. Therefore, we included the eligible
studies based on the following criteria: (1) the studies were conducted and published
by 2015; (2) were designed as quantitative empirical experiments; (3) included
measures on handwriting and keyboarding simultaneously; (4) reported sample size
and the correlations and/or means (with SD) of handwriting, keyboarding, and/or
writing measures; (5) were print in English; and (6) are available to the public,
either online or in library archives.
Literature search
Studies for this meta-analysis were identified mainly through electronic searches in
four databases: ERIC, PsycINFO, Web of Science, and ProQuest (including
dissertations and theses global). The primary search among titles, abstracts and
keywords was conducted using keywords including handwriting and keyboarding,
transcription and keyboard,pen and keyboard, and/or writing. We also searched the
reference lists of collected documents during the coding procedure to identify
additional relevant studies.
The initial search resulted in 20 documents, all of which were journal articles;
duplicated studies located from different databases were excluded. Utilizing the
selection criteria mentioned above, a total of seven documents were retained for
further consideration. Two studies were longitudinal, and each included two cohorts
(i.e., Berninger, Abbott, Augsburger, & Garcia, 2009; Berninger et al., 2006).
Fig. 1 Funnel plots with 95% confidence limits for the relationship between handwriting and writing
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Coding procedures
Each study was coded for study descriptors and effect sizes which related to the
meta-analytic calculation. Study descriptors were same as the first study. Effect
sizes included the correlations between handwriting and keyboarding, and the
comparison between handwriting and keyboarding on writing measures. Not all the
studies included both types of effect sizes, so we coded them separately. All studies
were double coded by the first author and a graduate student independently. The
interrater reliability was 0.90. Disagreements were resolved through discussion and
decisions were revised by the first author.
Analytic procedure
Because of the limited sample size and dependence of participants among samples,
we did not honor this study as a meta-analysis. The analytic process, regarding the
correlations between handwriting and keyboarding, and their correlations with
writing measures, was conducted using CMA. The comparisons of means on writing
measures under handwriting and keyboarding modes were reported only in the two
longitudinal studies. The results on the patterns regarding these comparisons were
analyzed qualitatively and systematically.
Results
Descriptive information of the sample articles is given in Table 3. Although some
studies focused their research on students with learning disabilities or special needs,
the results of the current analytic study concerned only the general population.
What is the relationship between handwriting and keyboarding
performances?
Handwriting and keyboarding fluency
Fluency under both handwriting and keyboarding modes was identified as the total
number of correct handwritten or typed letters within a limited period of time. There
were four studies (i.e., Berninger et al., 2006; Christensen, 2004; Connelly, Gee, &
Walsh, 2007), two of which were from one longitudinal study using two cohorts,
reporting effect sizes. For the longitudinal study, we included only the results from
the last experimental period to control for the potential effects of grade level, as the
participants from the other two studies were from intermediate grade levels. The
average weighted effect size was 0.561 (95% CI [0.510, 0.608], p\.001).
Handwriting and keyboarding speed
Speed under both modes was identified as the number of handwritten or typed letters
per minute. No decision on correctness was made under this condition. There were
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Table 3 Qualitative descriptions of Study 2
Study NGrade r
Fluency
r
Speed
r
Accuracy
r
HW
r
K
M
HW
(SD)M
K
(SD)
Berninger et al. (2006)
a
92 3 0.30
87 0.46
91 0.07
73 5 0.30
76 0.42
75 -0.03
128 1 Auto letter 3.0 (2.3) 4.3 (3.6)
Total time 107.3 (25.6) 99.4 (27.4)
122 3 6.2 (2.4) 8.1 (4.0)
61.5 (20.0) 68.5 (25.6)
113 3 Auto letter 5.1 (2.6) 8.9 (4.7)
Total time 63.8 (23.3) 65.8 (30.9)
106 5 8.7 (3.6) 14.9 (5.3)
45.9 (17.0) 35.3 (16.6)
Berninger et al. (2009)
a
124 2 Auto letter 4.45 (2.20) 6.20 (4.02)
Total time 81.09 (27.35) 88.25 (35.65)
229 4 7.18 (3.41) 11.73 (5.35)
54.47 (22.28) 47.82 (25.17)
106 6 10.12 (3.44) 18.31 (5.09)
35.93 (13.93) 25.64 (15.60)
Christensen (2004) 276 8, 9 0.51 Quality 0.44 0.54
Length 0.30 0.55
Connelly et al. (2007) 314 K to 6 0.70
48 5, 6 Quality 0.45 0.42
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Table 3 continued
Study NGrade r
Fluency
r
Speed
r
Accuracy
r
HW
r
K
M
HW
(SD)M
K
(SD)
Perminger et al. (2004) 47 5 0.05
52 0.340
Roger and Case-Smith (2002) 38 6 0.342
Weintraub et al. (2010) 63 0.52 0.07
a
Longitudinal study
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five studies included (i.e., Berninger et al., 2006; Perminger et al., 2004; Rogers &
Case-Smith, 2002; Weintraub, Gilmour-Grill, & Weiss, 2010). For the two effect
sizes from the longitudinal study, the decision of choice was consistent with the
previous study. The participants from the other three groups were all in the
intermediate grade levels or adults. The average weighted effect size was 0.431
(95% CI [0.335, 0.519], p\.001).
Handwriting and keyboarding accuracy
Accuracy under both modes was identified as counting only the number of correct
letters or characters through handwriting or keyboarding. No limits on timing were
considered under this condition. There were four studies (i.e., Berninger et al., 2006;
Perminger et al., 2004; Weintraub, Gilmour-Grill, & Weiss, 2010) including two
from the longitudinal study. The average weighted effect size was 0.039 (95% CI
[-0.081, 0.159], p=0.521). The 95% confidence interval included the zero point,
so we concluded that accuracy of handwriting and keyboarding are not statistically
significantly related.
Do handwriting and keyboarding differ on the contributions to writing?
Correlational comparison between handwriting and keyboarding fluency on writing
quality
Only two studies (i.e., Christensen, 2004; Connelly et al., 2007) included effect
sizes to compare this relationship. The average weighted effect size regarding the
handwriting mode was 0.441 (95% CI [0.349, 0.526], p\.001). In contrast, the
effect size regarding the keyboarding mode was 0.524 (95% CI [0.440, 0.599],
p\.001).
Correlational comparison between handwriting and keyboarding fluency on writing
fluency
Only one study (i.e., Christensen, 2004) reported this type of effect size comparably.
The average weighted effect size regarding the handwriting mode was 0.300 (95%
CI [0.189, 0.404], p\.001), while that of the keyboarding mode was 0.550 (95%
CI [0.462, 0.627], p\.001). There was no overlap across the 95% confidence
intervals under both modes, which may suggest the significant difference between
the influences of handwriting and keyboarding fluency on writing fluency. However,
the generalizability of this conclusion was limited because we only had one sample
study.
Mean comparison between handwriting and keyboarding modes on automatic letter
writing
The two longitudinal studies reported the means of automatic letter writing under
both modes. Berninger et al. (2006) studied two cohorts, one from Grades 1 to 3,
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and the other form Grades 3 to 5. The other article by Berninger et al. (2009)
partially combined the results from two cohorts because one was from Grades 2 to 4
and the other was from Grades 4 to 6. Measurements on Grade 4 for both cohorts
were considered as one grade level, although the results were recorded longitudi-
nally. Due to the violation of the independence assumption and the mixture of
groups, the reported means and SDs were not available for further calculation of the
weighted effect sizes. However, the overall pattern suggested the students tended to
write more letters within a limited period of time (15 s) under the keyboarding
mode, and the results of F tests in both studies were statistically significant (both
p=.001). This finding was consistent across the grade levels.
Mean comparison between handwriting and keyboarding modes on writing time
Another comparison of means made in both longitudinal studies was on the total
writing time. The design of reporting the results was the same as previously
discussed. However, this comparison of means suggested some discrepancy. Only
the group of second graders in Berninger et al. (2009) indicated that the writing time
was longer under the keyboarding mode than the handwriting mode, and the result
of F test was statistically significant at a=.05 level (p=.03). Results from all the
other groups (i.e., groups of Grades 1, 3, 4, 5, and 6) reported statistically significant
priority (all ps\.01) of keyboarding mode on the total writing time.
Discussion
According to the presence of presentation and writer effects (Graham et al., 2011),
handwriting serves as a critical factor of both the evaluation and development of
writing performances. Although the contribution of handwriting instruction on
writing has already been cumulatively reported, the findings from the first meta-
analysis study provided further support of the beneficial relationship between
handwriting and writing. Additionally, the findings from the second meta-analytic
review suggested that handwriting contributed to writing as much as keyboarding
did, which suggests that students should develop handwriting skills and receive
explicit instruction about the technology. Results from the current studies supported
the statement by Berninger (2000) and merited the benefits of handwriting as a
transcription component.
Integration of the development of handwriting and writing
We proposed that handwriting fluency would correlate to the writing measures
significantly. The hypothesis was supported by the significant effect size of 0.423
(SE =0.045). We anticipated that there would be some constraints on this
relationship across studies, such as grade levels, handwriting and writing measures,
writing genres, and orthographies. However, the contribution of handwriting fluency
to writing was relatively robust, because none of the moderator effects were
identified with statistical significance. It is critical to be aware of the lower a-level
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(i.e., a=.01) which we applied on moderator analyses, because of the possible
shrink on estimation of confidence intervals through RVE technique when having a
limited number of studies.
We further explored the contribution of handwriting fluency to each writing
measure. As anticipated, handwriting fluency was identified with significant
correlation with most of the writing measures. The only exception was with
complexity, which emphasizes syntactic construction and manipulation. The skills
of complexity relied more on executive functions, like planning and self-regulation,
based on the Simple View of Writing. Besides, previous research with first- and
second-language learners has suggested that complexity was further limited due to
students’ language proficiency levels (Larsen-Freeman, 2006; Vyatkina, 2012),
although it could be improved through specific writing instruction on the text
structure (Watanabe & Hall-Kenyon, 2011). Other extraneous factors, such as the
text genre and the measures used, could impact on the evaluation of complexity
(Beers & Nagy, 2009). This might explain why we failed to find a significant
relationship between handwriting fluency and complexity.
The meta-analysis by Santangelo and Graham (2015) has already shown that
students with handwriting instruction would perform significantly better on writing
quality, writing productivity, and writing fluency compared to their peers without
handwriting instruction. The practical importance of handwriting instruction is
further supported through the current meta-analysis, as we found the consistency of
the relationship between handwriting fluency and writing. Although the contribution
of handwriting fluency varied across different writing measures, handwriting
fluency was identified as a significant factor of students’ performance on writing
quality, writing fluency, and substantive quality.
The power of our findings from the two studies on handwriting significance was
compromised by the limited availability of studies. With more research considering
the contributions of handwriting, its importance would be better understood.
Comparative influence of handwriting and keyboarding on writing
While we notice the contribution of handwriting to writing, we are also aware of the
challenges from its competitive peer, keyboarding, because both are candidates of
the writing modes. If we found the superiority of keyboarding, it is possible that
keyboarding should be widely encouraged in classrooms as a substitute for
handwriting practices.
In the second study, we found limited studies were designed as having
handwriting and keyboarding modes as treatment and control. All of the studies
included in the current review had the same group of participants measured under
both modes, although some studies intended to compare students’ writing
performances correspondingly. We found that handwriting fluency was significantly
correlated with keyboarding fluency (r=0.561, 95% CI [0.510, 0.608], p\.001),
especially on the measure of speed (r=0.431, 95% CI [0.335, 0.519], p\.001). In
other words, students with higher handwriting fluency appeared to have higher
keyboarding fluency. As Berninger and Swanson (1994) suggested that transcription
consists of handwriting and spelling, the failure of accuracy measures to raise
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significant correlation may be due to the influence of spelling and working memory.
The automatic spell check capability of keyboarding may lead to bias as well,
although no study explicitly mentioned this point.
When we compared the performances of handwriting and keyboarding on
writing, we found that students could write faster and produce larger quantities of
writing under the keyboarding mode. In other words, students produced more typed
words than handwritten ones within the same period of time. They also had to spend
more time completing their handwritten composition, although the amount of text
written was not more than that under the keyboarding mode. This was not
surprising, as previous research consistently suggested that most students could
write faster with keyboarding (Brown, 1988). However, the advantage of
keyboarding on this aspect was constrained by some limitations. The findings were
generated from only two longitudinal studies, and the participants were the same
group under both modes. Although these participants had prior experience with
keyboarding, their proficiency level under each mode was not explicitly identified.
Furthermore, the amount of productivity was not the only major criterion of writing
evaluation. The high productivity did not guarantee a structured in-depth planning
and then a high writing quality. For example, Mueller and Oppenheimer (2014)
investigated students’ learning when they took notes under different writing modes.
They found that with access to keyboarding, students tended to write verbatim
rather than processing information and rewording it under the handwriting
condition, which could be detrimental to their learning process. Although the
amount of words in a typed manner could be almost three times more than those
handwritten ones, students’ learning achievement was not significantly promoted
with keyboarding. Similarly, when considering writing as a comprehensive practice,
choices of writing modes as either handwriting or keyboarding may not lead to a
significant discrepancy to evaluate students’ writing performance.
We found some overlaps (i.e., correlation ranging from 0.440 to 0.526) on the
95% CIs when comparing the relationships of handwriting and keyboarding fluency
on writing quality. Although the non-independent group assignment did not allow
further comparison between the two effect sizes, the evidence of overlapping
indicated that handwriting and keyboarding are comparable to each other on their
contribution to writing quality. Overall, despite the widespread usage of technology
in classrooms, handwriting is still critical for students’ writing development, and
should be explicitly instructed.
Limitations
Admittedly, there are some limitations in our studies. We only included peer-
reviewed articles and theses. Excluding other unpublished literature, such as
research reports and manuscripts, could lead to insufficient representation of the
relationship between handwriting, keyboarding and writing. However, examination
on publication bias suggested that the current findings were not limited due to
publication bias. Rather, this supported the significance of our findings. Second,
although we intended to include studies of all orthographies, limited studies on non-
English languages could be located, which constrained the power of moderator
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analysis across languages. The insufficient amount of non-English research may
influence the significance of the relationship between handwriting and writing in
other languages, since studies on English were dominant. More studies on
handwriting, keyboarding and writing would be strongly needed for such moderator
analyses. Finally, the dependence within studies on handwriting and keyboarding
hindered further examination and comparison. Given the result that these two
writing modes were moderately positively associated, the significance of handwrit-
ing and handwriting instruction was still highlighted, which deserved exploration in
future research.
Conclusion
Through the two studies related to the relationship of handwriting, keyboarding and
writing measures, we stressed the need for incorporating handwriting as an essential
part of instruction in classrooms. Handwriting and keyboarding both significantly
positively associated with the development of writing, for a variety of writing
measures. This further supports the simple view of writing, which emphasizes the
contribution of transcription skills on text generation. Besides, handwriting did no
worse than keyboarding on writing quality and actually significantly related to
keyboarding performance, particularly on speed. In addition to identifying the
significance of handwriting, the current studies also indicated additional research
needs on handwriting to explore its implementation and effectiveness.
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