The relationship between students’ use of ICT for social communication and their computer and information literacy
Alkan and Meinck Large-scale Assess Educ
The relationship between students' use of ICT for social communication and their computer and information literacy
This study investigates the relationship between students' use of information and communication technology (ICT) for social communication and their computer and information literacy (CIL) scores. It also examines whether gender and socioeconomic background moderates this relationship. We utilized student data from IEA's International Computer and Information Study (ICILS) to build multivariate regression models for answering the research questions, and accounted for the complex sample structure of the data by using weights for all statistical analyses, employing jackknife repeated replication for variance estimation. Students who frequently use the internet for messaging and participation in social networks (i.e., at least once a week) scored on average 44 points higher than those who use ICT for the same purpose only less than once a week or never. The direction of this effect was the same in all 21 participating educational systems, the difference ranging from 19 to 75 points (always statistically significant). We continued the analysis by testing whether the relationship is moderated by gender; as girls use more often ICT for social communication and have higher CIL scores on average. After controlling for the gender effect the CIL scores between the two examined groups decreased only by 2 points on average. Even after including students' socio-economic background into the model, the difference in CIL between the two groups of interest declined only little-to 32 points on average across all countries. The difference remained to be statistically significant in all countries but one. The results suggest a strong relationship between students' CIL proficiency level and the frequency of their use of electronic devices for social communication; hence, respective skills needed at schools and later on at the workplace are reflected in their use outside of school and for socializing.
(e.g., Becker 1994; Hativa 1994; Kozma 1991; Kulik and Kulik 1987; Liao 1992;
Osunade 2003; Ryan 1991; Van Dusen and Worthren 1994; James and Lamb 2000; Attewell
and Battle 1999; Sivin-Kachala 1998; Weaver 2000; Weller 1996; Wenglinsky 1998)
et al. (2002) suggest that there is a positive relationship between the number of
computers available at school and students’ science achievement.
that computer use has no effect on students’ achievement in reading, mathematics,
science or social studies. There is also a number of studies that identified negative
relationships between computer use and student achievement
(Ravitz et al. 2002; Papanastasiou
who analysed the results of TIMSS, found a negative
relationship between computer use and achievement in a number of countries such as
Cyprus, Hong Kong and United States of America. According to this study, students
who use computers most frequently in the classroom were lowest achievers in TIMSS
Papanastasiou et al. (2005
) found that computer use
does not have a positive nor negative effect on students’ science achievement based on
PISA results, but the way of computer use affects science achievement.
Most of the international studies focused so far on the relation of ICT use and
students’ competencies in reading, science and mathematics. The amount of research
dedicated on computer and information literacy is very limited and most studies examine
mainly internet access and online use
(Olafsson et al. 2014)
. In the computer and
information literacy (CIL) area, the first cross-national study is ICILS
(Fraillon et al. 2014)
assesses the extent to which students know about, understand, and are able to use
information and communication technology (ICT). The main purpose of ICILS is to
determine how well students are prepared for study, work and life in the digital age. With the
information age the term “digital natives” was coined for the generation born in the early
1980s, also referred to as the first members of the millennial generation
In his article, Prensky claimed that “the arrival and rapid dissemination of digital
technology in the last decade of the twentieth century” had changed the way students think
and process information, making it difficult for them to excel academically being
exposed to outdated teaching methods. However, according to the ICILS results,
although students have had an increased amount of exposure to technology, it does not
necessarily imply that they are digital natives. In all the participating countries, on
average 17 % of the students did not even achieve the lowest level of CIL determined by the
study. On average, only 2 % of the students achieved the highest level with a maximum
of 5 % in Korea
(Fraillon et al. 2014)
This finding raises the question how so called digital natives use twenty first century
technology in daily life. It is known from the literature that age plays a significant role in the
usage of computers and internet. As shown in Fig. 1
(Zichuhr and Madden 2012)
, and Fig. 2
(TurkStat 2014) below, there was a steady increase in internet use across all age groups
in Turkey and the US. In the beginning of the current century, however, the younger age
groups use internet more often compared to the older age groups in both countries.
1 See Fraillon et al. 2014 for detailed explanations of the determined CIL levels.
Internet use by age group in Turkey
In most European countries, as shown in Fig. 3, more than 80 % of young people (aged
16–29) used a computer on a daily basis. In all countries, percentages of the daily use of
computers among young people is higher than for the whole population
Further, literature suggests that many children engage in a wide range of online
activities. ICT use by students has expanded to Internet, e-mail, chat, programming,
graphics, spreadsheet, online shopping, online searching for literature and other educational
materials. The students mostly use ICT for general purposes, i.e., communication, word
processing, entertainment, etc. rather than for educational means
According to Olafsson et al. (2014), the most common online activities of 9–16 years
olds in Europe are: using internet for school work (85 %), playing games (83 %),
watching video clips (76 %) and instant messaging (62 %). Communication via the internet is
ubiquitous; often schoolwork is accompanied by chatting and texting. A study published
Gokcearslan and Seferoglu (2005)
showed that—at that time—Turkish students’ main
focus is on playing games instead on learning activities.
The internet use has high rates among young people when it is compared to the whole
population in the EU-28 for basic skills such as using a search engine (94 %) or sending
an e-mail with attachments (87 %), while more than two-thirds of young people posted
messages online (72 %), just over half used the internet for calling people (53 %) and
around one-third (32 %) used peer-to-peer file sharing services. The proportion of young
people of posting messages online was 34 percentage points higher than the average for
the whole population
(Eurostat 2014; Fig. 4)
Already in 2003 Prensky reported that young Americans talk more than 10.000 h on
the phone and send more than 200.000 e-mails and text messages until the age of 21. A
study conducted in the US found that 80 % of online teens use social network sites,
Facebook being the most popular, with 93 % of those teens reporting its use
In 2014, according to number of active users, Facebook is the most popular social media
platform with 1184 billion users
. In 2015, Facebook is still most
popular social media platform among young people and 71 % of all teens from 13 to 17
use Facebook, 52 % of them use Instagram and 41 % use Snapchat. (Pew Research Center
“The use of social networks among children research report” focused on the use of
social media among 9–16 year olds in Turkey showed that 85 % of students have
computers at home, 70 % of all students get online at least once a day and 66 % use social
media at least once a day, spending 72 min on average. This shows that most of the time
spent on internet is dedicated to social media. The same study shows that 99 % of the
children who have a social media account use Facebook. 60 % of the children reported
that they don’t study enough because of spending too much time on Facebook, 25 % of
them said that they spend less time with their parents and friends
The most common online social activities for young people in the EU-28 in 2014 included
sending and receiving e-mails (86 %) and participating on social networking sites (82 %)—
for example, Facebook or Twitter, by creating a user profile, posting messages or making
other contributions—while close to half (47 %) of all young people in the EU-28 uploaded
self-created content, such as photos, videos or text to the internet
Summarizing the literature, the high importance of students’ use of ICT for social
communication in their daily life is evident. But does this type of ICT use enhance students’
CIL skills? Or, does it even rather have a negative effect, because less time remains for
“worthwhile” computer usage, such as learning activities? This study examines the
relationship between students’ use of ICT for social communication and their computer and
information literacy and attempts to contribute to a deeper understanding of this relationship.
Methods and data sources
Students’ data of ICILS was used to explore the hypotheses. ICILS gathered data from
almost 60,000 Grade 8 (or equivalent) students and 35,000 teachers in more than 3300
schools from 21 countries or education systems within countries. These data were
augmented by contextual data collected from school ICT-coordinators, school principals,
and the ICILS national research centres.
Students completed a computer-based test of CIL that consisted of questions and tasks
presented in four 30-min modules. Each student completed two modules randomly
allocated from the set of four so that the total assessment time for each student was 1 h.
After completing the two test modules, students answered (again on computer) a
30-min questionnaire. It included questions relating to students’ background
characteristics, their experience and use of computers and ICT to complete a range of different
tasks in school and out of school, and their attitudes toward using computers and ICT
(Fraillon et al. 2014)
IEA’s IDB Analyzer was utilized for all statistical analyses, including the estimation of
percentages, means and regression models. The IDB analyzer takes the complex data
structure of ICILS data into account by applying sampling weights and employing
jackknife repeated replication for variance estimation. Comparisons between dependent
samples were conducted using regression models in order to account for the covariance
between the comparative groups.
We first analysed the relationship between students’ CIL score and their use of ICT for
social communication. In the ICILS study, the student questionnaire included three
questions that require students to rate the frequencies of their use of ICT applications.
From these questions four scales were derived. One of them was “Students’ use of ICT
for Social Communication” (S_USECOM). The students were asked to identify the
frequency with which they were using the internet for various communication and
information exchange activities outside of school. The response categories were “never”, “less
than once a month”, “at least once a week but not every day” and “every day”. S_USECOM
had an average reliability of 0.74
(Fraillon et al. 2015)
The index variable (“S_USECOM”) consists of the following items:
How often do you use the Internet outside of school for each of the following activities?
1. Posting comments to online profiles or blogs.
2. Uploading images or videos to an [online profile] or [online community] (for
example. Facebook or YouTube).
3. Using voice chat (for example Skype) to chat with friends or family online.
4. Communicating with others using messaging or social networks [for example instant
messaging or (status updates)].
We could identify indeed a relationship between students’ CIL score and their use of
ICT for social communication: in all educational systems participating in ICILS (further
for simplicity referred to as “countries”), the CIL score increased along with an increase
of students’ scale score in “Use of ICT for social communication”. This relationship was
statistically significant in 16 out of 21 countries. However, the relation was weak; the
explained variance of the CIL score was less than 10 % in most countries. We continued
the analysis by investigating further the relationship between CIL and each of the four
variables constructing the scale score for “Use of ICT for social communication”.
Posting comments to online profiles or blogs
There were no consistent patterns for relations between the reported frequencies for this
variable in most countries except for Chile, Thailand and Turkey—the countries with
relatively low CIL average scores. In these three countries, the CIL score increased along
with an increasing frequency of postings.
Uploading images or videos to an [online profile] or [online community] (for
example. facebook or youtube)
Interestingly, students with a medium frequency of ICT use for uploading images or
videos had an average CIL score of 20 more points than those who reported to either never
do that or do it every day. This pattern could be observed in all countries and was
statistically significant in all countries but three (Republic of Korea, Turkey,
Canada—Newfoundland and Labrador).
Using voice chat (for example Skype) to chat with friends or family online
No clear patterns could be identified for relationships between the CIL scores and
frequencies of ICT usage for voice chats.
Communicating with others using messaging or social networks [for example
instant messaging or (status updates)]
Apparently this variable had the closest relationship with CIL among the variables
constructing the index variable (“S_USECOM”): as shown in Fig. 5, the more frequent
students use ICT for communication using messaging or social networks the higher was
their CIL score, a finding that generally holds in all countries. Looking at the
cross-country average, mean CIL scores of students who never use the internet for communication
in Fig. 5, CIL scores of students reporting to use ICT for communication at least once
a week or even every day were rather close to each other; also, no large differences in
CIL scores occurred for students using ICT for communication less than once a week
(or never). Therefore we collapsed the respective categories accordingly. This procedure
split the countries’ target populations into two groups of varying proportions, as can be
seen in Fig. 6. On average, three-fourth of the students use the Internet for
communication more than once a week. This proportion is less in Thailand and Turkey.
Comparing the resulting two groups of students, we found an average difference in
CIL scores of 44 points on favor of students using ICT for social communication more
frequently. The direction of the effect was the same in all countries and ranged from 19
points difference in Switzerland to as much as 75 points in the Slovak Republic (refer to
Table 2, Model 1, coefficients of E-communication). In all countries, the difference was
found to be statistically significant. Since these results were rather striking, we wondered
if this effect was moderated by other variables. Consequently we set up various
multivariate regression models in order to control for such effects.
* Statistically significant (p < 0.05) coefficients
a Met guidelines for sampling participation rates only after replacement schools were included
b Country surveyed the same cohort of students but at the beginning of the next school year
c Due to missing occupation codes no SES variable was derived, hence Model 3 was not applicable
Gender as moderating variable
It is known from the literature that girls spend on average more time on social network
sites and use them more actively than boys
(Duggan and Brenner 2013)
reported that some 95 % of teenagers use the internet in the US. 42 % of girls who use
the internet report to video-chat, while only about a third of boys engage in that
activity. Girls are also more active in their texting and mobile communication behaviours
(Lenhart et al. 2010)
. Our own study confirms this finding for all ICILS countries as can
be seen in Fig. 7—except for Turkey. Interestingly, in Turkey (highlighted by the black
arrow in Fig. 7) boys report to use the Internet for social communication more often
than girls. The differences of the gender group percentages are statistically significant in
Although gender is a major determinant in CIL scores of ICILS, it did hardly
moderate the difference in CIL scores between the two groups presented in Fig. 5. The group
differences remained significant in all countries (see Model 2 in Table 2, coefficients of
Socio-economic background as moderating variable
In a next step we included the national index of students’ socio-economic background
(variable “S_NISB”) into the model, reasoning that the availability of internet access and
communication devices may depend on the socio-economic status (SES) of the students.
The “digital divide”—referring to the gap between those who do and those who do not
have access to ICT’s
—generally affects individuals who are
unemployed or in low-skilled occupations, and who have a low income and/or a low level of
education. Students from families with a lower SES tend to be less confident and
capable in navigating the Web to find credible information
support the theory that SES influences students’ access (exposure) to
ICT and internet. The findings of
suggest that even when controlling
for basic Internet access, among a group of young adults, SES is an important predictor
of how people are incorporating the Web into their everyday lives.
showed that SES had a direct positive relationship with computer experience and an
indirect negative relationship with computer anxiety. The findings are supportive of the
digital divide and they imply that information technology may in fact be increasing
inequalities among social strata in their access to employment opportunities.
After controlling for both, gender and SES, the difference in CIL between our two
groups of interest declined to 32 points on average across all countries. However, the
difference remained to be statistically significant in all countries but one (Denmark).
Table 2 presents regression coefficients of all three discussed models; Fig. 8 presents
the differences in CIL scores of students using ICT for social communication more vs.
less than once a week for all three considered models (coefficient of “E-communication”
in Table 2). Evidently, this difference is hardly moderated in any country by gender, while
the socio-economic status plays a larger role. In twelve out of twenty countries, after
controlling for gender and SES, the examined difference in the CIL score decreases
by more than 10 points. Only in Switzerland neither SES nor gender seemed to be
associated with the difference in CIL scores between the two groups of interest, i.e., the
coefficient of E-communication remains constant across the three models.
Further variables with potential moderating effects
We also investigated the effect of further variables that may have moderated the found
relationship and thereby could have affected the presented relationship in significant
ways. We identified such variables based on evidence from the literature, evidence from
(Fraillon et al. 2014)
or simply by applying common sense. It would exceed the
purpose of this paper to present all details of these analyses; however, the following
paragraphs give some major findings.
While girls use ICT more often for social communication, boys use it more often for
(Rideout and Foehr 2010)
. This is also evident from ICILS data and is
presented as cross-country average in Fig. 9. The patterns are similar for all participating
countries. However, there was no general relation between using ICT for playing games
and CIL except for Turkey and Thailand, where an increased frequency of gaming was
related with increasing CIL scores.
Further, one may argue that the overall use of computers could have a moderating
effect on the studied relationship. However, including the respective variable into the
regression model proofed to not change much the effect of ICT use for social
communication on CIL and also did not enhance the explained variance of the CIL score
Discussion and conclusions
The arrival and rapid dissemination of digital technology in the last decade of the
twentieth century raises the question how so called digital natives use technology in daily life
and what relevant skills they need to develop in order to participate effectively in the
digital age. From the literature, the high importance of students’ use of ICT for social
communication in their daily life is evident. In this paper we tried to answer the question
if this type of ICT use enhances students’ CIL skills or if it—on the opposite—perhaps
even rather has a negative effect, because less time remains for “worthwhile” computer
usage, such as learning activities.
We first analyzed the relationship between students’ CIL score and their use of ICT for
social communication. The CIL score increased along with an increase of students’ scale
score in “Use of ICT for social communication” in all educational systems participating
in ICILS. This relationship was statistically significant in 16 out of 21 countries.
However, the relation was weak. We continued the analysis by investigating further the
relationship between CIL and each of the four variables constructing the index “Use of ICT
for social communication”. We found out that the variable which has the closest
relationship with CIL was “Communicating with others using messaging or social networks [for
example instant messaging or (status updates)]”, while other variables comprising the
index showed different or no patterns related with CIL.
For accommodating further analysis on this variable, we decided to split students’ data
into two groups. We collapsed the five original categories of the variable into two
categories, reflecting the use of messaging or social networks “at least once a week or even
every day” versus “less than once a week (or never)”.
Comparing the resulting two groups of students, we found a large average difference
in CIL scores (44 points) favoring students using ICT for social communication more
frequently. The direction of the effect was the same in all countries; the difference ranged
from 19 points in Switzerland to as much as 75 points in the Slovak Republic. Since these
results were rather striking, we examined whether this effect was moderated by other
variables such as SES and Gender. We found however that the moderating effect of these
variables on the observed relationship was weak or even negligible in all participating
countries. In other words, the relation between the use of ICT for communicating with
others using messaging or social networks and CIL scores was still high and consistent
across countries when controlling for SES and Gender.
This positive and cross-nationally observed relationship was rather unexpected,
especially because the relationship between the communication index created by ICILS and
the CIL scores was weak. Trying to understand this phenomenon, we considered the
nature of messaging and participation in social networks. We see that it actually includes
posting comments, uploading and downloading images and videos—hence, these
features are no different than the separate items creating the social communication index.
In fact the single item basically contains the other index items. Possibly the written
communication portion included makes the difference, or the actual widespread of
activities involved in messaging/electronic social networking explains the indistinct positive
relationship with CIL. In future cycles of ICILS it may be worthwhile to review the index
To explore this phenomenon further, we also should focus on the CIL construct. As
Fraillon et al. (2014) pointed out in the ICILS international report, the CIL construct
was conceptualized in terms of two strands:
Strand 1; collecting and managing information, focuses on the receptive and
organizational elements of information processing and management,
Strand 2; producing and exchanging information, focuses on using computers as
productive tools for thinking, creating, and communicating.
When we consider the interactive nature of social media, it can be assumed that they
provide students with a medium for collecting and managing information as
anticipated in Strand 1 and also for producing and exchanging information as conceptualized
in Strand 2. Hence, this item seems truly be related with both strands of the CIL
construct, which may be one reason for the close relationship. Lacking of an
experimental design, this study cannot make causal inferences on the relation between CIL and
e-communication. Therefore we cannot conclude if frequent use of ICT for
communication enhances CIL skills, or if in turn students with high CIL use more frequently ICT
for social communication.
Future studies should also monitor the use of social networks in education further.
Students should not be expected to accomplish high skills in using information and
computer technology and at the same time expect them to keep this aspect of their
personality outside of their social life. Rather, it is worth to explore the additional
learning opportunities arising from electronic tools and media out- but also and especially
inside schools. According to findings from Fraillon et al. (2014), there is a need in many
countries to equip teachers with the respective knowledge to use ICT (including social
communication tools) in their teaching. Utilizing social media for teaching may hold the
potential to increase CIL for all students independently from their gender and SES
backgrounds; and thereby avoid that students with low CIL or limited access to ICT may
increasingly lack opportunities to actively participate in the modern society.
As a matter of fact, nowadays messaging and Facebook or other social networks
became a part of students’ daily life. As parents, teachers and educators, our
responsibility is to help our children to benefit from social networks educationally.
MA developed the research questions, conducted the literature research and drafted significant parts of the manuscript.
SM developed the research design, conducted data compilation, the statistical analysis and interpretation of results
and drafted significant parts of the manuscript. Both authors have given final approval of the manuscript version to be
published and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy
or integrity of any part of the work are appropriately investigated and resolved. All authors read and approved the final
1 Ministry of National Education, Ankara, Turkey. 2 IEA Data Processing and Research Center, Hamburg, Germany.
The authors are thankful to Diego Cortes for his very useful comments while reviewing this paper.
The authors declare that they have no competing interests.
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