Mobile phone placement during lectures and dependency
on LINE and text messaging: Survey of students at a
women’s university in Japan
Keywords:
LINE messaging, text messaging, mobile phone dependency, classroom behavior, higher education

Yuuki KATO, Sagami Women’s University
Shogo KATO, Tokyo Woman’s Christian University

Abstract
This study measured the dependency on text messaging of students in lectures at a women’s
university in Japan, comparing students who placed their mobile phone on their desk duringlectures with those who did not do so. Dependency was measured by using a text-message
dependency scale. Dependency on LINE messaging was measured by the same scale with “text”
replaced by “LINE” in each question. The results of the questionnaire survey showed a significant
difference in “emotional reaction,” one of the three subscales of the scale used in the study,
between students who placed their mobile phone on their desk and those who did not: the LINE
messaging dependency score was higher among those who did. Also, in each subscale score andin the total of those scores, dependency on LINE messaging was significantly higher thandependency on text messaging for both students who placed their mobile phones on their desks
during lectures and those who did not do so.

28

Journal of Socio-Informatics Vol. 8 No. 1 Feb. 2016

top, but it can be said that, at least as a background

1. Introduction

to this study, it is not difficult to find students
Previous studies discussed the use of personal

using mobile phones on desks during lectures at

laptop computers during university lecture.

Japanese universities in the present day.

Although these studies pointed out the negative

Accordingly, we undertook an investigation ofeffect of student laptop use during lectures,the use of mobile phones during lectures. In afinding that it was a distraction from the lectures

preliminary investigation in which 21 Japanese(Fang 2009; Fried 2008; Hembrooke and Gay

university

2003),

different

studies

showedstudents

participated,

52.4％

of

increased

students responded that they “use mobile phones

learning effectiveness through the appropriate

during lectures,” and 42.9％ of students said thatuse of laptops during lectures (Barak et al. 2006;

they “don’t feel embarrassed about operating

Demb et al. 2004; Gay et al. 2001). In modern

mobile phones during lectures (Tachino et al.

university lecture halls, the use of not only laptop2012).” In a study by Tachino et al. (2013a), a

computers but also of mobile phones (including

questionnaire was distributed to 20 students who

smart phones) by students in lectures has also

placed their mobile phones on their desks during

been frequently observed (Amali et al. 2012;

an exercise class in a computer lab room. The

Campbell 2006; Hammer et al. 2010; McCoy 2013;

students were asked to answer two questions: a

Wei and Wang 2010; Wei et al. 2012).

free response regarding the “reason for placing

In the past, we saw almost no use of laptop

the mobile phone on the desk,” and a yes or nocomputers by students in lectures at Japanese

question as to the “sense of guilt about placing auniversities, as is seen in other countries, but themobile phone on the desk.” The results showedpersonal use of mobile phones by students duringthat the most common reason for placing a

lectures was a common sight (Tachino et al.

mobile phone on the desk, given by 7 students,2012). In the past, use of mobile phones by

was “for the purpose of receiving contact,” and 9

students during lectures was conducted “underof the students responded that they felt no sense

the desk,” that is, out of sight of the instructorof guilt about placing their phone on their desk

(Matsushita 2007). However, we observed that

(Tachino et al. 2013a). Also, in Tachino et al.

the personal use of mobile phones by students(2013b) and Tachino et al. (2014), a yes/noduring lectures has changed owing to thequestionnaire was given to 237 students, asking

widespread use of smart phones, which was

about their “experience of placing a mobile phone

sparked in Japan by the introduction of theon the desk during lectures.” Among respondents,

iPhone in 2008. In other words, the shift in the

67.9％ said that they placed their phone on theirpersonal use of mobile phones to easy “on thedesk during regular lectures, and 30.8％ said thatdesk” use was made possible by the fact that thethey did so even in lectures where mobile phonebacks of smart phones are flat and that theuse was prohibited (Tachino et al. 2013b; Tachinophones are usually operated by touchscreen. It

et al. 2014). The common finding of thesecannot be said that the shape and design of smart

preliminary investigations is that most university

phones is the sole cause for the change fromstudents who use mobile phones during lectures

hiding one’s phone under the desk to using it onplace their phones on their desks for the purpose
29

Mobile phone placement during lectures and dependency on LINE and text messaging: Survey of students at a women’s university in Japan

of using their phone as a communication tool.

KATO et al(Kato et al 2012, 2013; Kato et al. 2013). Typically,

Building on the preliminary investigations

a speedy response is desired in mobile text

mentioned above, our current investigative study

message communications. Students are aware(Kato and Kato 2016) surveyed university aboutthat this expectation should be modified during

the use of mobile phones in lecture. The

classes. However, when there is pressure to notquestionnaire began with a question regarding

wait, or to keep others from waiting, until class

whether the student had their mobile phone

has finished, and in situations where there areplaced on their desk “now” (from the time ofrules restricting the use of mobile phones, a

distribution of the questionnaire to about 30

sense of unease among students demonstrates aminutes after the beginning of the class). The

clear dependency on mobile text message

analysis

students

communication. Yoshida et al. (2005) writes,

according to the answer on that question and(translated from Japanese) : “In recent years, thecomparing the other responses between groups.

use of mobile phones without respect of time or

The results of this study are given below. It wasplace, and the prioritization of mobile text

seen that the ratio of students who placed theirmessaging over communication with others rightmobile phone on their desk was 64.5％ and thatin front of them, is becoming a significant

there was a higher probability among those who

dependency issue with mobile text messaging

did so to use their phones during lessons toamong young people.”

proceededbygrouping

check phone, text, and LINE message content

Long hours of use was named as the primary

and to respond (by replying, etc.) to thosecause of “Internet dependency” according to a 2013

messages; further, those who placed their phone

Ministry of Internal Affairs and Communications

on their desk felt more unease when rules

survey targeting participants between upper

restricting the use of mobile phones during

primary school age and age 25 (Ministry ofclasses were in place (Kato and Kato 2016). An

Internal Affairs and Communications, Japan

additional pattern was seen: in mobile phone2014). According to the survey, 68.8％ of highcommunication by students during classes, text-

school students and 65.6％ of university students

based communication was an easy choice. In

responded that they had taken away from time

particular, the LINE application, which is a

dedicated for other activities in order to make(primarily smart phone-based) communication

more time for Internet use, mainly from sleeping

tool for free chat and voice over IP telephone(48.1％ of high school students and 47.5％ ofcalls, was used more often than standard mobile

university students) and study (46.6％ of hightext messaging (Hereafter, “LINE messaging”

school students and 34.6％ of university students)

will refer to LINE’s chat function, called “Talk”(Ministry of Internal Affairs and Communications,in-app) (Kato and Kato 2016).

Japan 2014). Many related studies point out thatusing

the existence of adverse effects on normal life

mobile phones during classes differs from

Althoughpersonal

communication

activities is one possible indicator of dependency

standard class behavior (Ling 2004), one reason(Okada 2014). It has been noted that women are

this behavior occurs is because students desire

far more likely to use their mobile phones more

the rapid exchange of mobile text messages

than a PC, and that more women use mobile text30

Journal of Socio-Informatics Vol. 8 No. 1 Feb. 2016

messaging and LINE (Ministry of Internal Affairs

setting, students will be influenced by theseand Communications, Japan 2014). LINE, invarious factors, intra-class comparison of students

particular, has been reported to be the most-usedshould allow for discernment of individual

mobile communication tool (LINE Corporationdifferences.

2013), particularly its chat, which is faster andIn certain types of classes, such as sports

easier to use for long periods of time than mobile

classes, multiple seminars, or classes where thetext messaging (Kato 2015). Also, because LINE

lecturer strictly prohibits or punishes cell phone

displays read receipts (a function that lets theuse in-class, external influences are too strong tosender know when his/her message has been

confirm student factor. A survey by Terao and Itoread by the recipient), many young people(2014) reported that 40％ to 60％ of students

continually check their phone to see if theirused their mobile phones in lectures for personalmessages have been read by the other party, inreasons when no particular rules about mobile

addition to normal use to send and receive

phone use in class were made. Because this ismessages. A previous study (Kato and Kato 2016)

about

showed that LINE messaging is used more thanpreliminary research, even though the classroom

text messaging in class, and as a result it isconditions may be different, the observation thatthought that dependency on LINE messaging isabout 50％ of students are using their mobile

greater among students than dependency onphones during lectures (especially those in which

other forms of text messaging. Because of theno rules regarding phone use have been set)

above, it is necessary to examine the degree ofsuggests that the relationships between the in-student Internet dependency as a factor inclass factors and the students’ behavior can beconsidering the personal use of mobile phones

elucidated. Against this background, the present

during lectures. Furthermore, consideration

study was done in a class at a women’s university

should be given to the main communication tools

confirmed to meet the above preliminary study

usedcommunication

requirements (Kato and Kato 2016). An all-female(mobile text messaging and LINE) within theclass was chosen to exclude the effects of gender.

inmobiletext-based

overall scope of Internet dependency.

the

same

as

our

abovementioned

Given the above, the present study examined

This study takes the student factor (dependency)

the following two hypotheses.

into consideration in the personal use of mobile

Hypothesis 1: Due to the high probability ofphones in lectures, but there are a variety ofuse of mobile phones during class by students

influences on student behavior. Many factors

who place their phone on their desk as comparedother than the student factor can be considered,with those who do not do so, there is a highsuch as lecture content, form of the lecture, thedegree of dependency on mobile text message

lecturer, and the classroom. However, moving

communication among students who place theirstudents to an experimental setting wherein all ofmobile phone on their desk during classes.

these factors are controlled for could cause

Hypothesis 2: Due to the trend for LINE text

students to alter their normal behavior. Therefore,

messaging to be used during classes, the degree

the present study was conducted during a lectureof dependency on LINE text messaging among

at an actual university. Although in a real-life

present-day female university students is greater
31

Mobile phone placement during lectures and dependency on LINE and text messaging: Survey of students at a women’s university in Japan

KATO et althan that on mobile phone text messaging,

SD 0.63 years) were the enrolled students inanother text communication tool.

attendance on the day of the questionnaire.
The survey was performed in December 2013

2. Purpose

during the eleventh class meeting, approximately
30 minutes after the class began. Students

This study examined the relationship between

required approximately 15 minutes to complete

the behavior of placing mobile phones on desks

the questionnaire. At the time of the questionnaire,during university lectures and the dependency ofno class rules were in place regarding the use ofuniversity students on mobile text messaging

mobile phones.

and LINE. The dependency of students who(2) Questionnaire

placed their mobile phones on their desks duringlectures was compared to students who did not.

The questionnaire distributed to student

The aforementioned Hypothesis 1 and Hypothesis

survey participants first required a “Yes or No”

2 were also examined.

response to the question, “Is your mobile phoneon your desk at the present moment?”

3. Method

For the rest of the questionnaire, questions
were used to measure dependency on mobile(1) Participants and Class Surveyed

text messaging and LINE messaging. The text-

This study was performed at a women’s

message dependency scale of Yoshida et al.

university in a liberal arts class on understanding(2005) and Igarashi et al. (2008) was used tomedia. This is an elective course, taken by first-

measure dependency on mobile phone text

to fourth-year students from various schools

messaging. This scale incorporated an element ofwithin the university. As a result, although small

dependency on communication, taken fromgroups of three to five friends were seen, there

previous studies on Internet, computer, andwas little overall social cohesion as is frequently

mobile phone addiction (e.g., Armstrong et al.

seen in courses intended for specific majors.

2000; Block 2008; Caplan 2005; Griffiths 2000;

Enrolled students perform investigations on self-

Kandell 1998; Morahan-Martin and Schumacher

selected topics related to media and compile their

2000; Park 2005; Young 1998), and created from afindings into a PowerPoint presentation. In

comprehensive viewpoint of dependency on

addition to general lectures, in each classcommunication media (Igarashi et al. 2008;

approximately 10 of these presentations are

Yoshida et al. 2005). The full scale contains 56

randomly selected for the respective students toitems, but there is also a 15-item short-version

give 5-min presentations, which are then critiquedscale (Igarashi et al. 2008, p.2318), and it was thisby the instructor and the rest of the class. This

short-version scale that was used in this study.

class was the same class surveyed in Kato andThis scale is composed of 3 subscales. There

Kato (2016).

are 5 questions in the “emotional reaction”

There were 101 students enrolled in thesubscale, such as “I feel disappointed if I don’t

course, and the 80 participants (all Japanese

receive any text messages,” and “I often check

women 18-21 years old, mean age 18.98 years ±my mailbox to see if I have a new text message.”32

Journal of Socio-Informatics Vol. 8 No. 1 Feb. 2016

There are 5 questions in the “perception ofexcessive use” subscale, such as “I sometimes
send text messages while engaging in aconversation with another person,” and “I
sometimes spend many hours on text messages.”

Figure 1 N umber of students who placed

There are also 5 questions in the “relationshiptheir mobile phones on the desk

maintenance” subscale, such as “I cannot

during classmaintain new friendships without text messages,”and “I can’t form any new relationships without

the two groups, an analysis of variance wasusing text messages.” The questions require

performed with 2 factors, membership in the on-

responses on a 5-point scale: not at all applicable,

desk group (an intersubject or “group” factor)

not very applicable, can’t say either way,

and dependency on mobile text messaging /somewhat applicable, and very applicable.

LINE messaging (an intrasubject or “tool” factor).

To measure dependency on LINE text

Responses to the two dependency scale

messaging, the phrase “text messages” wasquestions were on a 5-point scale and were

replaced by the phrase “LINE messages” in eachanalyzed as Likert items, with “Not at allof the 15 questions in the text-message

applicable” given a value of 1 and “Very applicable”

dependency scale. For example, the phrase “Ia value of 5. Additionally, there was 1 student infeel disappointed if I don’t receive any text

each group who reported that they do not use

messages” for text-message dependency wasLINE messaging, and data for these 2 studentschanged to “I feel disappointed if I don’t receive

were omitted from the analysis.

any LINE messages” for LINE text messaging.

In the results of the analysis of variance using

Permission was obtained from the creators of

the total score of all 15 questions, the tool factor

the text-message dependency scale for the

had a significant main effect (F (1, 76) = 45.50, p

replacement of “text messages” with “LINE< .001), the group factor did not (F (1, 76) = 2.05),

messages” in the text of each question.

and the interaction was not significant (F (1, 76)= 0.95). Figure 2 shows that in both groups the

4. Results

dependency on LINE messaging was greaterthan the dependency on mobile text messaging.

Responses to the question, “Is your mobile

An analysis of variance was also performed forphone on your desk at the present moment?”the 3 subscale scores. Additionally, Cronbach’s

showed that 67.5％ (54 students) had theiralpha was calculated for each subscale with themobile phone placed on their desk (Figure 1).

following results for text messaging and LINE

This group of 54 students is referred to as themessaging, respectively: 0.84 and 0.90 for“on-desk group” hereinafter, and the group of 26

emotional reaction, 0.73 and 0.83 for excessive

students who answered negatively is called theuse,“not-on-desk group.”

maintenance.

and

0.91

and

0.85

for

relationship

Next, to compare the score for dependency on

In the results for the emotional reaction

text messaging and LINE messaging between

subscale, there were marked differences between
33

Mobile phone placement during lectures and dependency on LINE and text messaging: Survey of students at a women’s university in Japan

KATO et almessage dependency.
For the relationship maintenance subscale, thetool factor main effect was significant (F (1, 76) =13. 30, p < .001), but the group factor main effectwas not (F (1, 76) = 0.63) and there was no
significant interaction (F (1, 76) = 0.75). Figure 5
shows that in both groups LINE-messaging
dependency

Figure 2washigherthanmobile-text

message dependency.

Comparison of average dependency

Finally, an analysis of variance was performed

scores between on-desk and not-using the scores of each of the 5 questions foron-desk groups

emotional reaction, where a difference in thesignificances of the tool factor main effect (F (1,group factor was observed. Significance was76) = 30.58, p < .001), the group factor main effectobserved for each of the following 3 items. For “I(F (1, 76) = 3.30, p < .10), and the interaction
effect (F (1, 76) = 3.03, p<.10). Figure 3 showsthat in both groups, LINE-messaging dependency
was higher than mobile text-message dependency,
but that LINE-messaging dependency was evenhigher in the on-desk group.
For the perception of excessive use subscale,the tool factor main effect was significant (F (1,76) = 58.63, p < .001), but the group factor main
effect was not (F (1, 76) = 0.49) and there was no

Figure 4 C omparison of average excessive

significant interaction (F (1, 76) = 0.00). Figure 4

use subscale scores between on-shows that in both groups LINE-messaging

desk and not-on-desk groups

dependency was higher than mobile text-

Figure 5 C omparison of average relationship
Figure 3

Comparison of average emotional

maintenancereaction subscale scores between

between on-desk and not-on-desk

on-desk and not-on-desk groups

groups34

subscalescoresJournal of Socio-Informatics Vol. 8 No. 1 Feb. 2016feel disappointed if I don’t receive any text
messages / LINE messages”, the interaction was
significant (F (1, 76) = 4.90, p < .05) as were thetool factor main effect (F (1, 76) = 24.57, p < .001)
and the group factor main effect (F (1, 76) = 3.48,
p < .10). Figure 6 shows that for both groups
LINE-messaging dependency was higher thanmobile text-message dependency, but that LINEmessaging dependency was even higher in the

Figure 7 C omparison of average scoreson-desk group. For “I feel disappointed if I don’t

between on-desk and not-on-desk

get a reply to my text message / LINE message

groups for the statement “I feel

immediately,” the tool factor main effect wasdisappointed if I don’t get a reply tosignificant (F (1, 76) = 17.96, p < .001) as was the

my text message / LINE message

group factor main effect (F (1, 76) = 5.63, p < .05),

immediately.”

but there was no significant interaction (F (1, 76)= 1.69). The item “I feel anxious when people
don’t immediately reply to my text message /LINE message” had the same pattern: asignificant tool factor main effect (F (1, 76) =14.22, p < .001) and group factor main effect (F (1,76) = 5.38, p < .05), but an insignificant interaction(F (1, 76) = 0.85). The LINE-messaging dependency
score was higher than the mobile text messaging
dependency score, and both scores for the on-

Figure 8 C
 omparison of average scores

desk group were higher than those for the not-between on-desk and not-on-desk
groups for the statement “I feelanxiouswhen

immediately

people

don’t

to

text

reply

my

message / LINE message.”on-desk group (Figures 7 and 8).

5. Discussion
Figure 6

Comparison of average scores
between on-desk and not-on-deskUsing a questionnaire delivered to students ofgroups for the statement “I feela women’s university in Japan, dependency on

disappointed if I don’t receive any

LINE and text messaging was measured fortext messages / LINE messages.”

students who placed their mobile phones on their
35

Mobile phone placement during lectures and dependency on LINE and text messaging: Survey of students at a women’s university in Japan

KATO et al

desk during class and those who did not do so,

communication is a form of chatting. That is,and two hypotheses were examined.

because LINE messages are regarded as more

The first hypothesis, that there is a high degreeofdependency

onmobiletext

casual,daily

conversation(withmessagesmessageexchanged simultaneously and continuously),communication among students who place their

the perception of excessive use score was higher

mobile phone on their desk during classes, isfor LINE messaging than for mobile text

partly supported. A difference in score wascommunication. As regular conversation createsobserved between the on-desk and not-on-deskand maintain personal relationships, it wasgroups in only the emotional reaction subscale ofexpected that the relationship maintenance score

dependency on LINE messaging, with the on-

would be slightly higher for LINE messaging,desk group having a higher score. Among the 3

which enables conversation-style exchanges

subscales, the score for perception of excessive

more readily than mobile text messaging does.

use was highest in both groups for both mobile

Additionally, LINE messaging notifies the senderphone text messaging and LINE messaging.

when a message has been read. This means that,

Excessive use indicates extended periods ofin addition to waiting for a reply that is notcontinuous mobile text messaging and LINE

arriving quickly, which occurs with mobile text

messaging, and the use of mobile text messaging

messaging, LINE messaging also causes users toand LINE messaging in communicating back andwait for a reply that is not arriving quickly even

forth with people as well. In contrast, thethough the sender that knows the recipient has

relationship maintenance subscale, which asked

read the message. Thus the emotional reactions

about the necessity of mobile text messages andof loneliness and unease arise more easily with

LINE messages to create and maintaining

LINE messaging.

personal relationships, was lowest among theAccording to LINE Corporation (2013), mostsubscales for both groups. Taken together, theseLINE users are in their teens and twenties, with

imply that university students use mobile text

the amount dropping for those 30 and older.

messaging frequently but do not think that

While most university students use LINE topersonal relationships are impossible to create

communicate

and maintain without mobile text and LINE

generation, most members of the older generation

messaging. It was also observed that students

use standard mobile text messaging, mainly

who place their phone on their desk during classbecause they are not as accustomed to the newer

have a marked tendency to feel lonely or uneasycommunication tool as younger students (Katowhen they do not receive a quick reply from the2015).

other party during their communication, but thiscommunicating by LINE are different from thoseemotional reaction was more apparent for LINEin mobile text messaging. Because for mostmessaging than in mobile text messaging.

university students, familiar people such as

Thus,

with

the

students

partiesoftheinvolved

same

when

The second hypothesis, that the degree offriends, significant others, and so on are generally

dependency on LINE text messaging amongin the same generation, it is assumed that they

university students is greater than that on mobile

use LINE to communicate with these parties andphone text messaging, is supported. LINE text

mobile text messaging to communicate with out36

Journal of Socio-Informatics Vol. 8 No. 1 Feb. 2016of-generation individuals such as superiors at

and dependency scale score, although it goeswork or parents. If parties are different, thewithout saying that future studies should

message content will also differ: in LINE, theinvestigate the various external and internal

content is mainly conversation that includes ainfluences on phone behavior.

variety of emotional expressions, while in mobile

6. Conclusions

text messaging the content is more likely to bemainly business-like exchange. Compared withmobile text messaging, the use ratio of LINE isThis study examined the relation between

therefore increasing, with LINE taking on an

dependency on mobile text messaging and LINE

important role in the deepening of relationships

messaging and the act of placing a mobile phonesuch as friendships. Because of this, it is thoughton the desk during classes, focusing on students

that there are many more messages received in

at a Japanese women’s university.

LINE and that the attention paid to replies and

1) Students who place their mobile phone onwhether messages have been read or replied totheir desk have a particularly high dependency

has contributed to increased dependency onscore for LINE messaging for emotionalLINE.

reactions, including feelings of uncertainty andloneliness in waiting for a slow reply.

This study was conducted in a classroom
where no rules had been set regarding mobile2) There is a higher dependency score forphones. However, this didn’t completely remove

LINE messaging than for mobile text messaging.

differences in influence between students. For

This study focused on the act of university

example, we assume that differences in student’s

students placing their phone on their desk during

seating were influential. Generally speaking, ifclasses. Our previous study showed that the act

the seat in front of you is occupied, it’s easier toof placing a mobile phone on one’s desk is a sign

take out your mobile phone without being seenthat shows the potential for mobile phone useby the lecturer. This can be described as anduring classes (Kato and Kato 2015). According

external influence on the placing of a phone on

to this study, this action also suggests a highthe desk. However, several student factors other

degree of dependency on mobile phone use bythan dependency can also be considered, such as

the student.

difference in student age. First-year students

7. Limitations and future research

may still experience residual influences frommobile phone rules in high school, which are
generally very strict. Also, individual differences

The number of samples in this study was 78, so

between students may also become factors, suchconsideration remained focused on classification

as student relationships and events taking placeof whether students did or did not place theirthat day (such as an emergency call, or having

mobile phones on their desk. In the future, it will

just received a romantic confession). This study,

be necessary to conduct this same survey under

however, demonstrated and clarified that there

the same conditions, but with an increase sample

are a number of correlations between thesize, to improve the quantity of data. By doing so,

behavior of setting phones on desks in lectures

it will become possible to classify phone use
37

Mobile phone placement during lectures and dependency on LINE and text messaging: Survey of students at a women’s university in Japan

KATO et alaccording to common student attributes (e.g.

and mobile world. Oxford, NY: Oxford University

academic year, major, seat that day, frequency ofPress.

mobile text messaging / LINE use, purpose of

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306-307.

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Modern university students are often called

Caplan, S. E. (2005). A social skill account of problematic“digital natives,” indicating a generation that has

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they are surrounded by computers and mobile

Demb, A., Erickson, D., & Hawkins-Wilding, S.

phones, and it is said that they are skilled at(2004). The laptop alternative: Student’s reactions

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during classroom lectures should be conducted

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Acknowledgements

Fried, C. B. (2008). In-class laptop use and its effects

This work was supported by JSPS KAKENHI

on student learning. Computers & Education,

Grant Numbers 24501220, 24700913, 15K01095,

50(3), 906-914.

15K01089.

Gay, G., Stefanone, M., Grace-Martin, M., &Hembrooke, H. (2001). The effects of wireless

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