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Exploring the relationship between children’s
knowledge of text message abbreviations and
school literacy outcomes
Beverly Plester*, Clare Wood and Puja Joshi
Coventry University, Coventry, UK
This paper presents a study of 88 British 10–12-year-old children’s knowledge of text
message (SMS) abbreviations (‘textisms’) and how it relates to their school literacy
attainment. As a measure of textism knowledge, the children were asked to compose
text messages they might write if they were in each of a set of scenarios. Their text
messages were coded for types of text abbreviations (textisms) used, and the ratio of
textisms to total words was calculated to indicate density of textism use. The children
also completed a short questionnaire about their mobile phone use. The ratio of
textisms to total words used was positively associated with word reading, vocabulary,
and phonological awareness measures. Moreover, the children’s textism use predicted
word reading ability after controlling for individual differences in age, short-term
memory, vocabulary, phonological awareness and how long they had owned a mobile
phone. The nature of the contribution that textism knowledge makes to children’s
word reading attainment is discussed in terms of the notion of increased exposure to
print, and Crystal’s (2006a) notion of ludic language use.
According to the Mobile Life Report (2006), 92% of British mobile phone users feel that
their phones are an essential part of their daily life. The BBC reported that in September
2007, nearly 5 billion text messages (or SMS, Short Message Service) were sent in Britain,
about 4,000 per second. Young adolescents from 12 to 15 spoke recently in a public
forum in the United States about the place of digital technology in their lives, and
many mentioned their phones, some commenting upon their sometimes excessive
enthusiasm for texting (Kids Speak Out, 2007). Fifty percent of young adults questioned
said they would rather text than talk to their friends (Reid & Reid, 2005). The Mobile Life
Report found that 51% of 18–24 year olds sent or received at least six texts a day. Further,
the Ofcom (2006) Media Literacy Audit, which focused on British children, reported that
8–11 year olds sent an average of 16 texts per week. Online and paper glossaries of
‘cyberspeak’ or ‘netspeak’ or ‘textspeak’ abound (e.g. Crystal, 2004; Ihnatko, 1997;
* Correspondence should be addressed to Dr Beverly Plester, Psychology Department, Coventry University, Coventry CV1 5FB,
UK (e-mail: b.plester@coventry.ac.uk).
The
British
Psychological
Society
145
British Journal of Developmental Psychology (2009), 27, 145–161
q 2009 The British Psychological Society
www.bpsjournals.co.uk
DOI:10.1348/026151008X320507

Sanderson, 1993), giving lists of symbols and abbreviations of various sorts that have
been used in computer mediated communication. Indeed, young people as a group
have been defined by others in terms of their computer mediated communication, for
example ‘Generation Txt?’ (Thurlow, 2003).
Thurlow (2003) examined over 500 older British teenagers’ text messages for
content and communicative form. He concluded that the messages demonstrated adept
and creative communicative ability, and did not demonstrate the corruption of language
feared by many. Thurlow (2006) has followed with a critical discourse analysis of over
100 media articles about text messaging, drawing out several themes of high profile
concern to the journalists, with the flavour being decidedly negative and often
exaggerated, published with little regard to the actual uses of text messaging, and often
in the face of evidence to the contrary. We read of reported intrusions of text language
forms, or ‘textisms’, in standard English writing, and anecdotes are cited to show other
forms of apparent decline in written English, in coursework, and examinations
(e.g. Associated Press, 2007; Sutherland, 2002). Text messaging is a rapidly growing
phenomenon, and has seen research into its social and communicative aspects (Reid &
Reid, 2005), its linguistic aspects (Crystal, 2006a, 2008), but little research on the
interaction of text or SMS literacy with standard English literacy with pre-teen children.
This is equally concerning in that such influential articles could be used to inform
educational policy decisions in the absence of empirical evidence.
Katz and Aakhus (2002) have called for expert-framed academic discussion about
the use of technology in communication, to balance the folk-framing of anecdote
and opinion. They have asked for data-driven conclusions. Kasesniemi and Rautiainen,
in the Katz and Aakhus volume, published an extensive survey of Finnish adolescents
between 13 and 18 years of age. They examined the SMS culture among the young
in a country with one of the highest rates of mobile phone ownership and usage
in Europe, through surveys, individual interviews, field notes, mobile communication
journals by teenagers, text messages collected by the teenagers (p. 173). Overall, the
perspective taken by the texters interviewed was highly positive, although the
authors acknowledged a more negative view expressed in the wider population.
Others (Crystal, 2005, 2006a, 2006b; O’Connor, 2005) have argued for more positive
approaches. Crystal has emphasized the linguistic flexibility and metalinguistic
competence that might be entailed as people move between alternative forms of
language as appropriate in different contexts.
O’Connor (2005), acknowledging concerns about the effects of SMS and instant
messaging (IM) on teenagers’ schoolwork, notes also that some educators value these
modes of communication in getting young people interested in expressing thoughts
in writing, and drawing attention to modes of expression. O’Connor cited American
teenagers’ positive views, but also those which acknowledged the potential for
interference with academic register language as SMS and IM users develop more
automatic usages of the abbreviated word forms that are seen to characterize text
messages, (e.g. Bell, 2003; Helderman, 2003; Lee, 2002). Ling and Baron (2007) have
noted some significant qualitative and quantitative differences between text message
and IM language, however, but O’Connor’s conclusions might be cautiously extended to
British pre-teen text users.
Pre-teens have been the fastest growing market for mobile phone companies (Hale &
Scanlon, 1999), and more recently, the Ofcom Media Literacy Audit found 49% of British
8–11 year olds had their own mobile phones. Little research has focused on this age
group’s phone use, text literacy, and associations between interactive media and
146 Beverly Plester et al.

other literacies, including the language skills required for success in English at school
(Wartella, Caplovitz, & Lee, 2004). As written standard English words come to be
recognized and used freely through experience, so also should text abbreviations for
those words, as they are used in sending and receiving text messages. With younger
children using text messaging and other interactive media, it will be important to see
what associations appear, and to explore the implications for the language curriculum.
Pre-teen and adolescent and young adult studies have all examined texting issues with
participants whose written language skills are already in place, but as the age of first
mobile phone use falls, children may come to be texting contemporaneously with the
establishment of reading and writing skills, and what we find about the relationship
between computer mediated communication literacies and standard school literacy will
be even more important.
The idea that the use of textisms when text messaging may be positively, rather than
negatively, related to reading attainment in children is not an illogical proposition if we
look at the existing literature on reading acquisition and consider the nature of the more
common forms of text abbreviation that children appear to use. Many, if not most,
textisms are essentially forms of phonetic abbreviation, as in the example of ‘2nite’
instead of ‘tonight’. To produce and read such abbreviations arguably requires a level
of phonological awareness (and orthographic awareness) in the child concerned.
Phonological awareness has been the focus of reading research for a number of
decades now, and such research has demonstrated a consistent association between
different forms of phonological awareness and reading attainment (e.g. Adams, 1990;
Snowling, 2000).
A further factor that is reliably associated with reading attainment is exposure to the
printed word. Stanovich and West (1989), for instance, in a study with adults, found
that their measure of exposure to text was able to predict word processing ability
independently of phonological skill, through orthographic processing skills.
Cipielewski and Stanovich (1992) demonstrated that children’s reading ability in fifth
grade, roughly the age of our younger participants, was predicted strongly by their
measure of text exposure, an Author Recognition Test, after earlier reading ability and
orthographic decoding skill were accounted for. Stainthorp (1997) produced a
Children’s Author Recognition Test as a British equivalent, which was also shown to
predict reading.
Stanovich (1986) documented a rising spiral relationship between phonological
skill, orthographic decoding skill, word recognition, vocabulary, and ability to free up
attentional resources for the engagement with the meaning of text, and so increase
the likelihood of further meaningful exposure to print. Dubbed the ‘Matthew Effect’,
Stanovich proposed that some of the associations between abilities might be fruitfully
seen as reciprocal, rather than one way, thus adding to the spiral. He also documented
the inverse effects whereby those poorer in early skills increasingly find it more
difficult to engage meaningfully with reading material of interest to them, and may fall
further behind.
It is possible that the freedom from regulated orthographic and spelling
conventions, and default to phonological coding that is one characteristic of text
abbreviations, could yield an increase in exposure to text for poorer readers, and
improve motivation to engage with written communication without the constraints
of school expectations.
In terms of spelling, although the textisms may be orthographically unconventional
in one sense, they do demonstrate an awareness of alternative legitimate orthographic
Text messaging and school literacy 147

spellings within English (e.g. ‘ite’ is pronounced the same as ‘ight’), albeit supplemented
with the use of numerals as shorthand characters. Moreover, it is important to
acknowledge that exposure to misspellings may not have a negative effect on the
subsequent learning of correct spellings in children (Dixon & Kaminska, 2007; Ehri,
Gibbs, & Underwood, 1988), through a proactive inhibitory effect, although exposure
to misspellings after learning correct spellings may be deleterious for adult readers.
In other words, although textisms are ‘misspellings’ in a conventional sense, they are
phonologically and orthographically ‘acceptable’ forms of written English, and for
children there is no evidence that knowledge or use of them would cause interference
with their learning of conventional written English.
Two initial studies have already explored some of the relationships between
pre-teens’ use of text language and standard school attainment (Plester, Wood, & Bell, in
press). In the first of these investigations, a mixed relationship emerged. Eleven year old
children were categorized as either more or less frequent text users, on the basis of
whether they were above or below the median in estimated number of texts sent
per day. The more frequent text users scored significantly lower in verbal and non-verbal
reasoning assessments than did children who reported that they did not use text
messaging at all, and marginally lower than the children who were below the median
estimate. The children were asked to translate a text message (with textisms) into
standard English, and another from standard English into a text message. Frequency of
text use had no effect upon the proportion of text abbreviations used. All groups used
roughly 58% textisms in their translation. Furthermore, the children with the highest
ratio of textisms to total words, the ones with the most densely abbreviated style, were
the children with the highest verbal reasoning scores, regardless of their level of
estimated use of text. The verbal reasoning measure used (the Cognitive Abilities Test) is
used by schools to predict children’s attainment in English Key Stage tests, and is highly
correlated with performance on English National Curriculum Key Stage 2 and Key
Stage 3 English language measures (Strand, 2006).1
A second study aimed to explore this mixed result by assessing 10–11-year-olds,
using more varied textism translation exercises and a standardized spelling test.
The children’s Key Stage 2 writing levels were also used in the analysis. This study found
that knowledge of textisms was positively associated with spelling attainment, and that
it was use of the more phonologically based forms of textism that could explain the most
variance in conventional spelling scores. When the data were analysed by Key Stage 2
attainment Level, the children achieving a Level 5 in writing were using the highest
proportion of textisms in the translation exercise, and were using significantly more
phonologically based text abbreviations than the children achieving Level 4.
One observation was that the children in the second study, who had scored in the
highest two levels of their Key Stage 2 English language assessments, were able to move
freely into a very different register of language by using so-called ‘Youth Code’ textisms,
which represent spoken casual pronunciations, such as ‘dat fing’. Thurlow (2003)
refers to this type of textism as ‘accent stylization’. But the children also knew that
such language was not appropriate in the context of their formal testing, showing
1
Key Stages represent phases in the English National Curriculum for state maintained schools, from beginning primary
education at Key Stage 1, to ending secondary education at Key Stage 4. Standardized assessments take place in English,
Mathematics, and Science at the end of the later Key Stages: Key Stage 2 assessments at age 11 and Key Stage 3 assessments
at age 14.

metalinguistic knowledge. Another observation was that the children appeared to be
novice texters, in that they used many different textisms for the same word, and had not
adopted codified text language forms, such as might be found in the netspeak glossaries
(Crystal, 2004; Ihnatko, 1997; Sanderson, 1993).
Two main conclusions can be drawn from these early studies. First, there was little
evidence that using text language was damaging to pre-teen children’s standard English
ability. Second, there was, in contrast, a strong positive relationship between their use of
textisms and other measures of their English ability.
Rationale
The present study set out to understand the nature of the apparent positive
association between conventional literacy and knowledge of textisms. As the
relationship may be explained by individual differences in phonological awareness and
orthographic decoding, the children were assessed on these skills, alongside other
baseline cognitive measures, such as vocabulary and short-term memory (given the
previously observed relationship between textism use and verbal reasoning ability).
Moreover, previous research had not considered the association between children’s
reading ability and their texting behaviour, so standard measures of word and
non-word reading were also included. Exposure to text is another factor associated
with reading progress, but we did not wish to add yet another formal test to an
already lengthy set of measures for the children to complete. However, we did
assess, how long the children had access to a mobile phone, as this may be seen as a
measure of a form of informal text(ism) exposure, which may be pertinent to our
research question.
As text language is both productive and receptive to be functional, and has features
akin to both written and spoken language, we would expect to find associations
between texting and both reading and spelling measures. We were interested in
particular in the extent to which any association is mediated by either phonological
awareness or cognitive factors, the children’s age, or the length of their exposure to
texting. A secondary question considered the children’s use of specific forms of textism
and the association between these forms and the various literacy outcomes.
Method
Participants
Eighty-eight children took part, recruited from Year 6 and 7 classes in five schools in the
Midlands, UK. These schools represented a wide range of socio-economic urban and
suburban catchments. There were 55 girls and 33 boys, with an overall mean age of 10.6
years (SD ¼ 0:64). About 78% of the children had sole use of a mobile phone and 15.4%
could borrow one when they wished. The mean age of acquiring a first phone was 9.0
years, (SD ¼ 1:34 years, range 6–12 years). The children reported using their phones
most for texting and talking, as follows: texting 38.8%; talking 30.6%; 15.3% played
games most; 10.6% took pictures most; and 4.7% cited ‘other’ uses. When asked whom
they talked to most, 54% said friends, 27.1% said parents, 16.5% said other family
members, and 2.4% reported ‘others’. When asked to whom they sent text messages
most, 68.7% said friends, 15.7% said parents, and 15.7% said other family members.
About 55.3% of respondents said they used predictive text at least some of the time and
44.7% said they never did.

Measures
The children were given a questionnaire asking age, sex, school year, whether they had
sole use of a mobile phone, or could borrow one, when they had received their first
phone, what purpose they used the phone for most, whom they phoned most, whom
they texted most. They were then tested individually on the following measures, which
were administered according to standardized instructions.
The British Picture Vocabulary Scales II (Dunn, Dunn, Whetton, & Burley, 1997)
was included as a baseline measure of children’s receptive vocabulary, so that this could
be used as a control variable in statistical analyses, as vocabulary scores are often
associated with reading and spelling attainment. Standardized scores were used in
subsequent analyses.
The forward and backward digit span subtests from the British Ability Scales II
(Elliot et al., 1996) were also included as baseline variables to give an indication of the
children’s verbal working memory capacity, given the known association between the
phonological loop and phonological awareness and word reading (e.g. Passenger, Stuart,
& Terrell, 2000). Ability scores are reported.
The word reading and spelling subtests of the British Ability Scales II (Elliot et al.,
1996) were used as simple measures of conventional reading and spelling ability, and
ability scores were used in the analyses presented here. To provide a measure of
alphabetic decoding ability, the Non-word Reading subtest from the Phonological
Assessment Battery (Frederickson, Frith, & Reason, 1997) was also used, and raw scores
on this measure are reported.
To assess the children’s phonological awareness two measures were used which
were selected as suitable for children in this age group: the Spoonerisms subtest
from the Phonological Assessment Battery (Frederickson et al., 1997), and the
Elision subtest from the Comprehensive Test of Phonological Processing (Wagner,
Torgesen, & Rashotte, 1999). It should be noted that because of the difference
in US and UK pronunciation of some of the items on the Elision subtest, which
requires the children to say a word when a specific phoneme has been ‘removed’,
items 13 and 16 were omitted from the test. Raw scores for both measures
are presented.
To assess the children’s knowledge of textisms, we developed a measure that
required the children to write their own text messages, as we wanted to elicit
spontaneous text messages from the children, but we had previously found considerable
difficulty getting children to remember to save, or record, or submit their record, of
their own actual text messages. So, we gave the children 10 scenarios, and asked them to
write the kind of text message they might write in each situation (full details are
provided in Appendix). For example:
. You’ve just seen your friend riding in his or her Dad’s brand new car [you decide
what kind] and it’s brilliant. You’d love to have a ride in it because it’s a really sporty,
fast one and you love cars. Your friend’s Dad is pretty good natured and very proud
of his car.
The elicited text messages were scored for types of textism used, and the ratio of
textisms to total words used. In order to compare our results more closely with the
analysis of older adolescents’ text messages reported by Thurlow (2003), we adopted,
and then adapted, his classification system, which has more categories than we had
previously used. Acronyms, for example, refer only to formal ones such as BBC, and

Initialisms is the label given other textisms such as LOL, laugh out loud where the same
principle has been used. We found that, unlike his ﬁndings, that we had many instances
of omission of apostrophes where they were appropriate, so we added that as
an additional category. If more than one alteration was employed in a single word,
we categorized on the basis of the ﬁrst change made. The 12 categories we used were
as follows:
. Shortenings (bro, sis, tues)
. Contractions (txt, plz, hmwrk)
. G-clippings (swimmin, goin, comin)
. Other clippings (hav, wil, couldn)
. Omitted apostrophes (cant, wont, dads)
. Acronyms (BBC, UK)
. Initialisms (ttfn, lol, tb)
. Symbols (@, & ,:-o)
. Letter/number homophones (2moro, l8r, wuu2)
. Misspellings (comming, are [for our], bolinase)
. Non-conventional spellings (fone, rite, skool)
. Accent stylization (wiv, elp [help], anuva)
Informed parental consent was obtained for all children prior to participation.
All children were briefed about the nature of the study and were advised that they did
not have to complete any assessment that they did not wish to. All children were
assessed individually in a quiet area of the school and the order of the tasks was
randomized to minimize order effects.
The children were tested in three sessions of approximately 20 minutes, spread over
3 days that were separated by up to a week, according to the convenience of the
participating schools. The children and schools were debriefed at the conclusion of the
study and thanked for their participation, but received no direct reward for
participation.
Results
Table 1 presents the summary statistics for the children’s scores on each of the main
measures taken in this study. It can be seen that a wide range of abilities was obtained.
Table 1. Summary statistics for all measures
Variable Mean SD Minimum Maximum
BPVS II vocabulary standard score (N ¼ 84) 102.46 16.41 47 139
BAS II digit span forward ability score (N ¼ 85) 146.12 18.59 88 194
BAS II digit span backward ability score (N ¼ 86) 116.77 22.79 59 190
BAS II word reading ability score (N ¼ 86) 152.28 25.92 31 187
BAS II spelling ability score (N ¼ 80) 106.93 14.01 55 141
PhAB non-word reading raw score (N ¼ 87) 16.76 4.10 2 20
PhAB spoonerisms raw score (N ¼ 87) 20.86 5.52 0 28
CTOPP elision raw score (N ¼ 86) 14.09 3.27 3 18
Ratio of textisms to words used in scenarios 0.34 0.17 0.04 0.79

The participants had vocabulary levels typical for their age (mean 102.5, SD ¼ 16:4).
Mean reading and spelling scores equated to the attainment expected of a child of 11; 3
and 10; 3, respectively, which is in line with or better than what we would expect of the
children in this sample. It should be noted that the use of scenarios to elicit text
messages in this study has resulted in a lower (and arguably more realistic) level of
textism use than has been previously observed, with the density measure indicating
a ratio of .34 (compared to .58 and .50 noted by Plester et al., in press). A gender
difference was observed, as girls had a higher ratio of textisms to total words than
boys, Fð1; 76Þ ¼ 6:38, p , :05. The girls’ mean ratio was .38 (.16) and the boys’ ratio
was .28 (.17).
Individual difference measures associated with literacy and textism measures
Pearson correlation coefficients were calculated between the measure of text
knowledge, age, how old the children were when they got their first mobile phone
and the various cognitive and literacy-related measures (see Table 2). In addition to the
original measures, two composite measures were calculated, a composite cognitive
score, comprising vocabulary, and digit span forward and backward z scores; a
composite phonological and alphabetic decoding score, comprising phoneme elision,
and spoonerisms z scores, along with non-word reading. Table 2 shows that these
individual measures are strongly related within each composite measure.
Table 2 shows that the children’s age was correlated only with the age at which they
received their first phone. Table 2 has also identified a number of marginally significant
correlations. The age of first phone was either significantly or marginally associated with
all of the reading skill and spelling measures, although it was not associated with the
cognitive cluster of measures. The measure of text language skill was associated either
significantly or marginally with word reading and spoonerisms, and with that, the
composite phonological score.
To assess whether the children’s age, vocabulary, short-term memory, phonological
awareness, and decoding skill, or length of time owning a mobile phone may explain the
observed relationship between word reading ability and children’s use of textisms,
structured multiple regression analyses were conducted and the results are shown in
Tables 3 and 4. Age was used as the first step in the first analysis, to verify the apparent
lack of relationship between it and other measures, and age of first phone was entered
first in the second analysis.
It can be seen that despite this very conservative analysis, the children’s knowledge
of textisms was able to account for a significant amount of variance in word reading
scores which was additional to that accounted for by vocabulary, phonological
awareness, alphabetic decoding ability, short-term memory, the children’s current age,
and the age at which the children got their first mobile phone.
Analysis by types of textisms used
In addition to our central analyses of variables predicting word reading, we also looked
at how various types of textisms were associated with literacy measures. Table 5
summarizes the children’s use of the 12 types of textisms used by the children in
response to the scenarios given. It can be seen that most of the children used
contractions, letter/number homophones, non-conventional spellings, and accent
stylizations, with homophones and accent stylizations being used frequently when they
were used, compared to the use of other forms.

Table2.Pearsoncorrelationsbetweenmeasureoftextismknowledge,howlongusingphone,andvariousindividualcognitiveandliteracymeasures
Age
Ageof
first
phone
Digitspan
forward
Digitspan
backward
BPVS
vocabulary
Composite
cognitive
score
Non-word
reading
Phoneme
elisionSpoonerisms
Composite
phonological
score
BASII
spelling
ability
score
BASIIword
readingability
score
Age
Ageoffirstphone.366**
Digitspanforward.1522.057
Digitspanbackward2.0782.179.317**
BPVSvocabulary.0302.139.195þ
p¼:094
.298**
Composite
cognitivescore
.0382.136.802**.821**.303**
Non-wordreading2.1172.215þ
p¼:055
.257*.378**.289*.388**
Phonemeelision.0302.212þ
p¼:063
.301**.529**.489**.516**.332**
Spoonerisms2.1122.276*.374**.510**.562**.547**.538**.613**
Composite
phonological
score
2.0682.293**.373**.541**.486**.593**.486**.897**.899**
BASIIspelling
abilityscore
2.1662.212þ
p¼:073
.221þ
p¼:066
.515**.304*.463**.627**.319**.534**.475**
BASIIwordreading
abilityscore
2.139.273*.203þ
p¼:077
.461**.506**.414**.638**.593**.712**.732**.701**
Ratiooftextisms
tototalwords
inscenarios
.1002.189.010.011.199.016.081.167.227þ
p¼:057
.213þ
p¼:076
.135.298*
*p#:05;**p#:01;þ
marginallysignificant,p,:10.

As not all children used all these various forms of textism, non-parametric
correlation coefficients were calculated between use of these different forms of textism
and the word reading and spelling measures. These are presented in Table 6. It can
been seen that there are fewer significant relationships between spelling and the
textisms compared to word reading and textisms, and that the strength of those
relationships is also weaker than those observed for word reading. For word reading
Table 4. A sequential regression analysis with children’s word reading ability scores entered as the
criterion variable
Model 1 R2
Change F Change p
Age of first phone .073 4.993 .029
Age of first phone, memory, vocabulary .484 33.316 ,.001
Age of first phone, memory, vocabulary,
non-word reading, phonological awareness
.042 6.253 .015
Age, memory, vocabulary, non-word reading,
phonological awareness, ratio of textisms to total words
.029 4.661 .035
Table 5. Summary statistics for the 12 types of textisms used in elicited texts with scenarios (NB Means
are based on those children who used that type of textism rather than whole sample and indicate how
many were used on average by those children over the 10 scenarios)
Mean SD Minimum Maximum
Shortenings (N ¼ 48) 2.00 1.30 1.00 8.00
Contractions (N ¼ 74) 9.01 10.24 1.00 53.00
G-clippings (N ¼ 40) 2.33 2.12 1.00 12.00
Other clippings (N ¼ 59) 3.49 2.8 1.00 10.00
Missing apostrophes (N ¼ 61) 3.23 2.49 1.00 12.00
Acronyms (N ¼ 1) 1.00 – 1.00 1.00
Initialisms (N ¼ 26) 2.88 4.26 1.00 21.00
Symbols (N ¼ 33) 4.30 3.89 1.00 15.00
Letter/number homophones (N ¼ 72) 13.18 8.87 1.00 34.00
Misspellings (N ¼ 51) 3.04 2.28 1.00 11.00
Non-conventional spellings (N ¼ 74) 6.96 6.59 1.00 39.00
Accent stylization (N ¼ 71) 13.28 9.61 1.00 38.00
Table 3. A sequential regression analysis with children’s word reading ability scores entered as the
criterion variable
Model 1 R2
Change F Change p
Age .000 0.028 .867
Age, memory, vocabulary .420 23.944 ,.001
Age, memory, vocabulary, non-word reading,
phonological awareness
.124 17.616 ,.001
Age, memory, vocabulary, non-word reading, phonological
awareness, ratio of textisms to total words
.037 5.594 .021

ability, the strongest relationships were observed for use of homophones, rsð78Þ ¼ :421,
p , :001, and accent stylizations rsð78Þ ¼ :507, p , :001, both phonologically based
types of textism.
Discussion
This study has examined the relationship, in 10- to 12-year-old children, between usage
of text message abbreviations (‘textisms’) and school literacy attainment. As expected,
we found associations between textism use and phonological awareness. What is most
important, the extent of children’s textism use was able to predict significant variance
in their word reading ability after taking into account age, individual differences in
vocabulary, working memory, phonological awareness, non-word reading ability, and
the age at which participants obtained their first mobile phone. This suggests that
children’s use of textisms is not only positively associated with word reading ability, but
that it may be contributing to reading development in a way that goes beyond simple
phonologically based explanations.
We acknowledge that correlational analyses cannot lead to a conclusion that
experience and skill with texting actively contributes to children’s word reading ability.
That experience and skill can, however, contribute to the prediction of their word
reading ability independently of the other measures used. It indicates that texting
experience and skill are deserving of further study, and require longitudinal study.
To draw even stronger causal conclusions would require experimental intervention,
but there are ethical and pragmatic concerns that urge caution in any research that
might be seen as encouraging mobile phone use in younger children.
It will be noted that there was no association found between overall textism use
and the children’s spelling and non-word reading scores. This suggests that, as anti-
cipated, at this stage of development there is no evidence of a detrimental effect of
textisms exposure on conventional spelling. This finding is compatible with the conclu-
sions of Ehri et al. (1988) that exposure to misspellings need not compromise children’s
learning of correct spelling. Instead, we would argue that many of the children’s
textisms reveal an understanding of ‘conventional’ letter-sound correspondences and
Table 6. Spearman correlation coefficients between reading (N ¼ 78) and spelling measures (N ¼ 72)
and the different forms of textism observed in the study
Word reading Spelling
Shortenings .133 .261*
Contractions .328** .179
G-clippings .362** .268*
Other clippings .205 .148
Missing apostrophes .199 .202
Initialisms .062 .005
Symbols .386** .277*
Letter/number homophones .421** .221
Misspellings 2.343** 2.269*
Non-conventional spellings .234* .146
Accent stylisation .507** .345**
*p , :05; **p , :01.

orthographic rules present in English, even though the resultant spellings are viewed
as unconventional. For example ‘nite’ as an alternative to ‘night’ does not break any
English language conventions, as it borrows the orthographic form from ‘bite’. The use
of letter and number homophones also reveals a creative recognition of phonological
similarity.
However, perhaps we might have expected evidence of a stronger positive
association between textisms use and the measures of spelling and non-word reading.
This may be because both spelling and non-word reading require alphabetic decoding
skills, whereas word reading can be tackled by accessing a learned sight vocabulary of
words that can be read without recourse to letter by letter decoding or recoding. Sight
vocabularies are typically built up through experience with text, and so it may be that
the overall pattern of associations found in this study is indicating that at least part of the
contribution that textisms are making to children’s reading development is explained by
the additional contact with text that mobile phones are also affording the children.
The strong associations between age of first phone ownership and reading skill
measures bears this out. This would certainly be compatible with the findings of
Stanovich (1986), Cunningham and Stanovich (1990), Cipielewski and Stanovich
(1992), who have established that experience with text contributes independently to
reading ability. But the modest correlations between text language skill and other
measures require explanation. Although textism use was not strongly associated with
measures other than spoonerisms and composite phonological score, and word reading,
it did contribute independently to predicting word reading ability when other measures
were accounted for. Text language use is seemingly contributing to reading in a way that
may not be fully reflected in the measures of language and cognitive skill we have used.
It is worth pausing to consider how text and IM language has been characterized
by various authors as playful, ludic, (Crystal, 2006a), comfortable (O’Connor, 2005),
vigorous, and ‘writing as recreation rather than work’ (Helderman, 2003). Texting is fun,
and owning a mobile phone gives children access to a technology that they enjoy using,
and which also provides them with the opportunity to engage in additional (and
sometimes frequent) written language activity. The textisms themselves are creative
expressions of children’s engagement with language and they are motivated to become
literate in their use in order to communicate with their friends rapidly and effectively,
and in a way that they feel in control of. The ludic hypothesis is strengthened by
the fact that textism use was associated most strongly with spoonerism scores.
Creating spoonerisms has a clear sense of play in it.
There is less judgment attached to text messaging than to other forms of writing –
children can write as conventionally or unconventionally as they wish, with or without
punctuation or capitalization, and all spellings are legitimate as long as the convention
for ‘reading’ them is an established one that will enable the recipient to understand it.
This point in itself is borne out by data showing that the most commonly used forms
of textism were those that were more phonologically based, whereas more symbolic
forms were less common, and as Sutherland (2002) observes, texting has only a
few hieroglyphs (codes comprehensible only to initiates). Glossaries of text language
(e.g. Crystal, 2004; Ihnatko, 1997) give no frequency data, nor did Thurlow’s (2003)
taxonomy, but we have seen here that the more mysterious textisms do not appear
often, at least with pre-teens.
If we look at the different forms of text abbreviation observed in this study, and how
their use was correlated with the literacy measures, we observe some interesting
associations that also suggest that the association between textism use and literacy is not

just about phonological awareness. For example, there was a high correlation between
use of symbols and both reading and spelling scores. These symbolic forms have to have
their meanings learned, and so these may be indicative of the children’s ability to learn
new forms of orthographic representation, and without the corruption of already
learned orthographic forms.
The textism ratio showed a sex difference with girls showing greater use of textisms
relative to boys. This would be compatible with findings regarding older adolescents
and adults (Reid & Reid, 2005), that males’ messages are intended, by and large, to
convey information, and in this, are shorter and more direct than females’, which are
more frequently intended to sustain relationships and share commentary. Therefore girls
will use more symbolic forms to convey emotion (such as ‘x’ as the end of messages, and
emoticons), and it could be argued that the use of textisms compared to real words is, in
itself, used to establish and maintain relations between speakers, given that so many are
shorthand terms for phrases about emoting (e.g. ‘lol’, ‘omg’) and relating (ttfn, CUL8R).
We have shown that the children who scored the highest in the use of accent
stylization also scored highest in standard literacy measures. The element of fun
with language is also captured in the high frequency of accent stylization textisms.
These engage the children in using phoneme–grapheme conversion rules to create
orthographic representations of the language register normally only spoken, ‘street
speak’ language, informal and used as a sign of belonging to an in-group for whom the
permission rules allow such language use. When questioned informally about using that
register of language in schoolwork, the children found even the suggestion ludicrous,
suggesting that texting ‘street speak’ indicates metalinguistic awareness.
They are aware of the two registers of language, and of the boundary conditions
surrounding the appropriateness of use of each. When we have seen linguistically
able children using an alternative register freely and appropriately, we might doubt
that publicized occurrences of text abbreviations in coursework or examinations
(Associated Press, 2007; Thurlow, 2006) are the result of children’s loss of standard
English proficiency, or even their not knowing the boundary conditions and permission
rules for their use. Other explanations might be sought, perhaps in deliberate flouting
of the permission rules, for any one of several possible reasons; or perhaps the
experienced texter’s mental representations of the divergent graphic forms expressing
the same word’s meaning and sound might be equally potent, and likely to emerge when
the meaning is cued. Young people’s comments suggest this could be an explanation
(e.g. Lee, 2002). If this were to be the case, remedial action would need to enhance the
student’s proof reading motivation and skill in order to spot such non-wilful intrusions.
Educators (O’Connor, 2005) have seen text and IM experience as valuable in raising
children’s awareness of the appropriateness of various registers of language, and
encouraged their use in the language teaching arena, but with explicit teaching about
the category boundaries and permission rules that apply (Helderman, 2003).
We found that some children in this study were given their first phone as young as
6 years of age, and that within a 2 year age range, the younger they were at time of
testing, the younger they were when they received their first phone. ‘Generation Txt’
(Thurlow, 2003) increasingly applies to younger and younger children. The age of first
phone was strongly associated with a number of measures of standard literacy, all in the
direction that suggests that experience with a mobile phone has been a positive factor in
literacy. This finding too calls for further exploration, in determining how experience
with mobile phones interacts with children’s other experience in charting the course of
their literacy development. Experience with other forms of computer mediated

communication, for example IM, e-mail, chat rooms, bulletin boards, websites such as
Myspace or Facebook, on-line games, might factor into children’s profile of literacies as
they become a more common feature of young people’s lives. Young adolescents
speaking of their digital technologies often mentioned these facilities alongside their
mobile phones (Kids Speak Out, 2007).
We acknowledge that the text messages we based our conclusions upon are not
naturalistic messages, being elicited in an experimental setting by the use of scenarios.
Generalization of findings to naturalistic texting should be cautious. The children here
were aware that the topic under investigation was texting, and if any situational
demands are evident in their messages, it is likely to be an excess of textism use in an
attempt to comply with perceived demands. That itself would be evidence of the
children’s awareness of the linguistic constraints of text literacy.
We have not explored the effects of socio-economic status, parental education, or
cultural values on the outcomes seen in this research, but further work might profitably
explore these with respect to the age of first phone ownership, the role of parents or
peers in engaging children in the texting skills, as well as early reading experience.
Formal exploration might follow of the relationship between children’s exposure to
texting and their exposure to other forms of print, such as is central to Stanovich’s work,
extending to exposure to other forms of digital text such as IM, e-mail, and educational
software, all of these being related to standard literacy measures.
Investigating in some detail the relationships between textism use and literacy
with the present sample of children has led us to conclude that there is no
compelling evidence to support the negative statements made in the media regarding
how children’s written language development is being disrupted by exposure to
text abbreviations. As Thurlow (2006) notes, although the collection of on-line and
paper glossaries and translation mechanisms might suggest that text literacy is about
the abandonment of conventional literacy, and selected anecdotes illustrate that point,
the elicited text messages written by this group of pre-teens would be almost
completely comprehensible to anyone willing to exercise phonological awareness,
and recognize texting as a written acknowledgement of speech, if not having all
features in common with speech. Most of the children’s use of symbols and initialisms
were uses of devices common to standard informal written English communication,
for example & @ xxx, ttfn.
In parallel with the lack of evidence found here for the demise of standard English
among the young, we have presented evidence that facility with text literacy is
positively associated with standard English literacy. As the possession of mobile phones
touches younger and younger children by the year, continuing research into the ways
using these phones contributes to developing linguistic competence will be very
important. The children studied here are already fairly well established in their written
language skills, but as more children receive phones near to the beginning of their
primary school years, the interaction between phone use and language skills may have a
different profile, and it will be important to know how we might best use texting and
other computer mediated communication in the children’s repertoire of choice to
enhance their language skill acquisition.
Acknowledgements
We thank the children and schools who supported and contributed to this study, and Ruth
Stronach and Deborah Felton who helped with the data collection.

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Appendix
Text message scenarios
Situation 1
It is Saturday morning, it is a sunny warm day, and you don’t have any plans, but you’d
like to go somewhere with your best friend. Your parents have told you its ok with them
if you go out with you friend.
Situation 2
You are on your way to meet your friend, waiting at the bus stop, and the bus has just
gone by and not stopped, so you are going to be late.
Situation 3
It is Tuesday. You just got home from school, and you have so much homework to do
that you don’t think you will be able to go to the club you usually go to on Tuesday
nights, but you know one of the others in the club will be coming by to pick you up.

[You decide what kind of club: swimming, judo, tennis, music, scouts, guides, and the
local youth club.]
Situation 4
Your best friend’s birthday is at the weekend, and he or she is having a party. [You decide
what kind of party]. You aren’t sure what you want to wear to look great, and another
friend is always good at helping you decide. You also aren’t sure what to get for a
present, and want to see if you might buy something together with this other friend if
that’s ok with him or her.
Situation 5
There is a new person in your class at school, and he or she hasn’t talked to anyone yet,
but you know that he or she is from another country somewhere. You think he or she
looks nice enough, but you’re not sure about just going up and talking to them. Your
best friend also would like to talk to them, but is a little unsure. Both of you feel silly
about feeling unsure because you’re usually conﬁdent. Your friend has just sent to a text
saying maybe together somehow you could get to know him or her, and wants to know
what you think.
Situation 6
Your sister’s cat was just hit by a car up the road from your house. It was killed instantly,
so you couldn’t even try to take it to the vet. You know she doesn’t know, because she
hasn’t come home from school yet, but you don’t want her to see it on the way home.
Situation 7
You know a secret [you make one up], and you’re dying to tell someone you can trust
not to tell anyone else.
Situation 8
Your friend’s Gran has just presented him or her with a home made jumper that she’s
worked really hard to knit, and you and your friend know that her arthritis makes it hard
for her to use her hands. But it’s a really awful and she’s going to insist that your friend
wears it. Your friend has sent you a text asking what he or she should do.
Situation 9
You’ve just had a text from your Mum. She’s in the middle of the supermarket and wants
to know what you’d like for dinner. She’s also forgotten to feed the dog and you know
he’s out of food.
Situation 10
You’ve just seen your friend riding in his or her Dad’s brand new car [you decide what
kind] and it’s brilliant. You’d love to have a ride because it’s a really sporty, fast one and
you love cars. Your friend’s Dad is pretty good natured and very proud of his car.

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