Journal of School Improvement and Leadership 2019

JOURNAL OF SCHOOL IMPROVEMENT AND LEADERSHIP

2019: 85-107

ARTICLEThe Effect of Key Competencies on Social Capital:
Social Outcomes of Learning in Japan

Kenji TSUYUGUCHIa and Tetsuo KURAMOTOb
aEhime University
bAichi University of Education

ABSTRACTKEYWORDS

This study attempted to determine the social outcomes of learning by

Social Capital

examining the relationship between key competencies and social capital. A

Human Capitalquestionnaire was completed by 3,575 participants aged 20–79 years from

Key competency

various areas of Japan. Items on the questionnaire focused on attributes such

Learning

as homeownership, education level, income, interactions, and trust. The
results indicated that (1) learning factors (i.e., sense of lifelong learning, key
competencies) had an effect on fostering social capital; (2) key competencies
could potentially minimalize the negative relationship between economic
conditions and social isolation; and (3) regardless of community, the social
outcomes of learning were nearly identical.

1 Introduction
This study attempts to determine the social outcomes of learning by examining the relationshipbetween key competencies and social capital. International discussions of learning outcomes havegenerally focused on economic performance in the context of human capital theory (Becker 1994).
In this theoretical context, it is assumed that learning under formal education expands humancapital (e.g., knowledge, skills, qualifications), which in turn boosts profits and economic growth.
However, by 2000 the Organization for Economic Co-operation and Development (OECD) had
proposed a shift away from learning outcomes based on economic gains to those with a social
focus. Interest in social capital, health, and well-being in addition to knowledge, skills, andqualifications consequently intensified among researchers and policymakers (OECD 2007a).
In Japan specifically, individuals began to focus greater attention on social capital following
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Tsuyuguchi & Kuramoto：The Effect of Key Competencies on Social Capital

the East Japan Great Earthquake Disaster. Indeed, verifying the determinants of social capitalfrom an educational/learning perspective is of great importance; accordingly, this research
investigates social capital (Putnam,Leonardi,& Nanetti 1993; Putnam 2001) as a social outcome oflearning.
In prior research, social capital has generally been taken as an exogenous variable. Since
Coleman (1988), studies focusing on social capital’s effects on human capital have increased.
Nevertheless, research wherein social capital is an endogenous variable remains sparse. Likewise,with the exceptions of Feinstein and Hammond (2004),Tuijnman and Boudard (2001),and Field(2005), studies that verify the effect of learning on social capital are few. In research in whichlearning factors are set as an explanatory variable of social capital, educational qualification isfrequently treated as a control variable. To generate social capital, people should recognize theimportance of building ties through learning and possess the ability to build such ties. Hence, inthe present study educational qualifications, sense of lifelong learning (Field 2005)), and key
competencies (Rychen & Salganik 2003) are set as learning factors.

2 Economic Outcomes and Social Outcomes of Learning
2.1 Human Capital
Japan has continued to invest huge amounts in the education/learning sector, including
homes, schools, and communities. As a result, the level of human capital (e.g., knowledge, skills)
has reached the top levels in the world. For example, reading and science were ranked fourth in
the Programme of International Student Assessment 2012 (PISA 2013). However, we should keep inmind that all the upper-ranked areas are small countries (or local governments in a country) suchas Shanghai, Hong Kong, and Singapore.
In addition, literacy and numeracy were ranked highest of 24 countries in the Programme for theInternational Assessment of Adult Competencies 2012 (PIAAC 2012), which addresses the academic
achievements of adults. The high academic achievement level of adults in Japan is demonstrated
by the following survey results. Non-graduate upper secondary education in Japan had higher
literacy scores than graduate upper secondary education in Germany and the United States. In
addition, low-skilled workers in Japan had higher literacy scores than semi-skilled workers inGermany and the United States (National Institute for Education Policy and Research 2013). We
can interpret this as showing that the learning system in Japan has significant effects on fostering
human capital, such as knowledge and skills. Does the learning system in Japan have an effect onother aspects of social performance besides human capital?
As described previously, OECD has been interested in the social outcomes of learning, andinsists on the significance of verifying the effect of learning on social outcomes, such as social
capital, health, and well-being. Since so much economic capital is invested in the
education/learning system, many people are naturally interested in the results of theeducation/learning. International achievement tests, such as PISA and PIAAC, are outcome
indicators of learning that are easy for people to understand. Therefore, many national
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Journal of School Improvement and Leadership 2019

governments are interested in these test results to ensure accountability to their citizens.
However, people do not learn solely to acquire knowledge, skills, and qualification. In Japanesesociety, educational purposes such as fostering rich ties with others and living healthy and happy
lives are included in the formal and informal education system. If we intend to explain theoutcomes of economic capital inputs in learning, we have to focus on the social outcomes oflearning, such as social capital, health, and well-being. Therefore, we think that the Japanese
government must ensure greater accountability than other countries in addition to verifying theeffect of learning on social outcomes. The question then arises of the degree to which the social
outcomes of learning in Japan have been achieved.
2.2 Social Capital, Health, and Well-being
In order to understand the actual situation of children’s social capital and health, the report
data of UNICEF Innocenti Research Institute will be helpful (UNICEF Innocenti ResearchInstitute,Abe,& Takezawa,2013). First we survey the situation of social capital of children.
Appropriate indicators are as follows: On the “percentage of children who have received
bullying,” which focuses on the relationships among children, Japan ranked tenth out of 30
countries. On the “percentage of NEET (Not in Education, Employment or Training),” focusing
on the relationship between children and society, Japan ranked tenth out of 30 countries. In
addition, “child abuse mortality,” focusing on the relationship between children and parents,
Japan ranked sixth out of 28 countries. Social capital of children has become somewhat
problematic compared to academic achievement.
On the other hand, the research report has the following three variables as indicators ofchildren’s health: “percentage of obese children” ranked 30th out of 30 countries, “percentage
having breakfast every morning” ranked first out of 30 countries, and “teen pregnancy rate”
ranked 28th out of 31 countries. The health of children in Japan as well as their academic
achievement is in the top level of OECD countries.
UNICEF Innocenti Research Institute et.al. (2013) is an international survey that studied thewell-being of Japanese children. The report measured children’s well-being from five
perspectives: material well-being, health and safety, education, behaviors and risks, and housing
and environment. Children in Japan ranked sixth out of 31 countries, which is relatively high.
In order to understand the actual situation of adult’s social capital, health, and well-being,
OECD (2011) will be helpful. Indicators of social capital of adults are as follows:

On “support

by social networks (whether do you have family or friend that you can count on when you needit?)” Japan ranked 24th out of 40 countries, and tenth out of 36 countries on “confidence in theothers (the percentage of people who responded that most people can be trusted)” and tenth outof 28 countries on “time for volunteer activities.”

In addition, on “vote rate” Japan ranked 23rdout of 39. This indicates that, based on international comparative data on adults’ social capital,
Japan has weaknesses in social networks and participation.
On the other hand, adult health indicators are as follows: On “expectation of life at birth” Japanranked first out of 40 countries and fourth out of 40 countries on “adult obesity rate.” The healthlevel of Japanese adults is among the highest in the world.
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Indicators of adult well-being are as follows: On “life satisfaction (the best life that may bethought is 10, the worst life that may be thought is 0),” Japan ranked 29th out of 40 countries andthird out of 40 countries on “dominant emotion (the proportion of respondents who often
experience positive rather than negative feelings the day before the survey).”Judging by“dominant emotion,” there are many people who experience a feeling of well-being in Japan.
2.3 Focus on Social CapitalInternational comparative data on the social outcomes of children and adults show multiple
indicators of social capital needing improvement. Such problems as bullying, NEET, and childabuse are social issues related to the social capital of children, while poor social support andparticipation are related to the social capital of adults. We hypothesize that these problems related
to social capital are affected by learning factors.
The present study focused on social capital as social outcomes of learning. Putnam,Leonardi &Nanetti (1993) define social capital as follows: “Features of social organization, such as trust, norms,
and networks, that can improve the efficiency of society by facilitating coordinated action” (p. 167). In
general, recent studies of social capital have measured social capital with reference to trust,norms, and networks, as indicated by Putnam et al. (1993). Social capital is a concept that has
gained international, interdisciplinary attention during roughly the last 30 years (e.g., Bourdieu
1986; Burt 1997; Coleman 1988; Kawachi,Subramanian,& Kim 2008; Lin 2008; Putnam et al. 1993;
Putnam 2001; Woolcock & Narayan 2000).
The main interest of social capital research in the field of education is in the effects of social
capital on human capital. Since Coleman (1988, 1990), the effects of social capital on humancapital, such as academic achievement, university enrollment rates, and dropout suppression,
have become the focus of social capital research in the field of education. (Anderson 2008; Croll
2004; Huang 2009; Gottfredson & DiPietro 2011; Ho Sui-Chu & Willms 1996; Louis & Marks 1998;
Morgan & Sorensen 1999; Parcel & Dufur 2001; Payne,Gottfredson,& Gottfredson 2003; Pong
1998; Smith,Beaulieu,& Israel 1992; Sun 1998,1999).
On the other hand, relatively little progress has been made in clarifying the determinants ofsocial capital. Several studies have verified the effects of SES and residential mobility on adults’social capital; however, only little research has taken social capital as an endogenous variable(e.g.,Aston & McLanahan 1994; Bryk & Schneider 2002; Hofferth & Iceland 1998; Swanson &Schneider 1999). In the present study, we demonstrate the effects of learning factors on social
capital, taking the effects of SES and residential mobility as control variables. This raises thequestion of what the effects of learning factors are on building social capital. The following
section, in which the analysis model is constructed, discusses previous studies of learning factorsthat might affect social capital.

3 Learning Factors’ Effects on Social Capital
It would appear that the focus of educational research is changing from “the effect” to “how to88

Journal of School Improvement and Leadership 2019build” (OECD 2007a). Researchers have devoted great time and expense to clarify the significanceand effects of social capital. The next stage might be called an exploratory stage on fostering theimportant capital of a given society. In this research, we examine the effects of learning on social
capital based on OECD’s viewpoint that learning fosters social capital. The present study assumes
that the following three learning factors—educational qualifications, the experience and sense of
lifelong learning, and key competencies—are suitable explanatory variables of social capital.
3.1 Educational Qualifications
Inaba (2007) carried out correlation analysis of the relationship between educational
qualification and social capital with prefectural-level data (N = 47). The results yielded a negative
correlation between educational qualification (the proportion of university or higher education)and social capital. On the other hand, a positive correlation was observed between educational
qualifications (the proportion of high school education or less) and social capital. However, thisresult was obtained by simple bivariate correlation analysis, leaving open the possibility thatdifferent results would be obtained with partial correlation analysis that includes control variable
such as population size, population density, financial index, university enrollment rates, and theaverage age of respondents. However, the result of this analysis has value in that it indicates that
educational qualifications have some influence on social capital.
Recent years have seen an increase in the number of studies using individual data todemonstrate a relationship between educational qualification and social capital. For example,
Yasuno (2014) analyzed the relationship between educational qualifications and social capital(social participation) with data from the sixth wave of the World Values Survey. His analysis
clarified that compared to a reference point of “high school graduate,” the participation rate of
the “junior high school graduate” group is lower. In addition, the survey of Ishida (2015)
demonstrates that educational qualifications (years of education) affect generalized trust andreciprocal norms but not neighborhood relationships.
On the other hand, Nagayoshi (2013) examined the effect of educational qualifications on social
exclusion as a reverse aspect of social capital. His analysis demonstrates that educational
qualifications have the effect of suppressing social inclusion (“I have never consulted anyone
even trivially in the past year”). Sasaki (2014) has revealed that the level of generalized trust (“Ican trust most people”) of university graduates is higher than that of high school graduates.
Misumi (2014) studied the effect of educational qualifications on social capital as measured fromthe three perspectives of generalized trust, generalized reciprocity, and tolerance. As a result, it
was revealed that educational qualifications (years of education) have a positive effect on
generalized trust and tolerance but not on generalized reciprocity.
This research obtained characteristic results on the relationship between educational
qualifications and social capital. The relationship between the two factors is positive whenanalyzing individual-level data but negative using community-level data.
3.2 Experience and Sense of Lifelong Learning
Certainly, educational qualifications are the most popular explanatory variable when89

Tsuyuguchi & Kuramoto：The Effect of Key Competencies on Social Capital

analyzing the effects of learning on social capital. However, “educational qualifications” refers to
the number of years in educational institutions or the degree acquired around age 20 under aformal education system. While educational qualifications illuminate part of a person’s learning
experience, it is not sufficient to encapsulate learning experiences after reaching adulthood.
Tuijnman & Boudard (2001) investigated the relationship between the participation rate inadult lifelong learning and social capital (civic participation and generalized trust as alternative
indicators) using international adult literacy survey data for 17 Western European countries.
Their analysis revealed that if a nation’s adult learning participation rate is high, the participation
rate in voluntary organizations and the level of generalized trust in others is also high.
Feinstein & Hammond (2004) used an analysis model in which the amount of participation inlearning courses during 10 years of adulthood (33‒42 years) was set as an explanatory variable ofsocial capital, for which aspects of citizen participation (political interest, participation in civic
activities, and voting) were the dependent variables serving as alternative indices of social capital.
They analyzed the effect of participation in learning courses on social capital (civic participation)
through control variables such as educational qualifications, occupational status, and SES. The
analysis shows that participation in learning courses has a positive effect on the three indices ofsocial capital. The study thus yields the interesting result that lifelong experiences in adulthood
have positive effects on building social capital.
Mitsubishi Research Institute (2011) is a study in which both educational qualification andlifelong learning experience are explanatory variables of social capital. The survey target age is30‒49. This study used multi-level modeling (individual-level and prefecture-level) in whichsocial capital (bonding social capital and bridging social capital) is a dependent variable. The
analysis revealed that both educational qualifications (“university and graduate school”) andlifelong learning experience (“degree of implementation of learning that will help to skill up
oneself”) have positive effects on bridging social capital. Previously acquired educational
qualifications and current learning activities for professional growth have the effect of expandingsocial capital. Furthermore, lifelong learning factors such as “degree of implementation of schoolsupport activities within one’s own community” and “degree of implementation of learning
activities by utilizing lifelong learning facilities within one’s own community” have positiveeffects on both bonding and bridging social capital. However, note that the study revealed
significant individual-level effects but not prefectural-level effects on social capital.
On the other hand, Field (2005) examined the effects of a sense of lifelong learning on social
capital (social participation willingness as an alternative indicator) in a survey of the UK. To thestatement, “people will be better citizens through continued learning,” 66.7% of respondents
answered that it is “important” to participate in their own community and 54.5% answered “notimportant.” The group who answered “important” about participating in cultural events, theirown church, and sports gave more positive responses to the statement that “people will be better
citizens through continued learning.”
Measurement of lifelong learning experience has been implemented for a limited age group(30‒40 years old), as in Feinstein & Hammond (2004) and Mitsubishi Research Institution (2011).
The research targets of these surveys are fundamentally of working age. However, this study90

Journal of School Improvement and Leadership 2019

surveyed a wide range of adults aged 20‒79 years, as described below, which presents the riskthat lifelong learning experience has been inordinately affected by age and employment status.
We thought it better to set “sense of lifelong learning“ as one of the learning factors rather than“experience of lifelong learning” as in Field (2005).
3.3 Key Competencies
As mentioned previously, preceding studies have focused on educational qualifications orexperience of lifelong learning as explanatory factors of social capital. These variables focus on
the quantitative aspects of the learning experience but do not touch on qualitative aspects oflearning experience, such as concrete value/sense or competency acquired through various
educational opportunities. The concepts of adult abilities are diverse. Therefore, it is a very
difficult task to specify and measure the abilities of adults. However, inspired by the DeSeCo(Definition and Selection of Competencies: Theoretical and Conceptual Foundations) Project, thecompetency concept of adults was recently clarified and a common understanding has beenreached on the international level (OECD, 2005; Rychen & Salganik 2003). The DeSeCo Projectfocused on the three important competencies of Using Tools Interactively, Interacting in
Heterogeneous Groups, and Acting Autonomously to realize the “quality of life” and “wellfunctioning society.”
Key competency theory was included in the project from the perspective of the building effects
of social capital (social network) in addition to economic growth effects by facilitating key
competencies. As this is a concept that has gained international consensus, we consider key
competencies useful as indicators of adult learning factors. We will examine key competencies asa qualitative aspect of learning experience, in addition to educational qualifications and thedegree of participation in lifelong learning courses as quantitative aspects of the effects oflearning experiences on social capital.

4 Research Questions
The following three research questions will be examined by focusing on educational
qualifications, a sense of lifelong learning, and key competencies as learning factors that have aneffect on building social capital.
4.1 Direct Effects of Learning Factors on Social Capital
The first research question is to reveal the direct effects of three learning factors (educational
qualification, sense of lifelong learning, and key competencies) on social capital. The present
study was designed to compare the effects among learning factor variables and the effects ofindividual-level and community-level factors on social capital. In previous studies, analysis
focused on one learning factor, as did analytical models comparing individual and communitylevel effects. Previous studies emphasized the effect of quantitative aspects of the learning
experience (educational qualifications). However, the qualitative aspects of learning experience91

Tsuyuguchi & Kuramoto：The Effect of Key Competencies on Social Capital(value and ability) might be more effective in building social capital.
Is the building of social capital determined by learning variables on the individual orcommunity level? The possibility is considered that one person’s social capital might increase byliving in a community where the level of learning factors is high even though the individual-level
learning factors are not high. When discussing the explanatory factor of social capital, it isimportant to include community-level factors in the model in addition to individual-level factors
to avoid statistical fallacies.
4.2 Adjustment Effect of Learning Factors in the Relationship between Economic Situation andSocial Capital
The second research question is to reveal the adjustment effect of learning factors on therelationship between economic conditions and social capital. The formal education system has
been expected to suppress re-production phenomena. We believe that an adjustment effect oflearning factors functions in the relationship between economic hierarchy and social capital. If
one person has a low education background, a low sense of lifelong learning, or low key
competencies, a low income level would lead to social isolation. On the other hand, anotherperson for whom these learning factors are high, even in a low income level, this would be
unlikely to lead to social isolation. The adjustment effect of economic inequity by learning factors
would occur also at the community level. If one community has an average low level of learning
factors, low economic conditions at the community level would lead to social isolation.
4.3 Community-level Differences in the Effect of Learning Factors on Social Capital
The third research question is to reveal the community-level differences in the direct effects oflearning factors on social capital. Is the effect of learning factors on social capital similar ordifferent between communities? If the effect of learning factors on social capital has
commonalities between communities, it may be expected that learning factors related to theformal and informal education system would yield high performance in any community incountry. However, if diverse effects on building social capital are observed, we would need towork to clarify the characteristics of a community showing a high incidence of the effect.
Therefore, to discover the institutional and policy implications of research findings, we should
check the difference or variance in the effect between communities.

4.4 Research Questions in this Study
Based on the aforementioned, the following three research questions are posed:
RQ1. Do learning factors have an effect on social capital? If so, is the effect quantitative (i.e.,
years of education) or qualitative (i.e., sense of lifelong learning and key
competencies)?
RQ2. Do learning factors have an adjustment effect on the relationship between economic
conditions and social capital? If learning factors have a low-level effect, poverty should
lead to social isolation. However, if learning factors have a high-level effect, they92

Journal of School Improvement and Leadership 2019should minimize the relationship between poverty and social isolation.
RQ3. Do any differences exist between communities that directly affect the influence oflearning factors on social capital?

5 Method
5.1 Data Collection
Data were obtained from the Security, Trust, and Social Participation of the Living Questionnaire(Grant-in-Aid for Scientific Research 24243040), which was conducted between October 10 andNovember 8, 2013. The questionnaire received approval from the Nippon University Ethical
Review Board, and was implemented by Japan’s Central Research Service. The survey targeted
10,000 people aged 20–79 years selected randomly from the Basic Resident Register, which
comprises 100 different areas. A two-stage random sampling mailing method was employed; thenumber of returned and valid questionnaires was 3,575, for a 35.8% response rate. The
respondents’ demographics are provided in Table 1.
Table 1. Respondents’ Attributes
N
SEX
AGE
OCCUPATIONRESIDENCEFORM
RESIDENCE YEARSHOUSEMATEEDUCATIONALQUALIFICATIONHOUSEHOLD
INCOME(million yen)

Male
FemaleSelf-employedManager
Regular employee
Temporary staff
Public officials
Part-time worker
Student
Unemployed
Full-time housewife/husband
OthersOwn house
Rented house
Alone
Some housemate
Junior high school or lessHigh school
Advanced vocational school
Junior college
University
Graduate school
Less than 200
200‒400
400‒600
600‒800
800‒1,000
1,000‒1,200
More than 1,200

1,628
1,947
3,575
341
87
820
195
168
536
61
588
594
94
2,747
721
3,484
346
3,155
375
1,438
407
383
844
81
354
1,051
816
497
329
147
145

MEAN

SD

COMPOSITIONRATE (%)

45.5
54.5
53.5

15.8
9.5
2.4
22.9
5.5
4.7
15.0
1.7
16.4
16.6
2.6
76.8
20.2

25.5

18.6
9.7
88.3
10.5
40.2
11.4
10.7
23.6
2.3
9.9
29.4
22.8
13.9
9.2
4.1
4.1

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Tsuyuguchi & Kuramoto：The Effect of Key Competencies on Social Capital

Table 2. Questionnaire Items
Items
Dialogue and Interaction
The degree of interaction with the neighborhood

N

M

3,552

3.73

.77

Frequency of socializing with friends andacquaintances

3,546

3.45

.94

Frequency of relationship with relatives
Affiliation
Residents’ association activities
Sports, hobbies, and recreation activities
Volunteer or NPO activities
Others

3,546

3.23

.89

3,532
3,534
3,528
3,511

1.97
2.84
1.62
1.41

3,544

.27

Specialized Reciprocal Norms
Do you think that if you have helped a person, you
would be helped from that person later?
Generalized Reciprocal Norms
Do you think that if you have helped people, you
would be helped by someone in a troubled
situations someday?
Generalized Trust
Do you think that you can trust people generally?

Trustworthiness in Public
City/Town Office
School/Hospital
Police office
Residents’ association
NPO/Civic group
Trustworthiness in Private
Neighborhood Residents
FamilyRelatives
Friends
Sense of Lifelong Learning
People becoming citizens may continue leaning
throughout life
Key Competency
I have the ability to use language, symbols, and text
interactively
I have the ability to use knowledge and informationinteractively
I have the ability to use technology interactively
I have the ability to relate well to others.
I have the ability to cooperate
I have the ability to manage and resolve conflicts
I have the ability to act within the big picture
I have the ability to form and conduct life plans andpersonal projects
I have the ability to assert rights, interests, limits,and needs

3,541

.18

SD

Component
Score

Scale
Daily (5), Frequently(4),
Sometimes (3),Rarely (2),Absolutely none (1)Daily (5), Frequently(4),
Sometimes (3),Rarely (2),Absolutely none (1)
Id.

.82

1.30
2.03
1.23
1.06

4 or more days per
week (7), 2‒3 days
per week (6), 1 day
per week (5), 2‒3days per month (4), 1
day per month (3), a
few days per year (2),not participating (1)

.60
.35
.65
.38

.44

Agree（1）Neither agree
disagree（0）Disagree（0）－.38Agree (1)Neither agree
disagree (0)Disagree (0)

.70

.58

nor

－
nor

3,446

4.94

2.26

It is possible to trust
most of the people (9)～ It should be withcaution (1)

－

3,427
3,426
3,422
3,385
3,345

2.94
3.23
3.10
2.76
2.69

.98
.93
.93
.90
.86

Able to count on (5)～Not able to count on
(1)

.80
.78
.77
.82
.79

3,442
3,434
3,452
3,455

2.97
4.26
3.55
3.62

1.02
.83
1.07
.96

Able to count on (5)～Not able to count on
(1)

.67
.73
.81
.76

3,468

3.00

.92

I think so (5) ～ Do
not think so (1)

－

3,496

3.32

1.01

Strongly Agree (5) ～Strongly Disagree (1)

.75

3,495

3.38

.99

.72

3,477
3,490
3,494
3,490
3,490
3,493

3.23
3.26
3.46
3.14
3.57
3.04

.99
1.07
.91
.89
.88
.97

.67
.69
.65
.77
.74
.71

3,488

3.28

.95

.77

94

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5.2 Dependent Variable
The Social Capital Integration Index (SCII) was created as a dependent variable. It was
based on Putnam’s (2001) Network, Reciprocal Norm, and Trust Index. The procedure forcalculating the SCII score is as follows.
First, measurement items were set from the perspectives of network (dialogue and interaction,
three items; affiliation, four items), reciprocity norms (specialized reciprocal norm, one item;
generalized reciprocal norms, one item), trust (generalized trust, one item; trustworthiness inpublic, five items; trustworthiness in private, four items), based on knowledge of previous studies
such as Putnam (2001). Measurement items and measures of subordinate variables are shown in
Table 2.
Next, principal component analysis (promax rotation) was extracted for each of the four
subordinate variables that were constructed from multi variables. One factor was extracted foreach variable. The ranges of the factor scores are as follows: dialogue and interaction (three
items, .58‒.82), affiliation (four items, .35‒.60), trustworthiness in public (five items, .77‒.82),
trustworthiness in private (four items, .67‒.81). In addition, the sum of squared factor loads,
which is an indicator of validity, and the α coefficient, which is an index of reliability, are as
follows: dialogue and interaction (66.2%; .74), affiliation (48.9%; .60), trustworthiness in public(74.2%; .91), trustworthiness in private (73.6%; .88).
Finally, using the variable scores obtained by the procedure above, principal component
analysis targeting seven subordinate variables was carried out. As a result of the analysis, one
principal component was obtained. Component scores include dialogue exchanges (.71),
affiliation (.58), specialized reciprocity norms (.42), generalized reciprocity norms (.40),
generalized trust (.51), specialized trust in public (.62), specialized trust in private (.68), andgeneralization confidence. The seven items explained 32.4% of the variance, and the reliability
score was .56 (α coefficient).
5.3 Individual-Level Explanatory Variables
Three variables related to learning (i.e., educational qualification, sense of lifelong
learning, key competency) and 12 control variables related to respondents’ demographics
were set as individual-level explanatory variables. A summary of these variables follows.
Educational qualification. This variable refers to one’s years of formal schooling. The
questionnaire included an item regarding educational experience , wherein points wereallotted as follows: junior high or less (9), high school (12), advanced vocational school (14),junior college (14), university (16), graduate school (18).
Sense of Lifelong Learning. To measure this variable, participants were asked to indicate (ona five-point scale) to what extent they agreed with the statement “People become good citizens
through lifelong learning.”
Key Competency. This refers to the various capabilities that one acquires through leaning
activities. Nine items were used to measure self-assessment of key competency, which werebased on the three categories specified by Rychen and Salganik (2003): using tools
95

Tsuyuguchi & Kuramoto：The Effect of Key Competencies on Social Capitalinteractively, interacting in heterogeneous groups, and acting autonomously (see Table 2).
Principal component analysis for the nine items resulted in the extraction of one main
component. The nine items explained 70.6% of the variance, and the reliability score was .95 (αcoefficient).
Control Variables. In addition to the aforementioned variables, 12 control variables wereset. These included sex, age, years of residence, employment (e.g., self-employed, regular
employee, temporary staff, public official, full-time housewife/husband), marital status,
living arrangement (i.e., alone or with housemates), income bracket (top or bottom 10%),and home ownership.
5.4 Community-Level Explanatory Variables
Five community-level explanatory variables were set (i.e., educational qualification, sense of
lifelong learning, key competency, population size, welfare recipient rate). The first threevariables were aggregated from municipal data. The population size of each municipality wascalculated according to the Japanese government’s 2013 Resident Population Demographics andHouseholds Database. Likewise, each community’s welfare recipient rate was calculated
according to the government’s 2011 Welfare Recipient Numbers Database.

6 Analysis and Results
6.1 Descriptive Statistics
Fifteen individual-level variables and five community-level variables were set as explanatory
variables; social capital was set as a dependent variable. Descriptive statistics for each variable
are provided in Table 3. The correlation matrices for the individual and community-levelvariables are shown in Tables 4 and 5, respectively.
6.2 Multi-level ModelingMulti-level modeling was employed to investigate the three research questions (see Table 6). The
null model (Model 0) excluded explanatory variables and was used to compare variances
between other models. Model 1 included individual-level variables as control variables, whereas
Model 2 included three individual-level variables as learning variables. Model 3 included Model
2 in addition to interaction terms for household income and learning variables; this was to
examine the adjustment effect of learning factors on the relationship between household income
and social capital. Models 4, 5, and 6 added community-level variables sequentially to Model 2.
Model 7 added all community-level variables to Model 2. Model 8 included Model 7 in addition
to interaction terms for the poverty and learning variables; this was to examine the adjustment
effect of learning factors on the relationship between poverty and social capital. The Akaike
information criterion fitness index indicated that Model 6 possessed the lowest value, and wastherefore the optimal model. Analysis of the multi-level modeling was conducted using IBM SPSS
19.0.
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6.3 Direct Effects of Learning Factors on the Social Capital [RQ1]
In interpreting the results, focus was placed on Model 6 as the optimal model. As explanatory
variables at the individual-level, sense of lifelong learning (β = .118, p < .01) and key competencies(β = .321, p < .01) had a positive effect on social capital. As explanatory variables at thecommunity-level, educational qualification (β = -.134, p < .01) had a negative effect on social
capital and key competencies (β = .321, p < .01) a positive effect. These results indicate that only
key competencies had an effect on fostering social capital at both the community and individuallevels. Hence, in assuming that social capital is a social outcome of learning, qualitative
characteristics are more important than their quantitative counterparts.
Table 3. Descriptive Statistics
Variables
Dependent Variable
Social Capital Integration Index
Explanation Variable: Individual-level
Sex (male=1, female=0; Dummy)Age (Z score)Self-employed (yes=1, no=0; Dummy)
Regular employees (yes=1, no=0; Dummy)
Temporary staff (yes=1, no=0; Dummy)
Public officials (yes=1, no=0; Dummy)
Full-time house-wife/husband (yes=1, no=0; Dummy)
Live with some housemate (yes=1, no=0; Dummy)
Household income segments: Low group (Lowest 10%)
Household income segments: High group (Highest 10%)Own house (yes=1, no=0; Dummy)
Residence years (Z score)
Educational qualification
Sense of lifelong learning
Key competencies
Experimental Variables: Community-level
Population size
Welfare recipient rate
Educational qualification at the community level
A sense of lifelong learning at the community level
Key competencies at the community level

Mean

SD

SE

Min

Max

.00

1.00

.02

-3.33

3.55

.46
.00
.10
.24
.06
.05
.17
.74
.10
.08
.65
.00
13.22
4.00
.00

.50
1.00
.30
.42
.23
.21
.38
.44
.30
.28
.48
1.00
2.24
.92
1.00

.01
.02
.01
.01
.00
.00
.01
.01
.01
.00
.01
.02
.04
.02
.02

.00
-2.12
.00
.00
.00
.00
.00
.00
.00
.00
.00
-.32
9.00
1.00
-3.33

1.00
1.68
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
6.11
18.00
5.00
2.47

.03
1.32
13.20
4.00
.00

1.02
1.26
.83
.21
.23

.10
.13
.08
.02
.02

-1.10
.00
10.78
3.48
-.66

3.51
5.41
14.94
4.52
.58

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Tsuyuguchi & Kuramoto：The Effect of Key Competencies on Social Capital

Table 4. Correlation Matrix of Individual-Level Variables
Variables

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

1. Social Capital Integration Index
2. Sex-.041*

3. Age.223**.087**

4. Self-employed.079**.098**.116**

5. Regular employees-.125**.222**-.358**-.183**

6. Temporary staff-.085**.032**-.058**-.080**-.135**

7. Public officials.006**.064**-.075**-.074**-.125**-.055**

8. Full-time house-wife/husband.091**-.407**.123**-.149**-.252**-.110**-.102**

9. Live with some housemate.154**.051**.240**.064**-.082**-.067**.037**.171**

10. Household income segments: Low group-.048**-.021**.154**.012**-.141**-.009**-.065**-.066**-.245**

11. Household income segments: High group.057**-.018**-.058**-.015**.074**-.010**.055**-.040**.061**-.100**

12. Own house.199**.041**.269**.126**-.092**-.049**.023**.015**.111**-.061**.014**

13. Residence years

057**.026**.138**.088**-.093**-.010**-.005**.010**.021**.038**-.016**.098**

14. Educational qualification-.024**.095**-.343**-.068**.194**.041**.153**-.129**-.006**-.201**.146**-.040**-.109**

15. Sense of lifelong learning.218**-.017**.044**.031**-.009**-.006**.043**.015**.071**-.073**.059**.038**-.040**.135**

16. Key competencies.363**.044**.101**.083**-.001**.006**.070**-.051**.078**-.068**.108**.053**.003**.133**

3

4.294**

Note. N = 3,575. ** p < .01, * p < .05.

Table 5. Correlation Matrix of Community-Level Variables
Variables

12

1. Population size
2. Welfare recipient rate
3. Educational qualification at the community level
4. Sense of lifelong learning at the community level
5. Key competencies at the community level.250*.477**.076**.132**.002**.369**.109**.009**.346**.440**

Note. N = 100. ** p < .01, * p < .05.

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Table 6. Multi-Level Modeling for Social Capital Integration Index as a Dependent Variable
Model 0Model 1Model 2Model 3Model 4Model 5Model 6

Model 7

Model 8-.002-.181**-.153**-.509**-.139**

-.097

1.176

.745

.588

Sex
Age

-.105**.135**-.088**.088**-.082**.083**-.085*.089**-.088**.088**-.086**.087**-.084**.089**-.086**.089**

Self-employed.105**.015**.011**.014.013**.012**.011**.011**

Regular employees-.108**-.148**-.152**-.150**-.149**-.150**-.151**-.153**

Temporary staff-.238**-.279**-.270**-.281**-.280**-.280**-.281**-.283**

Public officials.036**-.073**-.067**-.077**-.073**-.076**-.078**-.073**

Full-time housewife/husband.096**.125**.123**.126**.126**.126**.126**.129**

Live with some housemate.174**.138**.138**.138**.138**.139**.139**.137**

Household income segments: Low group-.177**-.111**.507**-.133**-.108**-.124**-.119**-.118**

Household income segments: High group.193**.079**.088**.089**.079**.083**.085**.083**

Own house.232**.229**.235**.208**.220**.210**.197**.189**

Residence years.157**.128**.127**.127**.125**.129**.128**.126**

Educational qualification-.006**-.005**-.007**-.006**-.007**-.007**-.008**

Sense of lifelong learning.118**.106**.118**.117**.118**.117**.117**Key competencies.321**.312**.321**.321**.321**.321**.322**

Fixed EffectIntercept
Individual-level

Household income segments: Low group × Educational qualification-.050**

Household income segments: Low group × Sense of lifelong learning.006**

Household income segments: Low group × Key competencies.142**

Household income segments: High group × Educational qualification-.035**

Household income segments: High group × Sense of lifelong learning.125**

Household income segments: High group × Key competencies-.068**(Continued)

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Tsuyuguchi & Kuramoto：The Effect of Key Competencies on Social Capital

Model 0Model 1Model 2Model 3Model 4Model 5Model 6

Model 7

Model 8Community-level
Population size-.086**

Welfare recipient rate-.039**-.055**.311**-.026**-.089**

Educational qualification at the community level-.134**-.097**-.094**

Sense of lifelong learning at the community level.116**.104**.136**Key competencies at the community level.412**.390**.023**

Population size × Educational qualification at the community level.017**

Population size × Sense of lifelong learning at the community level-.150**

Population size × Key competencies at the community level.027**

Welfare recipient rate × Educational qualification at the community level.010**

Welfare recipient rate × Sense of lifelong learning at the community level-.012**

Welfare recipient rate × Key competencies at the community level.225**

Random Effects
Between-Community Variance.045**.043**.039**.044**.036**.033**

Educational qualification.058**.040**.000**.000**.000**.000**.000**.000**.031**.000**

Sense of lifelong learning.000**.004**.000**.000**.000**.000**.000**Key competencies.009**.007**.009**.009**.009**.009**.009**

Within-Community Variance.944**

864**.745**

742**

745**

745**

745**

.744**.744**

ICC.058**.044**.057**.055**.050**.056**.046**.042**.040**

AIC

8672**

7970**

7354**

7359**

7349**

7357**

7344**

7349**

7359**

Note. Individual-level: N = 3,575. Community-level: N = 100. ** p < .01, * p < .05.

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Journal of School Improvement and Leadership 2019

Fig. 1. Interaction Plot of Household Income Segments and Key Competencies

Fig. 2. Interaction Plot of Welfare Recipient Rate and Key Competencies

6.4 Adjustment Effect of Learning Factors in the Relationship between Economic Situation andSocial Capital [RQ2]
In interpreting the results, focus was placed on Models 3 and 8, which included interaction
terms for the learning factors and economic condition variables. In Model 3, there was astatistically significant adjustment effect for the interaction term of the low income group and key
competencies (β = .142, p < .05). In Model 8, there was a statistically significant adjustment effect101

Tsuyuguchi & Kuramoto：The Effect of Key Competencies on Social Capitalfor the interaction term of welfare recipient rate and key competencies (β = .225, p < .01).
Interaction plots are provided in Figures 1 and 2. These results suggest that key competencies
had an adjustment-effect relationship with economic conditions and social capital at both theindividual and community levels.
6.5 Community-Level Differences in the Effect of Learning Factors on Social Capital [RQ3]
If the effect of learning factors on social capital differed between communities, the variance ofthe slope presented in the random effect column (see Table 6) should be significant. However,the variance of slope relationship between the three learning factors and social capital was not
significant between communities. Hence, the learning factors’ effect on social capital was constant
between communities.

7 Discussion
The purpose of the present study was to reveal the social outcomes of learning by clarifying
the relationship between key competencies and social capital. The analysis demonstrates that key
competencies (at both individual and community levels) have direct effects on building social
capital, even controlling for a variety of variables. The components of key competencies, such as
using tools interactively, interacting in heterogeneous groups, and acting autonomously (Rychen& Salganik 2003), contribute to building ties with family, neighborhood, and members of the local
community. The present study reveals that the building of social capital is determined by thesubstantial ability of individuals formed by learning activities rather than educational
qualification levels. Moreover, community-level key competencies also have effects on thebuilding of social capital. In a community with many people who have high-level key
competencies, residents have the benefit of lowered risk of social isolation. We can interpret thisas meaning that people who have high-level key competencies make rich social ties with theirsurroundings.
As mentioned previously, social capital contributes to children’s development and growth(e.gColeman 1988; Putnam 2001). On the other hand, as is well known, when many adults in acommunity experience social isolation, this has a negative impact on children’s development andgrowth. It is very interesting that the major factor for building social capital is the key
competencies of adults. Based on the present study’s results, we might insist that children’sabilities would be increased by building social capital through adults’ abilities acquired throughlearning activities. It should be noted here that the building of social capital is hardly affected byeducational qualifications acquired through the formal education system but rather by adults’abilities (such as key competencies) acquired in the process of gaining educational qualifications
and lifelong learning rather than the educational qualifications themselves.
Key competencies have an adjustment effect on the relationship between economic hierarchyand social capital in addition to a direct effect on social capital. As mentioned previously, the key
competency level of an individual has the effect of maintaining ties with the surrounding102

Journal of School Improvement and Leadership 2019residents without falling into social isolation, even if they face economically difficult
circumstances. Such effects have been confirmed also for key competencies at the community
level. The improving effects of adult key competencies at the individual and community levels
have the power to counteract tendencies to social isolation due to bad economic conditions. The
above results suggest that to counteract social isolation and increase social ties, we should carryout social investment in learning opportunities to foster key competencies.
However, we should further investigate whether the key competency level has similar effects
on building social capital in all communities within a nation. If there are variances in the effectbetween communities, social investment effects would be similarly diverse nationwide. On theother hand, in the absence of such variance social investment effects would be uniform
nationwide. Random effect analysis shows the effect of key competencies on social capital iscommon to all communities. Therefore, we insist that the implementation of development policyof adult key competencies is possible on the national level.

8 Conclusion
Based on the analysis and discussion above, let us summarize the features of the social
outcomes of learning in Japan. The present study measured “learning experiences” in focusing
on the sense of lifelong learning and key competencies as qualitative aspects of the learning
experience, in addition to educational qualifications as a quantitative aspect of the learning
experience. In addition, the present study measured “social outcomes” in focusing on social
capital. Based on these results, we confirmed the following three features.
First, the building of social capital is affected by the qualitative aspects of learning experience.
Promoting the understanding of the significance of lifelong learning and acquiring key
competencies through learning experience are effective in building rich ties among people.
Moreover, we found that in communities whose key competencies are high on average, people
who live there have the possibility of cultivating rich ties among people. On the other hand,people who live in communities with high educational qualifications on average are vulnerable
in regard to the cultivation of rich ties among people. This confirms the claims of Inaba (2007)
and Ishida (2015). If you aim at achieving economic growth, investment in educational
qualifications is effective. However, if you aimed at building social capital, investment ineducational qualification would not have a direct effect. In order to foster ties among people inthe community, including family, relatives, and the neighborhood, it is effective to invest in thequalitative aspects of learning experience, such as a sense of lifelong learning and key
competencies, rather than investing in the quantitative aspects of learning like educational
qualifications.
Second, key competencies as a qualitative aspect of learning have an adjustment effect on therelationship between economic hierarchy and social capital. As the analysis suggests, learning
has the effect of suppressing the erosion of social capital that occurs in economic difficulties in
addition to increasing social capital otherwise. If you do nothing to cope, economic difficulties
103

Tsuyuguchi & Kuramoto：The Effect of Key Competencies on Social Capitalerode social ties and promote social isolation. Certainly, it is not socially desirable that a difficult
economic situation lead to social isolation. However, by increasing the key competency level, it
is possible to avoid such negative effects. We think that these findings reveal a new aspect ofsocial outcomes of learning that has not pointed out before.
Finally, the qualitative aspects of learning (the sense of lifelong learning and key competencies)
have direct effects on building social capital in communities anywhere. The phenomenon of“building ties through learning” would appear in any community in any country regardless ofcommunity factors. Moreover, it was confirmed that if building social capital is a policy goal, thedevelopment of the sense of lifelong learning and key competencies are valid as educational
policy or social investment at the national level.

9 Limitations and Prospects for Future Research
Finally, we briefly discuss the limitations of this study and prospects for future research.
First, the present study has methodological limitations in measuring key competencies as themost important variable in learning factors. In the present study, key competencies were
measured with a questionnaire rather than a test like PIAAC. Measurement by test is expensive.
As the present study set out to measure 10,000 people on a limited budget, measurement by test
would have been very difficult. Issues of the validity and reliability of measurement byquestionnaire of key competencies (substantially a self-assessment of key competencies) havebeen cleared. However, further efforts to improve the measurement will be necessary in the
future.
Second, the present study uses the integration index as an index of social capital. This does notallow verification of the impact of explanatory variables on each component of social capital, suchas network, reciprocal norms, and trust. Analyzing each component element leads to redundancy
issues in the results. However, the confirmation of analysis results for each component is an
important research work that we plan to carry out in the future.
Third, the present study is not sufficient to demonstrate the causality of the relation between
key competencies and social capital. This study adopted a one-shot survey. Therefore, the resultspresented in this study are correlations rather than indications of causality. In the future, we will
try to examine the causal relation between key competencies and social capital by collecting
longitudinal data.
Fourth, the present study has the problem that the community-level data are not necessarily
representative. The characteristics of a municipality are summarized by samples of no more than
100 people. In addition, the characteristics of subordinate communities were ignored by choosing
the municipality as the community unit, which is also not necessarily representative. We shouldinterpret the analysis results in light of these limitations.
Finally, the present study insufficiently describes how the development of key competencies
contributes to building social capital. The present study was able to examine the effects of key
competencies on social capital. However, quantitative research cannot reveal how the
relationship between key competency and social capital is configured in the real world. In the104

Journal of School Improvement and Leadership 2019

future, it will be necessary to carry out qualitative research on this issue.

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Acknowledgement
We would like to thanks for respondents who cooperated with this investigation. Present study was
carried out with the aid of the Japan Society for the Promotion of Science, Grant-in-Aid for Scientific
Research (A) 24243040 FY 2012-2015, and (B) 26285177 FY2013-2016.
This Paper is a slight modification version of AERA's manuscript（2017 AERA in Texs）.

107