Journal of Socio-Informatics
Vol.13, No.1

Sep. 2020[Refereed Research Note］
Gender and Socioeconomic Differences in Adolescents’ Perceived
Information and Communication Technology (ICT) Competencies

Shuji TOBISHIMAThe Society of Socio-Informatics

Journal of Socio-Informatics
Vol.13, No.1

Sep. 2020◆CONTENTS◆[Refereed Research Note］
Gender and Socioeconomic Differences in Adolescents’ Perceived Information
and Communication Technology (ICT) Competencies

Shuji TOBISHIMA…  1

Refereed Research Note
Gender and Socioeconomic Differences in Adolescents’
Perceived Information and Communication Technology(ICT) Competencies
Keywords:
Perceived ICT competence, gender, socioeconomic status, second-level digital divide, PISA

Shuji TOBISHIMA, Gunma University

Abstract
Based on tenth-grade students’ perceived ICT (information and communication technology)
competencies, this study investigates the gender and socioeconomic differences in adolescents’digital skills in Japan. This study used data from the Programme for International Student
Assessment (PISA), which was conducted in 2015 by the Organisation for Economic Co-operation
and Development (OECD). The multiple regression analysis results demonstrated that genderand family socioeconomic status (SES) had statistically significant effects on adolescents’
perceived ICT competencies. Specifically, the surveyed girls exhibited lower perceived ICT
competence levels than boys, and family SES had a positive effect on adolescents’ perceived ICT
competencies. The results also indicated that ICT availability at home partially mediated theeffect of family SES on adolescents’ perceived ICT competence levels. In contrast, internet usage
time suppressed the effect of SES on adolescents’ perceived ICT competence levels. Moreover,the (positive) effects of ICT availability at home and internet usage time on adolescents’ perceived
ICT competencies were weaker for girls than for boys. It is presumed that girls are more likely touse ICTs for communicational purposes than boys, which may not improve their digital skills.

1Gender and Socioeconomic Differences in Adolescents’ Perceived Information and Communication Technology (ICT) CompetenciesTOBISHIMA

Furthermore, digital skill inequalities may

1. Introduction

exacerbate existing social inequalities (Van Dijk
The term “digital divide” originally referred to2005, Witte & Mannon 2010). For example, Falck

gaps in physical access to information and

et al. (2016) analyzed data from the Programmecommunication technologies (ICTs) such as

for the International Assessment of Adult

computers and the internet. The digital divide

Competencies

received worldwide attention from the late 1990s

Organisation for Economic Co-operation andto the early 2000s. Although it was a serious

Development (OECD) to find that ICT skills areproblem at the time, this type of digital divide wassubstantially rewarded in the labor market. Thus,

expected to disappear as ICTs became more

the unequal distribution of digital skills among

popular and easier to access.

different social groups can lead to income

However, the diffusion of internet use has not(PIAAC)

conducted

bytheinequality among them.

eliminated the digital divide, as evidenced by two

Few studies have empirically investigated theimportant facts. First, gaps in physical access tosecond-level digital divide in Japan, which is the

ICTs are still an important issue, even in

aim of this study. Instead, there are several cross-developed countries (Campos-Castillo 2015).

national studies on the (first- and second-level)

Second, the widespread use of the internet hasdigital divide among adolescents using data fromled to the development of a new type of digital

thedivide. With internet usage rates reaching highStudent Assessment (PISA), in which Japan has

levels, the focus of research on the digital divide

participated since the first survey conducted inhas shifted from gaps in physical access to ICTs

2000. These studies demonstrated that there areto gaps in ICT usage and digital skills. The former

genderis referred to as the “first-level digital divide,”adolescents’ ICT use and digital skills.

OECD’sandProgrammeforsocioeconomic

International

differencesin

whereas the latter is referred to as the “second-

For example, Notten et al. (2009) investigated thelevel digital divide” (Attewell 2001, Hargittai

influence of gender and socioeconomic status (SES)2002) or the “digital inequality” (DiMaggio et al.

on adolescents’ access to and use of ICTs in 30 of the2004).

countries that participated in PISA 2003. They found

By analyzing data from a survey of youth in thethat girls have lower odds of informational and game

Netherlands, Peter and Valkenburg (2006)

use of ICTs, whereas there is no gender difference

showed that the “emerging digital differentiation

regarding communicational use. Furthermore,

hypothesis,” rather than the “disappearing digital

parental education level and occupational status

divide hypothesis,” is supported. That is, thehavewidespread use of the internet has not necessarily

communicational use, but have negative effects on

eliminated any socioeconomic disparities related

game use. Other studies using PISA data also

to ICT usage. Rather, a new form of differentiation

demonstrated that 15-years-old students’ self-

has occurred in terms of how people use ICTs.

reported digital skills (Zhong 2011) and internet

Another study showed that physical access gaps

literacy levels (Ma et al. 2019) differ by gender andare gradually decreasing, whereas digital skill

SES.

gaps tend to increase (Van Dijk 2006).

positive

effectsoninformational

and

By applying multilevel models, these cross2

Journal of Socio-Informatics Vol. 13 No. 1 Sep. 2020

national studies provided rich information on notclasses in Japan (the OECD average was 45.0%).

only the student-level but also the school- andTherefore, Japan is an important research target

country-level factors that affect student ICT

when studying the second-level digital divide.

usage and digital skills. However, Ma et al. (2015)

Moreover, the use of portable internet devices

analyzed PISA 2009 data to elucidate that asuch as smartphones has rapidly spread sincesecond-levelisthe early 2010s in Japan. According to the results

dependent on several country-level factors suchof the Survey on the Internet Use Environment ofas GDP per capita, research and development

Youths conducted by the Cabinet Office, high(R&D)

digitalinvestments,

divide’sandmagnitudeonschool students’ smartphone ownership andsecondary education. Therefore, it is necessary

expenditures

usage rates, which was only 6.8% in 2011, reached

to more fully investigate each country’s second-

54.8% in 2012 and exceeded 90% in 2014. It islevel digital divide to provide a more complete

expected that the spread of smartphones andpicture as to what causes these divides.

other devices has changed the way people use

In Japan, internet use has increased rapidly

ICTs. Therefore, it is not appropriate to apply thesince the late 1990s. According to the results offindings from the existing research that has

the Communications Usage Trend Survey

relied on early- and mid-2000s PISA data to the

conducted by the Ministry of Internal Affairs andcurrent Japanese society.

Communications, the internet usage rate was

2. Research Question and Hypothesis

only 9% in 1997 but steadily increased to 37% in
2000, 70.8% in 2005, 78.2% in 2010, and 83.0% in
2015. Although several studies investigated the

The purpose of this study is to contribute to afirst-level digital divide (Kimura 2001, Tarohmaru

better understanding of the second-level digital

2004, Higuchi 2013), few studies have exploreddivide in Japan. Using a representative sample

the second-level digital divide in Japan. Ono andobtained by PISA 2015, this study specificallyZavodny (2007) is one of the few exceptions;investigates the gender and socioeconomic

however, their research is based on surveys thatdifferences in adolescents’ digital skills in Japan.

were conducted in the 1990s. Apart from the

The research questions addressed in this study

findings of the cross-national studies using PISA

are as follows:

data, little is known about the second-level digital
divide in Japan.

RQ1: Do adolescents’ digital skills differ by

A rationale for focusing on Japan is thatgender?

Japanese schools would not have contributed to

RQ2: Do adolescents’ digital skills differ by SES?

narrowing the digital skill gap between students.
According to the results of PISA 2018, Japan had

As mentioned above, previous studies using

the lowest percentage of students using ICTs in

PISA data have demonstrated that 15-years-old

language, math, and science classes at school

students’ access to and usage of the internet(National

Policy(Notten et al. 2009), self-reported digital skills

Research 2019: 242-244). For example, only 14.0%(Zhong 2011), and internet literacy levels (Ma etof tenth-grade students used ICTs in languageal. 2019) differ by gender and SES. For example,

Institutefor

Educational

3

Gender and Socioeconomic Differences in Adolescents’ Perceived Information and Communication Technology (ICT) CompetenciesTOBISHIMA

Zhong (2011) analyzed data from PISA 2003 andinternet.

2006 to find that boys tend to show higher selfreported digital skills than girls. Moreover, family

As discussed above, ICT availability at home

SES had a positive effect on adolescents’ self-

and the amount of time spent using the internet

reported digital skills. It would be reasonable toare expected to correlate with adolescents’ digital

suppose that Japan is no exception. Therefore,skills. However, even if the home ICT environment

hypotheses 1 and 2 for this study are as follows:

is fulfilling, it is unclear how adolescents actuallyuse ICTs at home. Similarly, the impact of internet
usage time on adolescents’ digital skills could

H1: Girls exhibit a lower level of digital skills

depend on how they use the internet. This study

than boys.

therefore examines whether and how the effects

H2: As SES increases, adolescents exhibit aof at-home ICT availability and internet usage

higher level of digital skills.

time on adolescents’ digital skills differ by gender
In addition to verifying these two hypotheses,

and SES in Japan.

this study includes a more detailed analysis that

Previous studies have exhibited gender andfocuses on the roles of ICT availability at homesocioeconomic differences in young people’s ICT

and the amount of time spent using the internet

usage. Tsai and Tsai (2010) found that boys are

regarding the effects of gender and SES on

moreadolescents’ digital skills.

whereas girls are more communication-oriented

exploration-oriented

internet

users,

internet users in Taiwan. A communicational use
RQ3: How are ICT availability at home andof ICTs tends to be routine, thus may not improvetime spent using the internet related to the gender

digital skills. In fact, young people’s digital skills

and socioeconomic differences in adolescents’

do not predict frequency of Facebook use indigital skills?

Chile (Correa 2016). Moreover, young adults
with higher levels of education use the internet

Digital skills are expected to improve as thefor more “capital enhancing” activities in thehome ICT environment is better prepared, andUnited States (Hargittai & Hinnant 2008).

ICTs are more frequently used. Therefore, we

Therefore, this study examines the following

can predict that ICT availability at home andhypotheses.

internet usage time would have positive effects
on adolescents’ digital skills. Further, if ICT

H4: The effects of ICT availability at home andavailability at home and time spent using thetime spent using the internet on digital skills areinternet are related to gender and SES, thenlarger for boys than for girls.

these factors may mediate the effects of gender

H5: As SES increases, ICT availability at homeand SES on adolescents’ digital skills.

and time spent using the internet have larger effects
on adolescents’ digital skills.

H3: The effects of gender and SES on adolescents’digital skills are (partially) mediated by ICT
availability at home and time spent using the4

Journal of Socio-Informatics Vol. 13 No. 1 Sep. 2020

3. Methodcompetence) is 0.019 (1.9%), which is below 0.05(5%). This means that the degree of student

3.1. Datahomogeneity within schools is negligible andThis study relies on data collected from thethus not for concern in this study (Heck et al.

OECD’s PISA 2015 survey . Since 2000, PISA

2013). Therefore, OLS regression analysis, rather

surveys have been conducted every three years, tothan multilevel modeling, was conducted in thisassess 15-years-old students’ reading, mathematical,

study.

1and scientific literacy levels. Approximately 540,000

3.2. Dependent Variables

students from 72 countries and regions participatedin the 2015 survey, and students from 46 countries

This study’s dependent variable is adolescents’and regions, including Japan, also responded to theperceived ICT competencies, which is a proxy of

optional ICT familiarity questionnaire. This study

their digital skills. This study used the PISA

uses Japan’s PISA 2015 dataset. 6,647 tenth-grade

index of perceived ICT competence (COMPICT),(the first year of high school) students from 198

which is based on IRT (item response theory)schools in Japan participated in PISA 2015 (National

scaling (OECD 2017: 330-331). Concerning their

Institute for Educational Policy Research 2016: 61).

perceived ICT competence levels, students were

In PISA 2015, a two-stage stratified random

asked, “Thinking about your experience withsampling procedure was employed to extract thedigital media and digital devices: to what extent

sample (OECD 2016: 293). First, schools were

do you disagree or agree with the following

randomly selected from all parts of each country.

statements?” In PISA 2015, the adolescents’

Second, about 35 students were randomly drawn

perceived ICT competencies were assessedfrom each selected school. Since some extractedusing the five variables listed below (OECD 2017:

schools and students did not participate in the331).

survey, sampling weights were used in thestatistical analysis to compensate for the bias due

1) I feel comfortable using digital devices that I

to the school- and student-level non-participation.

am less familiar with.

The response rates for schools and students in2) If my friends and relatives want to buy new

Japan were 99% and 97%, respectively (OECDdigital devices or applications, I can give them

2016: 295).

advice.

The PISA 2015 data, due to the two-stage3) I feel comfortable using my digital devices atstratified sampling design, have a multilevel

home

structure wherein students are nested in schools.

4) When I come across problems with digital

In a clustered sample such as this, the error

devices, I think I can solve them.

terms may be correlated within each school,5) If my friends and relatives have a problem

which can lead to biased standard errors.

with digital devices, I can help them.

However, the intra-class correlation coefficient(defined as the ratio of between-group variance to

The students responded to all questions with athe total variance) for this study’s dependent

four-point Likert scale, ranging from 1 (strongly

variabledisagree) to 4 (strongly agree). The scale(i.e.,

adolescents’

perceived

ICT
5Gender and Socioeconomic Differences in Adolescents’ Perceived Information and Communication Technology (ICT) CompetenciesTOBISHIMA

reliability (Cronbach’s Alpha) for Japan was 0.875

portable music player (Mp3/Mp4 player, iPod,®

(OECD 2017: 329).

or similar), printer, USB (memory) stick, andebook reader (e.g., Amazon® KindleTM) .

3.3. Independent Variables
This

study’s

independent

Instead of using this simply summed variable,variablesarethis study performed a multiple correspondence

described in this section.

analysis (MCA), which is equivalent to a principal
component analysis for categorical data, using

Genderthe 11 items listed above. A rationale for using all

This study measured students’ gender with a

11 items is that Van Deursen and Van Dijk (2019)

dummy variable (1: girls, 0: boys).

found that diversity in access to devices andperipherals affects inequalities in internet skills

Socioeconomic status (SES)

and uses.

Regarding adolescents’ SES, this study used

The result of MCA demonstrated that the first

the PISA index of economic, social and culturaldimension accounts for 91.65% of the total

status (ESCS). The ESCS is a composite scorevariance, indicating the unidimensionality of ICT

obtained by a principal component analysis using

availability at home. This study uses the row

parents’ education levels (PARED), highest

score of the first dimension as an index of ICT

parentalhomeavailability at home. As the coordinates of eachpossessions (HOMEPOS) including books in theoccupation(HISEI),

andvariable categories (yes/no) described in Table 1

home. As a result of the principal component

indicate, a large value of the constructed variable

analysis, factor loadings of PARED, HISEI, andmeans the high ICT availability at home. Table 1

HOMEPOS for Japan were 0.76, 0.74, and 0.68,

also shows that the absence of the internet

respectively (OECD 2017: 340).

connection, a printer, and a USB (memory) stick

This study uses this unidimensional SES

at home contributed greatly to the definition of

measure to simplify the interpretation of

the first dimension.

interaction effects . Moreover, using the same
2

variable as many existing studies using PISA data

Time spent using the internet outside of(e.g., Zhong 2011, Ma et al. 2019) ensures theschoolThis study measured adolescents’ time spentinternational comparability of the results.

using the internet outside of school weekly. For

ICT availability at home

both weekdays and holidays, the respondents

The original PISA index of ICT availability at

could choose from the following categories: “nohome (ICTHOME) was measured by the sum oftime” (coded as 0), “1 to 30 minutes per day”

the availability of the following 11 items at home(0.25h), “31 to 60 minutes per day” (0.75h),(1: yes, 2: no): desktop computer, portable laptop“between 1 hour and 2 hours” (1.5h), “between 2or notebook, tablet computer (e.g., iPad®),hour and 4 hours” (3h), “between 4 hour and 6

internet connection, video game console (e.g.,hours” (5h), and “more than 6 hours per day”

Sony PlayStation ), cell phone (without internet(7h)3. To reflect the weekly internet usage time

access), cell phone (with internet access),outside of school, the responses offered for

®

®

6

Journal of Socio-Informatics Vol. 13 No. 1 Sep. 2020

correlated with SES (the correlation coefficient =Table 1. MCA Results (Dimension 1)

0.342) but weakly related with gender (Hedges’s
g = 0.085). This result indicates that the first-level
digital divide by SES still remains in Japan.
Next, we investigate the second-level digital
divide in Japan. Tables 3 and 4 display the estimation
results of the multiple regression analyses ofadolescents’ perceived ICT competencies. This
study examines mediation effects by hierarchicalregression procedures4. The estimation result ofModel 1 demonstrates that girls have lower
perceived ICT competencies than boys. Also, apositive regression coefficient of SES indicates thatadolescents with higher SES backgrounds havehigher perceived ICT competencies.
In Model 2, ICT availability at home wasincluded as an additional independent variable,
and the estimation results indicate that ICT
availability at home has a positive effect onadolescents’ perceived ICT competence levels.
Moreover, the SES regression coefficient (0.026)
was smaller than that in Model 1 (0.108), and theeffect of SES was not statistically significant(p>0.05) in Model 2. This result indicates thatweekdays and holidays were multiplied by 5 days

ICT availability at home mediated the effect ofand 2 days, respectively.

SES on adolescents’ perceived ICT competencelevels5.

Table 2 shows the descriptive statistics ofvariables used for the regression analyses. The

The amount of time one spends using thesample size after listwise deletion is N = 5,945.

internet was added as an independent variable inModel 3, and the estimation results demonstrate

4. Resultsthat time spent using the internet has a positiveeffectonadolescents’

perceived

ICT

Regarding the first-level digital divide, thiscompetencies. The SES regression coefficientstudy examined the gender and socioeconomic

was 0.087, which was statistically significant

differences in ICT availability at home, which is(p<0.001) and larger than that in Model 2 (0.026).

the index concerning access to various devices

In contrast to ICT availability at home, time spentand peripherals. Due to the large sample size, weusing the internet suppresses the effect of SES

consider the effect sizes rather than the p-value

on adolescents’ perceived ICT competence

here. ICT availability at home is moderately

levels6. In other words, SES has a positive direct7

Gender and Socioeconomic Differences in Adolescents’ Perceived Information and Communication Technology (ICT) CompetenciesTOBISHIMA

Table 2. Descriptive Statistics

Table 3. Multiple Regression Analysis Results (Models 1 and 2)

Table 4. Multiple Regression Analysis Results (Models 3 and 4)

8

Journal of Socio-Informatics Vol. 13 No. 1 Sep. 2020

Figure 1. Predictive Margins with 95% CIs
effect and a negative indirect effect through timeeffects of ICT availability at home and time spent

spent using the internet on perceived ICT

using the internet differ by SES. However, neither

competencies. This is due to a negative

the interaction effect between SES and ICT

correlation between one’s time spent using theavailability at home nor the interaction effectinternet and SES (the correlation coefficient is

between SES and time spent using the internet–0.105) despite the fact that both variables have

was statistically significant (p>0.05). These

positive effects on adolescents’ perceived ICT

results indicate that the (positive) effects of ICT

competencies .

availability at home and time spent using the7

Next, this study examined whether and howinternet do not differ for adolescents withthe effects of ICT availability at home and timedifferent SES levels.

spent using the internet differ between girls and5. Discussion

boys. The estimation result of Model 4
demonstrates that the interaction effect between
gender and ICT availability at home (p<0.05), as

Using PISA 2015 data, this study investigatedwell as the interaction effect between gender andthe gender and socioeconomic differences ininternet usage time (p<0.001), were bothadolescents’ perceived ICT competencies innegative. These results indicate that the positive

Japan. The results of the regression analyses

effects of both ICT availability at home and timedemonstrated that girls exhibited lower perceived

spent using the internet are smaller for girls.

ICT competencies than did boys. Thus, theSpecifically, the regression coefficient for ICT

results offer support for Hypothesis 1. The

availability at home was 0.177 for boys but 0.122

results also showed that SES had a positive effect(=0.177–0.055) for girls. Similarly, the regression

on adolescents’ perceived ICT competencecoefficient for time spent using the internet waslevels,0.026 for boys but only 0.018 (=0.026–0.008) for

supported. These findings indicate that the

girls. Figure 1 graphically represents the

spread of ICTs has not eliminated the digitalinteraction effects.

divide. Rather, as this study demonstrates, theindicating

that

Hypothesis

2

wassecond-level digital divide does exist in Japan.

Model 4 also examined whether and how the9Gender and Socioeconomic Differences in Adolescents’ Perceived Information and Communication Technology (ICT) CompetenciesTOBISHIMA

However, it should also be noted that adolescents’

Hypothesis 5 was not supported. Previous studies

perceived ICT competence levels are largely

have suggested that young people’s ICT usage

unexplained by gender and SES, as indicated byvaries depending on SES (Peter & Valkenburg

low R value in regression analysis.

2006, Hargittai & Hinnant 2008, Notten et al.

2

As expected, both ICT availability at home and2009). However, the present study’s results

the amount of time spent using the internet had

indicate that it might not necessarily be the casepositive effects on adolescents’ perceived ICTthat adolescents with higher SES tend to use

competence levels. However, these two variables

ICTs more effectively to improve their digital

played different roles with the effect of SES on

skills.

perceived ICT competencies, and the results of

A limitation of this study relates to how digitaltesting Hypothesis 3 were mixed. That is, ICT

skills were measured (Litt 2013). Due to data

availability at home mediated the effect of SES on

limitations, this study used adolescents’ perceived

adolescents’competencies,

ICT competence levels in the statistical analyses

whereas one’s time spent using the internet

rather than adolescents’ objectively measured

suppressed the effect of SES on perceived ICT

digital skills. However, it is possible that one’s

competencies. This is because SES is positively

perceived and actual ICT competencies arecorrelated with ICT availability at home but

different (Hargittai & Shafer 2006). Due to thenegatively correlated with time spent using theuse of subjective indicators, this study’s findings

internet.

may depend on the measurement of digital skills

perceived

ICT

Moreover, the effects of ICT availability at(Merritt et al. 2005). It is necessary to verify thehome and time spent using the internet on
perceived

ICT

differed

Regarding this issue, special attention should

between girls and boys. That is, the positive

be paid to gender differences, as women may

effects of ICT availability at home and internet

underestimate their digital skills compared tousage time on adolescents’ perceived ICTmen (Sieverding & Koch 2009). Therefore, thecompetencies were weaker for girls than forgender difference in adolescents’ perceived ICTboys. The result offers support for Hypothesis 4.

competencies observed in this study can be

It could be assumed that these results are due toattributed to the gender bias regarding self-

the gender differences in ICT usage (Notten etevaluations of digital skills. In fact, while boys

al. 2009, Tsai & Tsai 2010). That is, it is presumed

outperformed girls in computer literacy, girls

that girls tend to use ICTs for communicational

outperformed boys in information literacy in the

purposes, which may not improve their digital

International Computer and Information Literacy

skills.

Study (ICILS) 2013 (Punter et al. 2017).

Futurecompetence

research

levelsrobustness of the results in future research.

shouldempiricallyinvestigate the relationship between such gender

Furthermore, due to data limitations, thisdifferences in ICT usage and skills.

study did not account for some possible

On the other hand, the magnitudes of theconfounders such as parental attitudes toward

effects of ICT availability at home and internet

ICTs. Therefore, future research is needed tousage time on adolescents’ perceived ICT

estimate more precisely the effects of ICT

competencies did not depend on SES. Therefore,

availability at home and internet usage time on
10

Journal of Socio-Informatics Vol. 13 No. 1 Sep. 2020

adolescents’ perceived ICT competence levels.

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13

Editor’s Notes
We are very pleased to announce the publication of Volume 13 of JSI, Journal of Socio-Informatics.
Through the peer review process, a paper has been accepted as a research note.
We want to provide a kind of fruitful public space open to every researcher who has interest insocioinformatics from all over the world. We are inviting you, our readers, to submit papers onsocioinformatics or other related fields. The Call for Papers of JSI is available on http://www.ssi.or.jp/
eng/index03.html.
Cordial greetings,

The Editor

Editorial Board of The Society of Socio-Informatics
Editor in Chief
Yuko TSUCHIYA, Hiroshima University of Economics
Editor in Subchief
Tomoko KANAYAMA, Institute of Advanced Media Arts and Sciences

Editorial board members
Chair
Yorio KITAMURA, Ritsumeikan University
Sub ChairSeiichiro SAKURAI, Meiji Gakuin University
Kunikazu AMAGASA, Showa Women’s University
Kaoru ENDO, Gakushuin University
Hiroyuki FUJISHIRO, Hosei University
Kenji IIJIMA, Prefectural University of Kumamoto
Kenichi ITO, Gunma University
Shogo KATO, Tokyo Woman’s Christian University
Yuuki KATO, Sagami Women’s University
Nobuaki KAWAI, Jissen Women’s University
Takahiro KAWAMATA, The University of Nagasaki, Siebold
Shigeo KAWASHIMA, Aoyama Gakuin Women’s Junior College
Sangmi KIM, Nagoya University
Tadamasa KIMURA, Rikkyo University
Yuko KITORA, Doshisha Women’s College of Liberal Arts
Ron KORENAGA, Rikkyo University
Atsushi KOTERA, Toyo Eiwa University
Keita MATSUSHITA, Kansai University
Kunihiko NAKANO, Shimane University
Morihiro OGASAHARA, Toyo University
Akiko OGAWA, Nagoya University
Shungo SAKAKI, Tokyo University of Technology
Isao SAKUMA, Bunkyo University
Yuichi SASAKI, Tokyo Keizai University
Masahito SHIMAZAKI, Akita Prefectural University
Akashi SUGIYAMA, Kyushu University
Soichiro TAKAGI, The University of Tokyo
Toru TAKAHASHI, Chuo University
Nobumoto UEHARA, Tokyo International University
Hitoshi YAMAMOTO, Rissho University
Shaoyu YE, University of Tsukuba

Journal of Socio-Informatics Vol.13, No.1
Sep. 2020
Published
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