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Differential outcomes of adult education on adult learners' increase in social inclusion

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To date a significant share of the European population can be considered at risk of social exclusion. It has been argued that adult education programmes are a powerful tool to support vulnerable adults increasing their social inclusion. This study aims to answer the question if and which subgroups of vulnerable adults experience an increase in social inclusion after joining adult education programmes. The results of our study show that 46.3% of the participants experience an increase of social inclusion in terms of ‘activation and internalization’ and 41.0% experience an increase in ‘participation and connection’. Results show that foreigners and people who live together experience a higher increase on variables of ‘activation and internalization’ and ‘participation and connection’. Furthermore, results show that learners who received school education at a primary level and have no professional qualification experience a higher increase of social inclusion on a few variables of social inclusion.
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Studies in Continuing Education
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Differential outcomes of adult
education on adult learners' increase in
social inclusion
Maurice de Greefa, Dominique Vertéb & Mien Segersc
a Artéduc, ‘s-Hertogenbosch, The Netherlands
b Department of Adult Educational Science, Faculty of Psychology
and Educational Sciences, Vrije Universiteit Brussel, Brussels,
Belgium
c Educational Research & Development, School of Business and
Economics, Maastricht University, Maastricht, The Netherlands
Published online: 14 Oct 2014.
To cite this article: Maurice de Greef, Dominique Verté & Mien Segers (2014): Differential
outcomes of adult education on adult learners' increase in social inclusion, Studies in Continuing
Education, DOI: 10.1080/0158037X.2014.967346
To link to this article: http://dx.doi.org/10.1080/0158037X.2014.967346
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Differential outcomes of adult education on adult learnersincrease in
social inclusion
Maurice de Greef
a
*, Dominique Verté
b
and Mien Segers
c
a
Artéduc, s-Hertogenbosch, The Netherlands;
b
Department of Adult Educational Science, Faculty
of Psychology and Educational Sciences, Vrije Universiteit Brussel, Brussels, Belgium;
c
Educational Research & Development, School of Business and Economics, Maastricht University,
Maastricht, The Netherlands
(Received 28 February 2014; accepted 13 August 2014)
To date a significant share of the European population can be considered at risk of
social exclusion. It has been argued that adult education programmes are a powerful
tool to support vulnerable adults increasing their social inclusion. This study aims to
answer the question if and which subgroups of vulnerable adults experience an
increase in social inclusion after joining adult education programmes. The results of
our study show that 46.3% of the participants experience an increase of social
inclusion in terms of activation and internalizationand 41.0% experience an increase
in participation and connection. Results show that foreigners and people who live
together experience a higher increase on variables of activation and internalization
and participation and connection. Furthermore, results show that learners who
received school education at a primary level and have no professional qualification
experience a higher increase of social inclusion on a few variables of social inclusion.
Keywords: continuous education; adult learning; transfer; social inclusion; learning
environment
Background
To date, social exclusion is still a threat for European society. Eurostat (2010) indicates
that 17% of the European population are considered at risk of poverty in 2007. In
addition, 22.6% of children aged 15 years had a low proficiency in reading, which was
higher than the 19.8% recorded in 2000 (Eurostat 2010). Due to these and other
comparable data of social exclusion, the European Commission underlines the necessity
of investing time, effort and resources to lift at least 20 million people out of risk of
poverty and social exclusion by 2020 (Grauman 2010). More specifically, the important
role of education has been argued.
For many years, authors like McClusky (1970) and Serrano-García and Bond (1994)
stress that education is a strong tool to empower vulnerable adults. Serrano-García and
Bond (1994) specifically states that learning can prevent problems in daily life, like
language problems in contacting official organizations, problems in assertiveness in
living together with others in one neighbourhood and the inability to make important
choices in their lives.
*Corresponding author. Email: info@arteduc.nl
Studies in Continuing Education, 2014
http://dx.doi.org/10.1080/0158037X.2014.967346
© 2014 Taylor & Francis
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The group of citizens experiencing social exclusion is very heterogeneous, for
example, low-skilled inhabitants, unemployed, early school leavers, new immigrants,
illiterate persons or older people. According to De la Fuente Anuncibay (2007), reasons
for each of these groups being at risk of social exclusion differ. A group of immigrants,
for example, risk social exclusion due to cultural backgrounds, linguistic aspects and
the distance between their country of origin and the new country (Dahlstedt and
Bevelander 2010) and the distance to the labour market of the new country (Whalgren
and Geiger 2010). For the group of unemployed people, Bjørkøe (2009) describes that
they experience a lack of achievement and self-actualization and therefore risk social
exclusion. Given the differences in background characteristics in the group of vulnerable
adults, it can be argued that adults participating in education programmes have a variety
of learning needs, and adult educators need to take them into account in order to be
effective in terms of improving social inclusion (Labouvie and Baltes 1973). To date,
although the importance of adult education in order to increase social inclusion seems to
be apparent (Nilsson 2010), it is not clear if learning needs of all learners are adequately
addressed and, therefore, if adult education positively impacts the social inclusion of all
participants regardless of their background.
This leads to the core question addressed in this study: are the positive outcomes of
adult education on participantslevel of social inclusion related to their background
characteristics?
Outcome of training and education in terms of social inclusion
The concept of social inclusion is a multidimensional one. One of the most holistic
descriptions refers to the World Banks (2007) definition, which includes four kinds of
capital, namely financial, physical, human and social capital. Hence, social inclusion can
be interpreted as a multidimensional process. In this respect, social exclusion can be
explained as a multidimensional disadvantage in terms of a lack of resources and quality
of life (Levitas et al. 2007). Besides the lack of resources and quality of life, Scharf,
Phillipson, and Smith (2005) describe social exclusion as a lack of material resources,
social relations, civic activities, basic services and neighbourhood exclusion. Likewise the
indicators of social exclusion according to the European Social Survey refer to the
regularity of meeting with friends and relatives, taking part in social activities, self-rated
physical health and mental health, self-rated income and the quality of the local area (Ogg
2005). As a result of the different descriptions of social inclusion, we define social
inclusion as a multidimensional process of individuals, who try to control and to cope
with resources and services, take part in society and its activities and connect to social
relations and feel included in the (local) area.
Social inclusion explained as multidimensional process based on four pillars
Thus, social inclusion refers to a multidimensional process of behavioural change based
on the interaction of an individual with its environment in different situations (e.g. Endler
and Magnusson 1976). The process of social inclusion can be interpreted in two different
ways. It consists of ones interaction with his or her environment in order to reach
emotional or functional satisfaction (see Figure 1). Specifically, the main axis of this
figure is the distinction between the increase of social inclusion on an individual level
(described as processes of activation and internalization) on the one hand and a collective
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level on the other hand (described as processes of participation and connection). First,
activation (process one) and internalization (process two) explain the increase of social
inclusion respectively as a functional and emotional reward for individuals themselves.
Second, participation (process three) and connection (process four) can be explained as
the functional or emotional outcome for the individual in interaction with his or her
environment.
Activation and internalization
In order to cope with practical daily problems, vulnerable adults need to increase basic
skills. In this context, social inclusion refers to the functional outcome for the individual
and can be seen as a process of activation. For example, one can read the subtitles on TV
or one is able to read and sort out his or her email. According to Bjørkøe (2009),
activation concerns the involvement of learners in meaningful and communicative
activities with a specific goal orientation. In this context, activation leads to an increase of
liveability within the direct surroundings (Fortuin and Keune 1997). Accordingly, the
learner has the opportunity to increase his or her self-control (Fortuin and Keune 1997).
Besides this increase of feelings of happiness and safety (in terms of increase of
emotional satisfaction for the individual himself or herself) can be seen as internalization.
More concretely, Mastergeorge (2001) explains the internalization of a process in which
an individual is satisfied with oneself and has the ability to lead his or her life in a
responsible and happy way.
Participation and connection
According to Bjørkøe (2009), participation is necessary in order to be socially included.
In this respect, participation refers to a growing stability of the individuals connection
with his or her environment (resulting in functional rewards). In other words, increase of
social inclusion can be explained as doing more things within the direct surroundings
(Guildford 2000). For example, one organizes activities in the neighbourhood or takes
part in official organizations (Verté, De Witte, and De Donder 2007).
Individual
I: Activation II: Internalization
Functional Emotional
III: Participation IV: Connection
Environment
Figure 1. Quadrant of social inclusion.
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On the other hand, the increase of social inclusion can be explained as an increase
of connection (e.g. Huisman et al. 2003; Priemus 2005). In this context, vulnerable
adults have better or more contact with others and experience an emotional satisfaction
after being in contact with the environment. According to Verté, De Witte, and De
Donder (2007), social inclusion is a process of meeting others and developing new social
interactions.
The influence of trainee characteristics on transfer
In the field of educational research, many authors (e.g. Peters 2004) have been discussing
the problem of fairness and more specifically inequality of education. Participants in adult
education programmes have to an important extent a demographic and socio-economic
background, which has been evidenced as being significant barriers to social inclusion. In
this respect, based on a study in 12 European countries, Tsakloglou and Papadopoulos
(2002, 211) demonstrate that in most of the countries included in the study, lack of full-
time employment, low educational qualifications, lone parenthood, non-EU citizenship
and bad health are positively and significantly associated with increased risk of social
exclusion. Verté, De Witte, and De Donder (2007) present comparable findings due to
the fact that it seems to be clear that several socio-demographic factors, more precisely
gender, racial background, age, marital status, number of children and (un)employment,
are important predictors of social exclusion.
In summary, several background and individual characteristics can influence the
learning outcomes in terms of social inclusion. In this study, we will discuss the impact of
socio-demographic factors (like gender, racial background, age, family composition and
(un)employment), educational background, motivational orientation and self-directedness
in learning.
Socio-demographic factors
According to Eurydice (2010), girls tend to achieve better results on reading and boys
show better results in mathematics in later school years. Kivinen and Rinne (1995,1996)
found that differences in gender, social inheritance of educational careers and inequality
of educational opportunities occur not only in childhood but also throughout the whole
(educational) lifespan. Therefore, we contend that gender might influence outcomes of
adult education in terms of the increase of social inclusion of the participants.
Second, the problem of educational inequality of immigrant learners has also been
addressed in many studies, mainly focusing on compulsory education. The 2006 OECD
PISA study showed that immigrants demonstrate substantially lower achievements on
reading, mathematical and science literacy skills (OECD 2006). The results also indicate
that immigrant learners not only score lower on subjects like writing and reading but also
display lower school attendance rates and lower probability of school completion.
Furthermore, with respect to age and social exclusion, Verté et al. (2011) evidenced
the influence of age on the rate of participation in society. More concretely, their research
on 70,000 older persons shows that the social network, besides informal care, doing
voluntary work and being involved in activities concerning culture, differs per category of
age, showing more participation among the young older people (6069 years old) and
less participation among the older people above 80 years.
Family circumstances, such as having a family and taking care of children, can also
influence the learning process (Preece 2010) as well as the rate of social inclusion. For
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example, negative stress such as family responsibilities can block the motivation to learn.
According to Gray (2009), older individuals who do not have a partner or are childless
experience poor support from their social network. Given the information that marital
status and number of children seem to influence the risk of social exclusion, we contend
that family status might jeopardize the outcome of participation in adult education in
terms of enhancing social inclusion.
Finally, the research of Tsakloglou and Papadopoulos (2002) shows a positive
association between the lack of full-time employment and the increased risk of social
exclusion. Participants who are unemployed are more threatened to become socially
excluded from society. According to Cedefop (2012), 43% of the learners who are
employed participate in non-formal education and training in order to improve their
competencies at work or their careers. For these learners, having a job stimulates them to
engage in education. To summarize, having a job can influence learning and possibly the
rate of social inclusion.
Educational background
According to the EU2010 (2010), the European percentage of early school leavers of
15% is problematic due to the fact that they are barred from becoming qualified for the
labour market and other forms of schooling in our society. Given these early school
leavers have often been experiencing learning problems in compulsory education (Vos,
De Vries, and Duvekot 2007), it might be expected that, more than those with a
successful prior education career, they experience problems in reaching the learning goals
of adult education programmes too.
Motivational orientation
Although there are many different theoretical perspectives on the construct of motivation
and its multidimensional nature (Gegenfurtner 2011), the role of motivational variables in
the learning process is generally accepted. In this study, we address two dimensions of
motivation: internal motivation and external motivation. In accordance with Gegenfurtner
et al. (2009), we define internal motivation as an internalized desire to participate in learning
experiences that is initiated and governed by the self. For example, participating in an adult
education programme offers the household opportunities to take care of financial matters.
External motivation refers to a desire to participate regulated by external rewards or
sanctions. For example, adults subscribe to adult education programmes in order to avoid
financial sanctions.
Self-directedness in learning
Based on a review of the different theoretical perspectives on the construct of self-
directedness in learning, Raemdonck et al. (2008) define self-directed learning as a
tendency in which learners use an active approach to learning by themselves and maintain
in overcoming barriers to learning. Raemdonck (2006) conducted interviews with low-
qualified employees and found out that there were large differences in the level of self-
directed learning within this group of employees. Based on these findings, it might be
expected that in adult education programmes groups of participants can be distinguished
based on their level of self-directedness in learning.
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Research goals and research questions
The current study aimed to measure the outcome of adult education programmes in terms
of perceived social inclusion of vulnerable adults. To be more specific, we intended to
explore differences between subgroups of participants with respect to perceived increase
in social inclusion (in terms of activation, internalization, participation and connection)
after joining programmes of adult education.
Methodology
In order to answer the research questions, a sample of learners in adult education centres
have been asked to fill in a questionnaire based on a validated instrument after a
standardized procedure. After gathering the data statistical analyses have been realized to
describe possible results.
Sample
Originally, our research targeted 1175 learners. These learners are low-qualified adult
learners joining courses in adult education centres. Specifically, the sample encompassed
three different kinds of courses in order to increase social inclusion, namely 36 different
basic skills courses, 40 different courses concerning digital competencies and 24 different
language courses. Only these three kinds of courses are part of the National Dutch
Framework of Education (Huisman and Tubbing 2005) with an explicit second goal
aiming to increase social inclusion and are provided by 31 regional adult education
centres (with 39 different locations). More specifically, each manager of an adult
education centre ensured that he or she selected courses based on face-to-face education
with more than five learners focusing on language skills, digital skills or basic skills
with an explicit goal of increasing social inclusion (for example, a course using the PC
for 55+or basic language learning in order to manage daily lifeor controlling your
own finances in daily life). At the beginning of the course, 787 learners (response rate of
67%) returned the questionnaire and 515 learners (response rate of 44%) did so at course
completion.
According to Table 1, a majority of the vulnerable adults are native born Dutch
citizens (81.8%) and female (68.7%). Furthermore, the typical learneris 41 years or
older (78.2%), has two children (42.6%), is married (64.4%), is unemployed (50.2%), has
less than 10 yearseducation (76%) and attends the course voluntarily (63.5%).
Procedure
At each location of the regional adult education centres, teachers joined a plenary training
and instruction session conducted by the researcher on guiding the learner in filling in the
questionnaire. Every teacher received a standardized written instruction for how to
stratify the low-qualified learners according to the guidelines of stratifying learners in the
different adult education centres.
Instruments
In order to measure the perceived increase of social inclusion, a validated instrument has
been used called the SIT (Social Inclusion after Transfer) instrument, consisting of social
inclusion scales and variables concerning socio-economic backgrounds, motivational
orientation and self-directedness in learning.
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Table 1. Sample characteristics: participantsbackground (N= 787).
Characteristic/category %
Gender
Male 29.7
Female 68.7
Nationality
Autochthonal 81.8
Foreign 15.8
Age
2140 16.9
4160 32.9
6180 45.3
Marital status
Married 64.4
Unmarried 16.8
Living together 5.5
Widowed 11.3
Number of children
0 15.2
1 10.9
2 42.6
3 20.1
4 6.4
Highest level of education
Primary school 2.0
Secondary school 12.7
Further education on level of middle class 3.0
Higher education 28.2
University 31.1
Other school systems 12.7
Total years of education
<5 33.7
610 33.3
1115 21
1620 5.8
Professional qualification
Yes 60.5
No 34.3
Attending courses
In behalf of work 25.3
Outside work 14.1
Both in behalf of and outside work 31.8
None 22.6
Job
Paid work 27.1
Voluntary work 14.5
Both paid and voluntary work 4.3
None 50.2
Motivation
Voluntary 63.5
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Social inclusion scales
de Greef, Segers, and Verté (2010) developed and validated in a prior study the SIT
instrument. The SIT instrument is based on self-reports. In order to overcome possible
bias of self-reports, the questionnaire has also been handed to teachers, who had higher
ratings than learners. Therefore, the self-reports can be considered as a possible
measurement of perceived increase of social inclusion. This instrument consists of two
scales measuring social inclusion.
First, activation and internalization, which has an eight-factor structure: national
language skills (9 items), digital skills (3 items), international language skills (3 items),
assertiveness (5 items), labour and upbringing skills (4 items), voluntary work and
neighbourhood skills (3 items), contact skills (7 items) and financial skills (theoretical
driven; see Table 2). Confirmatory Factor Analysis (CFA) showed a good fit of the model
to the data with χ
2
(1820, 70) by N= 787, Comparitive Fit Index (CFI) = 0.912, root mean
square error of approximation (RMSEA) = 0.079 and standardized root mean square
residual (SRMR) = 0.052.
The second scale of social inclusion, participation and connection has a seven-factor
structure, that is meeting and attempting (4 items), meeting intimate contacts (4 items),
attempting in associations in neighbourhood (7 items), being active in nature and sports
(4 items), involvement in arts and culture (2 items), gaining membership in social and
other groups (4 items) and preventing loneliness (11 items; see Table 2). Also for this
scale, all items (confirming the hypothetical factors) provided a good fit to the data with
χ
2
(1956, 50) by N= 787, CFI = 0.884, RMSEA = 0.0690.79 and SRMR = 0.063.
Socio-economic backgrounds, motivational orientation and self-directedness in learning
The background variables are age, racial background, gender, marital status, number of
children, (un)employment and educational background (highest level of education, number
of years of education, professional qualification and attendance of courses). Second in this
study, we measure two dimensions of motivation (to mention internal and external
motivation) by using a nominal variable existing of one item referring to voluntary,
encouraged or obliged participation in adult learning. Finally, the Raemdonck (2006) scale
of self-directed learning with 14 items was used. The CFA results evidenced a one-factor
structure, χ
2
(408, 40) by N= 787, CFI = 0.937, RMSEA = 0.074 and SRMR = 0.039.
Statistical analyses
As a first step, a change variable was constructed for each subscale of the activation and
internalizationscale and the participation and connectionscale by computing the
difference between T
0
and T
1
per variable. By using SPSS for each subscale, a percentage
of the learners perceiving increase of social inclusion after joining the adult education
Table 1 (Continued)
Characteristic/category %
Sent by official organization 7.8
Sent by employer or colleague 2.9
Encouraged by member of family, friend or acquaintance 11.2
Note: Missing values are excluded in percentage calculations.
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programme could be analyzed. Besides this, it is possible to define the percentage of
perceived decrease or stabilization per subscale.
Second, in order to discern differences between subgroups, a non-parametric analysis
was conducted among trainee characteristics and the perceived increase in social
inclusion. The bivariate analyses of data, depending on the variables, were performed
by means of chi-squared tests, MannWhitney tests and KruskalWallis tests. These tests
make it possible to compare the differences of perceived increase of social inclusion
between subgroups. The comparison per subgroup will be realized by using the socio-
demographic variables, the variables concerning educational background, motivation and
the rate of self-directedness in learning. The decision for this non-parametric analysis and
the use of the chi-squared tests, MannWhitney tests and KruskalWallis tests has been
made due to the fact that the data do not represent a normal distribution. Therefore,
multilevel analyses and calculations do not seem to be relevant enough and non-
parametric analysis is needed.
Table 2. Questionnaires used in this study, scales, example items per scale and reliability
coefficients (N= 308).
Questionnaires Scales
No. of
items
Example of items per
scale
Cronbachs
alpha
1. Self-directed
learning
Self-directed learning 14 Taking initiative to
learn
0.899
2. Activation and
internalization
National language skills 9 Being able to read 0.921
Digital skills 3 Being able to use the
computer
0.936
International language
skills
3 Speaking different
languages
0.889
Assertiveness 5 Being able to solve
problems
0.894
Labour and upbringing
skills
4 Being able to solve
problems
0.815
Voluntary work and
neighbourhood skills
3 Working as a volunteer 0.673
Contact skills 7 Respecting others 0.881
3. Participation and
connection
Meeting and attempting 4 Meeting people 0.819
Meeting intimate contacts 4 Visiting family 0.873
Attempting associations
in neighbourhood
7 Organizing activities in
neighbourhood
0.847
Being active in nature
and sports
4 Enjoying sport
activities
0.613
Involving into arts and
culture
2 Enjoying the arts 0.696
Getting a membership 4 Member of a
sports club
0.572
a
Preventing loneliness 11 Example feeling empty 0.800
a
a
Means that the items have a different scale, namely nominal and ordinal. So this number reflects a Spearmans
correlation.
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Due to the fact that the design of the study did not include control and experimental
groups, the researchers are aware of possible bias in the response. Therefore, the results
after analysis will be described in terms of perceived outcome instead of effects. Second
validation of the subscales has been done before the beginning of this study in order to
prohibit overestimating perceived social inclusion of the learners.
Results
First step in describing the results is the analyses of the descriptive and the perceived rate
of social inclusion for the learners. Second, the rate of perceived increase of social
inclusion has been described and explained per subgroup based on the socio-demographic
factors, the educational background, the motivational orientation and the self-directedness
in learning.
Table 3. Means and standard deviation (SD) of change in social inclusion variables for increase of
social inclusion.
Dependent variables of
social inclusion
Mean
T
0
SD
T
0
Mean
T
1
SD
T
1
Mean of
change
SD of
change
% of population
experiencing
increase
Activation and
internalization
6.83 1.37 7.60 1.24 0.77 0.88 46.3
National language skills 7.15 1.42 8.22 1.23 1.08 1.02 34.5
Digital language skills 5.03 2.23 7.55 1.98 2.52 2.01 54.7
International language
skills
4.70 2.58 6.73 2.35 2.03 1.53 45.2
Assertiveness 6.70 1.67 7.99 1.38 1.29 1.29 40.9
Labour and upbringing
skills
5.99 2.14 7.78 1.86 1.78 1.35 29.7
Voluntary work and
neighbourhood skills
3.81 2.22 6.32 2.05 2.50 1.65 35.4
Contact skills 7.12 1.73 8.30 1.34 1.18 1.18 35.3
Financial skills 6.00 2.36 7.98 2.01 1.98 1.35 23.9
Participation and
connection
4.03 1.00 4.30 1.14 0.64 0.61 41.0
Attempting in
associations and
neighbourhood
3.06 2.06 4.77 2.34 1.71 1.25 41.4
Being active in nature
and sports
5.41 1.79 6.94 1.58 1.53 1.32 30.9
Involving into arts and
culture
3.98 2.06 6.60 1.82 2.63 1.68 29.3
Getting a membership 1.23 0.26 1.60 0.30 0.36 0.22 21.8
Meeting and attempting 5.91 1.90 7.66 1.60 1.75 1.58 32.4
Meeting intimate
contacts
7.24 1.36 8.27 1.16 1.02 1.06 36.4
Preventing loneliness 2.25 0.52 2.62 0.39 0.37 0.36 44.3
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Descriptive
The descriptive findings as presented in Table 3 show that 46.3% of the participants
perceived an increase in activation and internalization. Furthermore, Table 3 shows that
41.0% of the participants perceived an increase in social inclusion in terms of
participation and connection. With respect to activation and internalization as social
inclusion indicators, the results show that 54% of the participants in our sample perceived
an increase in digital skills, but in contrast, 23.9% perceived better financial skills. With
respect to participation and connection, 44.3% of the participants perceived less
loneliness, and only 21.8% perceived to have more memberships after participating in
adult education programmes.
Differences between subgroups
Based on the results of the means of chi-squared tests, MannWhitney tests and Kruskal
Wallis tests, differences between subgroups can be determined for each kind of trainee
characteristic.
Table 4. Results of bivariate analyses between socio-demographic factors and social inclusion
variables among participants who experience an increase of social inclusion.
Independent variables
Dependent variables of
social inclusion Gender
Racial
background Age
Marital
status
Number
of
children
(Un)
employment
Activation and
internalization
0.245 0.151 0.238 0.005** 0.802 0.371
National language skills 0.237 0.028* 0.221 0.000** 0.276 0.832
Digital skills 0.460 0.935 0.000** 0.013* 0.627 0.001*
International language
skills
0.139 0.414 0.059 0.655 0.690 0.893
Assertiveness 0.041* 0.848 0.089 0.000** 0.034* 0.605
Labour and upbringing
skills
0.814 0.471 0.023* 0.048* 0.424 0.233
Voluntary work and
neighbourhood skills
0.112 0.308 0.487 0.901 0.793 0.573
Contact skills 0.563 0.110 0.236 0.000** 0.642 0.784
Financial skills 0.773 0.491 0.224 0.119 0.202 0.176
Participation and
connection
0.678 0.856 0.045* 0.124 0.528 0.505
Attempting in associations
and neighbourhood
0.525 0.897 0.140 0.832 0.868 0.202
Being active in nature and
sports
0.900 0.063 0.655 0.798 0.894 0.591
Involving into arts and
culture
0.625 0.039* 0.637 0.977 0.561 0.567
Getting a membership 0.956 0.234 0.402 0.129 0.256 0.060
Meeting and attempting 0.800 0.021* 0.138 0.024* 0.118 0.956
Meeting intimate contacts 0.706 0.018* 0.378 0.019* 0.418 0.897
Preventing loneliness 0.203 0.345 0.156 0.275 0.030* 0.334
*Correlation is significant at the 0.05 level (two-tailed). **Correlation is significant at the 0.01 level (two-tailed).
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Table 5. Results of bivariate analyses between educational background, motivation and self-directedness in learning and social inclusion variables among
participants who experience an increase of social inclusion.
Independent variables Dependent
variables of social inclusion
Highest level of
education
Number of years of
education
Professional
qualification
Attendance of
courses Motivation
Self-directedness
in learning
Activation and internalization 0.026* 0.832 0.172 0.828 0.525 0.954
National language skills 0.103 0.142 0.603 0.525 0.230 0.245
Digital skills 0.069 0.076 0.666 0.072 0.059 0.504
International language skills 0.023* 0.592 0.516 0.341 0.820 0.436
Assertiveness 0.160 0.605 0.921 0.053 0.071 0.527
Labour and upbringing skills 0.467 0.879 0.154 0.157 0.681 0.631
Voluntary work and neighbourhood skills 0.125 0.160 0.394 0.040* 0.814 0.738
Contact skills 0.249 0.254 0.762 0.223 0.331 0.888
Financial skills 0.758 0.289 0.852 0.728 0.047* 0.305
Participation and connection 0.609 0.488 0.529 0.613 0.873 0.455
Attempting in associations and
neighbourhood
0.731 0.625 0.164 0.196 0.818 0.501
Being active in nature and sports 0.391 0.641 0.177 0.807 0.205 0.171
Involving into arts and culture 0.128 0.201 0.736 0.006 0.410 0.307
Getting a membership 0.182 0.904 0.043* 0.602 0.841 0.824
Meeting and attempting 0.406 0.841 0.769 0.511 0.742 0.903
Meeting intimate contacts 0.041* 0.708 0.538 0.315 0.469 0.063
Preventing loneliness 0.150 0.247 0.280 0.204 0.851 0.781
*Correlation is significant at the 0.05 level (two-tailed). **Correlation is significant at the 0.01 level (two-tailed).
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With respect to gender, age and ethnic background, especially groups with different
ethnic backgrounds perceive differences in the rate of the increase of social inclusion
(see Table 4). Specifically, for the variables national language skills(U(417) = 9422.5;
p= 0.028), meeting and attempting(U(407) = 8695; p= 0.021) and meeting intimate
contacts(U(415) = 9222.5; p= 0.018), foreign learners perceived a higher increase than
native learners, and native learners show a higher perceived increase on involvement in
arts and culture(U(370) = 8065; p= 0.039) than foreign learners.
Second, according to Table 4, the family-related variables such as marital status seem
to be the most important and show differences between perceived rate of increase of
social inclusion on the scale activation and internalization(H(3, 430) = 12.665, p=
0.005) and more specifically in national language skills(H(3, 416) = 19.568, p= 0.000),
digital language skills(H(3, 405) = 10.754, p= 0.013), assertiveness(H(3, 404) =
18.266, p= 0.000), labour and upbringing skills(H(3, 321) = 7.925, p= 0.048),
contact skills(H(3, 393) = 18.328, p= 0.000), meeting and attempting(H(3, 406) =
9.451, p= 0.024) and meeting intimate contacts(H(3, 414) = 9.978, p= 0.019) as part
of participation and connection.
Furthermore, the extent to which the perceived level of social inclusion has increased
is also related to the educational background of the learners (see Table 5). Learners with
(special) primary school education experience show the highest perceived increase in
international language skills, and learners with higher or university education show the
least perceived increase in international language skills(r(336) = 0.023, p< 0.05). This
is also the case for the perceived increase in meeting intimate contacts(r(364) = 0.041,
p< 0.05). Besides this, people with a professional qualification show less perceived
increase in getting a membershipthan people who are unqualified (r(359) = 0.043, p<
0.05). Learners who did not attend any courses show less perceived increase in voluntary
work and neighbourhood skills than people who attend courses on behalf of an employer,
outside of work or both (H(3, 310) = 5.210, p= 0.040).
Finally, motivational orientation, the rate of employment and the rate of self-
directedness in learning show less or no different patterns related to perceptions of
increase in social inclusion (see Tables 4 and 5).
Conclusion and discussion
With this study, we aim to gain insights into the question of to what extent subgroups of
vulnerable adults differ on their perceived increase in social inclusion after joining adult
education. Our results show that 46.3% of the participants perceived an increase in social
inclusion on the subscale activation and internalization, whereas 41.0% of the
participants perceived an increase in social inclusion on the subscale participation and
connection. Furthermore, the percentage of learners perceiving an increase in social
inclusion varies from 21.8% (getting a membership) to 54.7% (digital language skills).
A closer look at the results shows that some results confirm earlier research, but other
results show different findings. The most interesting findings refer to ethnic background,
marital status and educational background. First, educational background indeed shows
that people with limited education show a higher perceived increase on certain skills,
such as international language skills and meeting intimate contacts compared to learners
with higher levels of education.
With respect to racial background and marital status, our findings show that
foreigners and people living together show a higher perceived increase on four or more
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specific variables of social inclusion than native learners (who have only lived in The
Netherlands) and people who are married, unmarried and widowed. This result confirms
among others the findings of Verté et al. (2011), which show that divorced and widowed
older persons perceived more social exclusion. The higher increase on several variables
of social inclusion encountered by foreigners compared to native learners might be
explained by the differences in perceived urgency. More concrete earlier research results
have shown that foreigners experience more urgency to improve their social inclusion
than native learners (Whalgren and Geiger 2010). In addition, differences can possibly be
explained by the fact that some foreign learners are lower skilled than native learners at
the beginning of the course. They may perceive a higher increase in social inclusion due
to their marginalized position at the beginning of the course.
According to the results of former research (e.g. Tsakloglou and Papadopoulos 2002;
Verté et al. 2011), we can expect to find different patterns for subgroups for the
background variables of (un)employment, motivational orientation and self-directedness
in learning. The lack of significant results for the fact if one does (not) have a paid job
and has been internally or externally motivated to join might be caused by the sensitivity
of our measures, due to the fact that our variables for un(employment) and motivational
orientation are nominal variables instead of scale variables based on Likert scales.
Additionally, we assume that the lack of association between self-directedness in learning
and perceived increase in social inclusion is due to the approach in the programmes of
adult education included in this study, which probably do not appeal to the learnersself-
directedness in learning. The concrete support of the teacher and the constructivist
learning approach during the lifelong learning programmes can possibly block the need
for self-directedness in learning.
However, we should be cautious in interpreting our research results. This research is a
first attempt to describe differences in learning results (in terms of social inclusion)
among adult learners after joining lifelong learning programmes. First of all, our research
focused on the differences in the group perceiving an increase in social inclusion. Taking
our results into account, a significant share of the research population does not experience
an increase, but rather stabilization or decrease in social inclusion. Therefore, more
analysis concerning this group is necessary in order to explain which part of the total
group of learners perceives a slight decrease. The rate of decrease can differ by subgroup
and can for example be explained by the differently used didactic teaching methods for
the particular subgroup. Therefore, new analyses are necessary in order to describe the
differences between perceived increase, stabilization and decrease of social inclusion for
several subgroups and the possible causes.
Regarding our sample, some subgroups were fairly small and this could have possibly
influenced the different patterns between the subgroups regarding marital status and racial
background. In addition, the different position (or levels) of some subgroups at the
beginning of the course could have resulted in differences in perceiving an increase of
social inclusion. As a result, some subgroups may have perceived a higher increase than
others.
The current study shows several directions for future research. First, our research only
concentrates on Dutch learners. In order to be able to generalize our findings, we suggest
cross-national studies based on the assumption that each country has different educational
systems and approaches in educating varying target groups. Since some target groups in
our study are fairly small, we suggest to increase the sample size of specific target groups
in future studies in order to get better research results. Third, in this study, we focused on
14 M. de Greef et al.
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the influence of individual variables on the perceived increase of social inclusion.
However, it might be expected that the training design features of adult education
programmes influence the outcomes and that insights into these programme design
features interacting with the variables addressed in this study will be needed.
In conclusion, we can confirm that there are differences between groups of vulnerable
adults in the extent to which they perceive adult education as positively affecting their
perceived level of social inclusion after joining adult education programmes. According
to the results, it is obvious that especially socio-demographic factors like racial
background and marital status next to educational background can determine the rate of
perceived social inclusion. Still in The Netherlands in the field of adult education,
programmes are not tailor-made and are comparable for native, foreign, married and
unmarried learners.
In order to attract more adult learners for continuing education, courses should be
tailored differently. According to the new results of the PIAAC study, continuing
education seems still to be necessary for a lot of citizens. For example, the results of the
PIAAC study in The Netherlands show that still 12% of the citizens experience illiteracy
(Buisman et al. 2012) and show a low level of proficiency in literacy, which can be
improved by joining courses of continuing education. In this case, professionals in
continuing education need to develop learning programmes, which reflect daily needs of
the potential learners and show the usability of learned competencies in daily life. For
example, instead of just learning grammar, learners need to practice language skills
during activities in the neighbourhood to apply a new attitude in cooperating with others
or need to have the opportunity to join a conversation at work to optimize their
conversation skills. In order to attract more learners for courses in continuing education,
these examples can be used, especially for the target-group vulnerable adults, who are
embarrassed to join education in later life due to their negative school experiences. But if
one shows the surplus value, for example, that one has better opportunities in finding a
job or that one will be better equipped in setting up his or her own small company or that
one has more opportunities to join nice activities in daily life, learning seems to be more
attractive for adults. With providing daily life examples during campaigning for
continuing education, more vulnerable adults will be motivated to join courses, while
they understand the possible surplus value of learning new knowledge or skills.
Acknowledgement
Besides this, the authors thank Dr Liesbeth de Donder for her support during the statistical analysis
and ir (ingenieur). Andrea Kuijpers for translating this article in English.
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... However, the instructional design of education programs alone does not sufficiently predict how social inclusion changes due to participation in these programs. For instance, existing research has shown that some adults who joined literacy programs did not experience an increase in certain aspects of social inclusion, such as 'reduced loneliness' and 'meeting intimate contacts' (de Greef et al., 2015). There seems to be elements besides the training design that play a role in increasing social inclusion outcomes. ...
... F. H. Nijhuis, 2006). The perception of vulnerable adults may explain part of the variations in their social inclusion outcomes: socio-demographic factors, such as marital status and ethnic background, have proven to predict how participants perceive the training and, in turn, how the perception influences their social inclusion outcomes after the adult education program (de Greef et al., 2015). Contextual factors of the participant influence the manner in which they experience the training, and therefore also how they perceive a change in social inclusion due to the training. ...
... More precisely, no prior research has investigated whether the perception of the participants plays a role in how participants experience changes in social inclusion outcomes with the literacy training (de Greef, . So far, elements of the training design deployed to predict an increase of social inclusion among vulnerable adults remain unsatisfactory (de Greef et al., 2015). Such inconclusiveness has encouraged the need to explore the role of participants' perception of the learning environment, to refine a more detailed construct of the antecedent contributive factors to the increase of social inclusion. ...
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