Applied Research Project: Research Questions

What motivates low-qualified employees to participate in training and development? A mixed-method study on their learning intentions

Eva Kyndt a,b

*, Natalie Govaerts b , Trees Claes

b , Jens De La Marche

b and

Filip Dochy b

a Institute for Information and Education Sciences, University of Antwerp, Antwerp, Belgium;

b Centre for Research on Professional Learning and Development, and Lifelong Learning,

University of Leuven, Leuven, Belgium

(Received 8 June 2012; final version received 30 December 2012)

The current research starts from the observation that low-qualified employees hold a vulnerable position on the labour market. It has been argued that learning and development can decrease this vulnerability; unfortunately research has shown that low-qualified employees participate considerably less in learning activities in comparison with high-qualified employees. According to the Theory of Reasoned Action, intention steers the actual behaviour of individuals. Therefore, this research will investigate which factors contribute to the learning intention of low-qualified employees. A cross-sectional mixed-method study was executed. In total 652 low-qualified employees completed a survey and 15 semi- structured interviews were conducted. The results show that prior participation in learning activities, self-directedness, undertaking time management activities and perceived organisational support are positively related to an employee’s learning intention. Furthermore, it is important that the content of the training offered is perceived useful and closely related to the job low-qualified employees execute.

Keywords: learning intention; low-qualified employees; theory of reasoned action

It is well known that for many years, if not decennia, our society has evolved into a

competitive industrialised society. Organisations have had to deal with technological,

environmental and economic changes. One of these changes that had a large impact

on organisations worldwide is the financial and economic crisis that started in 2008.

The reports of the Belgian government indicated that a total of 9382 bankruptcies

occurred in the following year in Belgium, an increase of 10.7% in comparison with

2008 (FOD Economics � General Board of Statistics and Economic Information, 2009). The success or failure of an organisation depends on many factors. According

to Schilling (2002), one of these factors is the investment in learning. She argues that

to cope with the constant environmental and technological changes, organisations

should invest in learning in order to acquire necessary capabilities to respond to

technological change and emerging opportunities (Angle 1989; Schilling 2002).

A deeper analysis of the failure rates shows that the industries with the highest

number of bankruptcies are also characterised by a high number of low-qualified

employees (Van Mechelen 2001), suggesting that these employees have a higher

*Corresponding author. Email: [email protected]

Studies in Continuing Education, 2013

Vol. 35, No. 3, 315�336, http://dx.doi.org/10.1080/0158037X.2013.764282

# 2013 Taylor & Francis

chance of unemployment. This can be supported by a Eurostat report (2009)

indicating that unemployment rates are the highest for low-qualified people (16%)

and the lowest for high-qualified people (6%). Research explains the vulnerability of

low-qualified employees on the labour market as a result of the decreasing demand

for traditional manual labour due to the fast-paced evolution of technology (De Grip

and Zwick 2004). According to Burdett and Smith (2002) low-qualified workers seem

to face a substantial risk of falling into a trap in which their lower educational level is

combined with fewer job opportunities and fewer training opportunities. Research

has shown that there is a difference in the level of participation in learning activities

between high- and low-qualified workers in industrialised economies (Arulampalam,

Booth, and Bryan 2004; O’Connell 2002; Taylor and Urwin 2001). Boeren, Nicaise,

and Baert (2010) showed that employees with a high level of education participate

substantially more in learning activities than employees with a low initial level of

education.

The current study focuses on the low-qualified employees as this population has

the lowest participation level (Boeren et al. 2010; O’Connell 2002; Taylor and Urwin

2001). Walberg and Tsai (1983) state that the participation in the current educational

activities can be predicted by looking at the early experiences regarding education;

therefore, this study will define a ‘low-qualified’ person based on the initial level of

education of the employee. Furthermore, Tharenou (2001) indicated that participa-

tion in learning activities can be explained by learning expectations and willingness

to learn, rather than factors within the organisational context; therefore, this study

focuses on the learning intention of employees as it predicts participation in learning

activities. The purpose of this study is to examine the learning intentions of low-

qualified employees as a first valuable step towards actual participation in learning

activities (Maurer, Weiss, and Barbeite 2003). By doing so, this study tries to help

organisations make decisions about policy strategies regarding training and

development aimed at increasing the learning intentions of their low-qualified

workforce.

In the first part of this article, the theoretical background of the study is

presented. First, a definition of low-qualified employees is given using the

International Standard Classification of Education (ISCED) scale; next, learning

intention is defined. Subsequently, the theoretical model used in this study is

presented. Finally, prior research on the variables that influence the learning

intention included in this study is presented. The second part describes the mixed-

method approach used in this study. The third part of the article concerns the

quantitative and qualitative results. The article concludes with a discussion of these

results and suggestions for future research.

Theoretical background

Low-qualified employees

This study uses the ISCED to describe low-qualified employees. This international

classification makes it possible to determine a clear cut-off point and has the

advantage that different educational degrees can be compared across different

countries. The ISCED definition provides a scale of employee attainments ranging

from 0 to 6 (Table 1).

316 E. Kyndt et al.

According to Illeris (2006), low-qualified workers have traditionally been

understood as those whose formal education consists of only a primary or lower-

secondary education and perhaps some short training courses. When the issue is

approached from a different angle, namely from those who are in a vulnerable

position on the labour market, other groups seem to be low qualified as well. Illeris

(2006) expands the traditional understanding of low-qualified employees with the

group of employees who have had a solid and officially recognised education but are

still in a vulnerable position. In short, these people are not considered as low

qualified, but their competences and skills are not in demand on the labour market

(Illeris 2006). For example, people with a general high school diploma belong to this

group. They are strictly speaking not low qualified, but there are few jobs available

on the labour market for people with no further education. They often end up in

sales or retail functions with few opportunities for career development in comparison

with other occupations (Greenhalgh and Mavrotas 1994). Following Illeris (2006),

low-qualified employees are defined as those who are part of the ISCED ranging

from levels 0 to 3. This means that all employees with a secondary school degree will

be considered low-qualified employees; this also includes the specialisation year that

individuals have obtained after their sixth year of vocational secondary education.

Learning intention

In line with prior research (e.g., Sanders et al. 2011), the Theory of Planned

Behaviour (Ajzen 1991) and the Theory of Reasoned Action (Ajzen and Fishbein

1980) will serve as the theoretical background for studying learning intentions. The

Theory of Planned Behaviour (Ajzen 1991) is an extension of the Theory of

Reasoned Action of Ajzen and Fishbein (1980).

According to Ajzen (1991) the individual’s intention to perform certain

behaviours forms a central factor within the Theory of Planned Behaviour. Ajzen

(1991) describes this intention as a factor that is assumed to capture the motivational

factors that influence behaviour, it indicates how willing individuals are to work or

try, and how much effort they are planning to invest in order to perform the planned

behaviour (Ajzen 1991). According to Ajzen the general rule for planned behaviour

is ‘. . . the stronger the intention to engage in behaviour, the more likely should be its performance’ (Ajzen 1991, 181). This statement is confirmed by research in the field

of employee learning. Maurer et al. (2003) have found that the intention to

participate in learning activities is a powerful predictor of actual participation.

According to them, a first valuable step in order to get employees to participate in

learning activities is to get them to commit to being involved in learning activities

Table 1. International Standard Classification of Education.

Level 0 Education preceding the first level (pre-primary)

Level 1 Education at the first level (primary)

Level 2 Education at the lower secondary level

Level 3 Education at the upper secondary level

Level 4 Education at the tertiary level, first stage

Level 5 Education at the tertiary level, first stage, leading to first degree

Level 6 Education at the tertiary level, second stage, leading to post-graduate degree

Studies in Continuing Education 317

(Maurer et al. 2003; Sanders et al. 2011). Moreover, empirical research has shown

that the relationship between a learning intention and participation is reciprocal in

nature; prior participation leads towards higher learning intentions, and higher

learning intentions relate to more participation in future work-related learning (e.g.,

Bates 2001; Kyndt et al. 2011; Maurer et al. 2003; Renkema 2006). In summary, a

learning intention can be described as an individual’s will to participate in a learning

activity in order to reach a desired goal. In this research, the focus is on the learning

intention of low-qualified employees regarding formal work-related training

activities.

Factors influencing a learning intention

Baert, De Rick, and Van Valckenborgh (2006) distinguish between three levels at

which possible influencing factors can be situated: the individual level, the level of

the learning activity and the contextual level that comprises the organisational

context and the broader context. At the individual level, four categories of influential

factors can be found: socio-demographic characteristics (gender, age, socio-economic

status, etc.), psychological characteristics (self-efficacy, self-directedness, etc.),

characteristics related to learning and education (educational past, level of

education, educational biography, etc.) and characteristics of the living situation

(financial situation, perception of available time, etc.) (Baert et al. 2006). It can be

mentioned that the variables, attitude, subjective norm and perceived behavioural

control, which are central within the Theory of Reasoned Action, can be located at

the individual level.

The second level at which Baert et al. (2006) identify factors that influence an

individual’s intention to learn is the level of the learning and training activity and the

environment in which this activity takes place. The learning content, work forms,

didactic sources and media are a few of the factors considering the learning activity

that are of influence. The learning context exists in the structural environment of the

learning activity itself, for example, the available rooms, the quality of the trainers,

the availability of information present, etc. The cultural environment of the learning

activity includes elements such as the language used during the training activity, the

code of conduct, etc. (Baert et al. 2006).

The final level at which Baert et al. (2006) identify factors that influence the

learning intention of individuals concerns the level of the social context and its

actors. Some of the actors who play an important role are other learners and

education providers, actors from the adjacent sector (welfare work, health care, etc.),

actors from the midfield sector (socio-cultural work, social partners, etc.) and the

government. Since the learning intention of employees related to work-related

learning is central in this field of research, a lot of attention has also been given to

the organisational context of the employee (e.g., Maurer et al. 2003; Sanders et al.

2011). Bates (2001) indicated the importance of a continuous learning culture for the

learning intention, while other researchers have investigated more specific concepts

within the organisational context. Kyndt et al. (2011), for example, have found three

factors that are related to the organisational context that influence the learning

intentions of employees: perceived job autonomy, perceived limited numbers of

opportunities and support for participation and perceived stimulation from the

318 E. Kyndt et al.

employer. In line with prior research (e.g., Maurer et al. 2003), this research study

focuses on factors regarding the individual and organisational levels.

Prior empirical research

Former research has identified several factors that are associated with a learning

intention. Although this research is limited, recently researchers have been paying

more attention to development intentions (e.g., Renkema, Schaap, and Van Dellen

2009), training intentions (e.g., Sanders et al. 2011) and learning intentions (e.g., Hurtz and Williams 2009; Kyndt et al. 2011). The factors influencing the learning

intentions found in former research and included in this study are discussed in this

section using the categorisation of Baert et al. (2006).

Characteristics of the learner

Socio-demographic characteristics

Prior research has related several socio-demographic characteristics to an employee’s

learning intention. The first socio-demographic characteristic that relates to a

learning intention is age. Several research studies indicated that age is negatively

correlated to learning motivation, meaning that older individuals are less motivated

to learn than younger people (Taylor and Urwin 2001; Warr and Birdi 1998). Boeren

et al. (2010) suggest that older employees’ motivation to learn can be explained by the fewer long-term perspectives on the labour market of older employees making the

investment to learn less attractive. Gaillard and Desmette (2010) indicate that the

effects of negative stereotyping of older employees can cause lower learning

intentions.

The relationship between gender and learning intention has been researched by

Sanders et al. (2011) indicating that lower-educated women have a significantly

higher learning intention than lower educated men. However, Kyndt et al. (2011) did

not find evidence to support this relationship, as they found no difference between males and females.

The importance of the initial level of education has been suggested by Baert et al.

(2006) and Pierce and Maurer (2009). They indicated differences in learning

intention across the initial levels of education, proposing that the individuals with

no diploma have the lowest learning intention.

Psychological characteristics

According to prior research, there is a relationship between several psychological

characteristics and the learning intention of employees. A first personal character-

istic that relates to the learning intention of employees is self-efficacy. Several

researchers have found that employees with a higher self-efficacy have a higher

intention to participate in formal learning activities (e.g., Maurer et al. 2003; Maurer and Tarulli 1994; Renkema 2006). Self-efficacy was introduced by Bandura (1977) as

a key concept in his Social Cognitive Theory. Ever since it has been the general

theory for this concept (e.g., Betz and Hackett 1981; Chen, Gully, and Eden 2001;

Gist 1987). Self-efficacy has been defined as ‘beliefs in one’s capabilities to mobilise

Studies in Continuing Education 319

the motivation, cognitive resources, and courses of action needed to meet given

situational demands’ (Wood and Bandura 1989, 408).

Another personal characteristic that has been investigated in relation to a

learning intention is self-directedness in career processes (Raemdonck et al. 2011). Self-directedness was positively related to the learning intention of employees (e.g.,

Kyndt et al. 2011) and work-related development behaviour (e.g., Gijbels, Raemdonck,

and Vervecken 2010). Miller, Kohn, and Schooler (1986) describe self-directedness as

the use of initiative, thought and independent judgement, focusing on the

independence and autonomy of the individual. Raemdonck (2006) has elaborated

more by defining it as a ‘characteristic adaptation to influence processes in life in

order to be able to cope for oneself ’ (61). The definition is a general description of

self-directedness as it includes all processes in life. According to Raemdonck (2006) self-directedness is domain-specific, meaning that the level of self-directedness and

the way individuals cope can differ from domain to domain. For the domain of

career processes, the definition would narrow down to influencing ‘career processes

in order to be able to cope for oneself on the labour market’ (Raemdonck 2006, 61).

Finally, employees’ time management can influence their learning intentions.

Time-management activities concern setting and prioritising goals, planning tasks and

monitoring progress (Peeters and Rutte 2005). While a lack of time is a frequently

used excuse for not participating in education (Illeris 2006), in most cases there is no lack of time as such, but a time conflict forms the basis for the non-participation

(Darkenwald and Valentine 1986). Undertaking time-management activities can play

an important role in resolving these time conflicts. Britton and Tesser (1991) have

found evidence that time management influences educational performance. The

current study investigates if undertaking time-management activities, such as planning

your day, making a to-do list, etc., is related to learning intentions of employees.

Organisational context

As mentioned before, the organisational context is the most relevant and most

researched context concerning employees’ learning intentions. Research has found

evidence for a positive influence of perceived organisational support on the learning

intentions of employees (Eisenberger et al. 2002; Maurer and Tarulli 1994; Tharenou

1997). Perceived organisational support is the general belief employees have in terms

of how much the organisation values their contributions and cares about their well-

being. It consists of three elements: organisational rewards and working conditions, support received from supervisors and procedural justice (Rhoades and Eisenberger

2002).

Promotion and pay are ways to reward employees (Becker 1964; Wise 1975).

According to Oshagbemi (2000) these two concepts are related to each other because

promotions often lead to increased pay. In addition, Raemdonck (2006) has found

that the potential to grow within a job is also positively related to the learning

intention of employees. Other research, as conducted by Quastel and Boshier (1982),

has found that employees with a high need for training, but low opportunities for training are less satisfied with their work content, their co-workers and promotion

opportunities. Quastel and Boshier (1982) further state that satisfied workers perceive

education as more relevant than dissatisfied workers, which suggests that satisfaction

about the promotion opportunities may lead to higher learning intentions.

320 E. Kyndt et al.

Research on the relationship between pay and learning intention is limited. Pay

satisfaction can be defined as the amount of positive affect individuals have towards

their payment (Micelli and Lane 1991). Research conducted by Kyndt et al. (2011)

suggested that financial benefits are positively related to an employee’s learning intention. Employees’ dissatisfaction with their current salary can act as a motivator

to participate in learning activities (Baert et al. 2006).

Present study

The present study focuses on low-qualified employees. In this research, low-qualified

employees are operationalised as employees with a secondary school education at the

most, corresponding with maximum level 3 on the ISCED. Due to the fast-paced

technological evolutions in the current society, the demand for manual work has

declined, making low-qualified employees more vulnerable on the labour market. De

Grip and Zwick (2004) have argued that low-qualified employees can cope with the

changes and demands of the labour market if they participate in additional and vocational training. Tynjälä (2008) stated, ‘while the organisation can create opportu-

nities for learning, it is still the reciprocal relation between the organisation and the

individual that determines learning’ (12). Besides the presence of opportunities to learn,

the employee must also show a willingness to take up these opportunities. Therefore, it

is important to further investigate the learning intention of low-qualified employees as

the preceding phase to actual participation (Kyndt et al. 2011). By using a mixed-

method approach, this study tries to provide a better understanding of what constitutes

and influences the learning intentions of low-qualified employees.

The research questions for the quantitative part of this study are:

� RQ1: Does the learning intention of employees who did not participate in past

learning activities differ from those who did participate?

� RQ2: What is the relationship between a learning intention and the individual

characteristics, self-directedness, self-efficacy and time management activities?

� RQ3: What is the relationship between a learning intention and the perceived organisational characteristics of support, promotion possibilities and pay

satisfaction?

In addition to the research questions stated above, two additional research questions

were formulated for the qualitative part of this study:

� RQ4: Which other factors could enhance or discourage the learning intention

of low-qualified employees? � RQ5: Which factors inhibit the learning intention to evolve towards actual

participation?

Method

This study uses a mix-method approach, combining quantitative and qualitative

research methods. The quantitative part of the research adopted a cross-sectional

Studies in Continuing Education 321

survey design, while the cross-sectional qualitative data were gathered by means of

semi-structured interviews.

Quantitative

Sample

The sample in this study consisted of 652 low-qualified employees. The participants

were employed in 11 different organisations that were characterised by a high

number of low-qualified employees, such as cleaning companies, automotive construction companies, penitentiaries, companies from the food industry, etc. The

majority (n �223) of the participants worked within government services. Within this group of low-qualified participants, 40 people (6.1%) did not have a diploma or

certificate of any kind, 20 (3.1%) had a primary school qualification, 89 (13.7%) had

completed the education of the lower secondary level, 23 employees (3.5%) had

completed special needs education and 480 (74.4%) had completed their education at

the upper secondary level. In total, 273 (41.9%) of the participants were male and 359

(55.1%) were female. The participants’ age ranged from 19 to 65 years, with a mean age of 42.46 years (SD �11.62).

Instrument

The first part of the questionnaire collected information regarding the participants’ personal characteristics: gender, age, seniority, number of children, initial level of

education, organisation, type of contract and previous participation in formal job-

related learning activities. The second part of the questionnaire was composed of

scales developed and validated by prior research; all variables were measured through

the perception of the participants, since Fishbein and Ajzen (1975) stated that the

perception of the environment is of more guiding influence for individual behaviour

than the objective environment. The dependent variable learning intention was

measured by five items derived from the research study of Kyndt et al. (2011). The first independent variable, self-directedness, was measured by using seven items of

the scale constructed by Raemdonck (2006). The four items measuring pay

satisfaction were derived from the research by Van Veldhoven et al. (1997). The

next variable, time management activities, was measured by seven items drawn from

the research of Britton and Tesser (1991). Organisational support was measured by

five items that were derived from the research of Rhoades, Eisenberger, and Armeli

(2001). Promotion opportunities were measured by using five items derived from the

research of Churchill, Ford, and Walker (1974) and Spector (1985). The last independent variable, self-efficacy, was measured by the scale from the research of

Chen et al. (2001). In total, 36 items measuring the independent variables were

retained after the factor analyses (see Appendix).

Analysis

The first step of the analysis comprised the calculation of the descriptive statistics.

Secondly, an exploratory factor analysis (maximum likelihood � varimax rotation) was calculated to determine the structure of the items measuring the dependent

322 E. Kyndt et al.

variable learning intention. Subsequently, an exploratory factor analysis (maximum

likelihood � varimax rotation) was performed on the items measuring the independent variables. Even though separate reliable and validated scales were

selected to measure these variables, the choice was made to perform an exploratory factor analysis in order to check the uni-dimensional structure of these scales.

The items measuring the dependent variable learning intentions had a determi-

nant equal to 0.128 and a significant Bartlett’s test (pB0.001). For the items

measuring the independent variables, the determinant equalled 0.00002, and the

significance of the Bartlett’s test was below 0.001. These results support the

conclusion that these data were suitable for factor analyses.

The analyses aimed at answering the research questions, started with an ANOVA,

to examine the relationship between prior participation in learning activities and learning intention. Since the participants in this study are employees who are

working within different organisations, we needed to check if a multilevel modelling

approach was required. To assess this, the intra-class correlation (ICC) and design

effect were calculated, based on a ‘null’ model that splits the variance between levels

(in this case individual and organisation). According to Peugh (2010) a non-zero ICC

and a design effect larger than two indicates the need for multilevel modelling. Based

on the null model predicting learning intentions (Table 2), an ICC of 0.06 and a

design effect equal to 1.6 were calculated, indicating that a multilevel approach is not necessary. Subsequently, a hierarchical regression analysis was performed. Step 1

included the individual characteristics: gender, age, seniority, marital status, number

of children, first language, contract, position in the organisation and sector as

control variables. Prior participation was included in a second step. The final and

third step included the independent variables that resulted from the exploratory

factor analysis.

Qualitative

Sample

The sample for this part of the research came from 15 low-qualified employees from

two different companies, a cleaning team within a hospital group (n �6) and several employees from government services (n �9). The majority of the participants were female (n �11). Finally, participants were between 24 and 51 years old.

Instrument

The questions of the semi-structured interview were based upon the results of the

quantitative research. All the original factors taken up in the quantitative survey

were questioned, with the exception of pay satisfaction. Since pay satisfaction was

left out of the regression model, this interview questioned if another financial factor,

Table 2. Covariance parameters: intercept model predicting learning intention.

Parameter Estimate SE

Residual 0.852690 0.053795

Intercept (subject �variance organisation) 0.057283 0.040614

Studies in Continuing Education 323

namely financial rewards, could possibly have an effect on learning intentions. In

addition, the interview also contained questions that were aimed at exploring which

other factors could enhance or discourage the learning intention of low-qualified

employees. Finally, factors that inhibit the learning intention to evolve into actual participation were explored.

Analysis

The first step of the analysis of the qualitative part of this research was the

transcription of the interviews. These transcriptions were coded and analysed using

Nvivo9 software. The unit of analysis for this research contained the entire

transcript. Chi (1997) defines a unit of analysis as a unit that represents a consistent idea, argument chain or discussion topic. For this study, this meant everything that is

related to learning intentions mentioned by the interviewee. Everything the

interviewee said was matched to learning intention when possible, and this was

marked as a unit of meaning.

The codes used for this analysis were both data- and theory-driven. Within every

unit of meaning related to learning intentions, the words and phrases mentioned by

the employee were analysed and coded. The theory-driven codes were extracted from

the quantitative part of this research and formed the basic framework for the coding process. The data-driven codes were added during the analysis.

Results

The quantitative analyses started with two exploratory factor analyses: one for the

dependent variable and one for the independent variables (pay satisfaction, time

management activities, organisational support, promotion opportunities, self-effi-

cacy and self-directedness). The factor analysis for the dependent variable yielded a one-factor solution that

explains 54.27% of the variance. The Cronbach’s reliability coefficient (a) amounted to 0.85. The second factor analysis for the independent variables resulted in a six-

factor solution explaining 55% of the variance. The six factors represent self-efficacy,

time management activities, perceived organisational support, self-directedness, pay

satisfaction and perceived promotion opportunities. All information regarding the

explained variance of these factors and the items loadings can be found in the

Appendix.

Learning intention and prior participation in learning activities (RQ1)

Three ANOVAs were performed to explore the difference in learning intention

between employees who did and did not participate in former learning activities. The

first analysis focused on employees who did and did not participate, regardless of

how long ago they participated. The second analysis compared employees who

participated during the last five years and those who did not participate during the last five years. The third analysis compared employees who participated up to one

year ago with those who did not participate during the past year. All three analyses

revealed a significant difference (Table 3). Employees who did not participate always

scored lower than those who did participate. In addition, it can be noticed that the

324 E. Kyndt et al.

effect size is the least strong for the comparison of the employees who did and did

not participate during the last year. Since the effect size of the comparison between

employees’ participation over the last five years is the strongest, this factor will be

included in the regression analysis. These results show that, after controlling for the

other variables included in this study, the difference between employees who

participated and who did not participate during the last five years remains significant

(see Table 4).

Individual and perceived organisational characteristics (RQ2 and RQ3)

The first step of the hierarchical regression, including the control variables, explained

9.7% of the variance. Prior participation, included in step 2, added 1.7% to this

amount of explained variance (FChange(1,434) �11.42, p�0.001). The final step, including the variables self-efficacy, self-directedness, time management activities,

organisational support and pay satisfaction increased the amount of explained variance by 24.7% (FChange(5,429) �33.38, p�0.001). In total, the final model predicted 36.3% of the variance. The significant predictors of an employee’s learning

intention are position in the organisation, prior participation, self-directedness,

organisational support and time management activities. All these variables predicted

learning intention in a positive way.

The qualitative analysis of the interviews showed, in line with the results of the

regression analysis, that participants with a high sense of self-directedness showed a

high learning intention. These participants had thought about how they could reach their career goals and, most often, participating in learning activities was the main

way of doing this. One of the participants had an ambitious career goal in mind; she

wanted to lead the company in the future. In order to do this she had looked up all

the courses she needed to take so that she would be ready for running a business on

her own. She has already taken a few courses to prepare step-by-step for this

possibility of taking over the business one day. As she stated:

I would have to follow a management course because I would have to do a lot of the accountancy myself as well, and marketing, but I have already taken a marketing course so that will be very useful in the future as well.

The results of the hierarchical regression analysis show that perceived organisational

support is positively related to an employee’s learning intention; the results from the

qualitative analysis add that the majority of our interviewees (n �10) responded that they think that their organisation valued continued training. In response to the

question ‘does your organisation consider training important?’ participants re-

sponded: ‘Yes, I think so. They do their best and try to get it organized . . . they try their best’ or ‘Yes, we receive training on a regular basis, also for our backaches for

Table 3. Results of ANOVA � prior participation.

Df F Sig. h 2

Participation, yes/no 1, 642 27.36 B0.001 0.041

Participation, last five years 1, 642 28.94 B0.001 0.043

Participation, last year 1, 642 18.93 B0.001 0.029

Studies in Continuing Education 325

example, not only for our job but also for ourselves, and yes I do think that a lot of

importance is attached to it’.

The results of the hierarchical regression of the research showed that pay

satisfaction was not significant when predicting employees’ learning intentions.

Therefore, the interview questioned if financial rewards could possibly influence

employees’ learning intentions. While the interviewees all agreed that a financial

bonus is pleasant, for several employees it is not a priority or motivator:

Table 4. Hierarchical regression predicting a learning intention.

Predictors B SE t p

Step 1 Constant 1.57 0.40 3.91 B0.001

Gender (female) 0.09 0.09 1.06 0.288

Age 0.005 0.01 1.01 0.316

Seniority �0.01 0.01 �2.38 B0.05 Sector (public) 0.33 0.11 3.05 B0.01

Marital status (partner) 0.09 0.05 1.73 0.084

Number of children 0.07 0.04 1.61 0.108

First language (non-Dutch) �0.05 0.08 �0.59 0.556 Type of contract (full-time) �0.001 0.001 �1.06 0.289 Position in organisation (clerk)

a 0.59 0.13 4.61 B0.001

Step 2 Constant 1.67 �

40 4.17 B0.001

Gender (female) 0.09 0.09 1.09 0.279

Age 0.01 0.01 1.02 0.310

Seniority �0.01 0.01 �2.18 B0.05 Sector (public) 0.38 0.11 3.44 B0.001

Marital status (partner) 0.10 0.05 1.92 0.055

Number of children 0.06 0.04 1.41 0.161

First language (non-Dutch) �0.05 0.09 �0.54 0.591 Type of contract (full-time) �0.001 0.001 �1.14 0.257 Position in organisation (clerk) 0.37 0.15 2.48 B0.05

Prior participation 0.35 0.12 2.88 B0.01

Step 3 Constant �0.82 0.46 �1.80 0.071 Gender (female) 0.02 0.07 0.25 0.803

Age 0.01 0.01 0.90 0.367

Seniority �0.10 0.004 �1.63 0.104 Sector (public) 0.09 0.10 0.93 0.352

Marital status (partner) 0.04 0.04 0.95 0.343

Number of children 0.05 0.04 1.45 0.149

First language (non-Dutch) �0.09 0.08 �1.14 0.253 Type of contract (full-time) �0.01 0.001 �0.70 0.487 Position in organisation (clerk) 0.31 0.13 2.40 B0.05

Prior participation 0.23 0.11 2.16 B0.05

Self-efficacy 0.07 0.07 0.90 0.367

Organisational support 0.21 0.05 3.67 B0.001

Time management 0.16 0.04 3.62 B0.001

Self-directedness 0.48 0.06 7.34 B0.001

Pay satisfaction 0.02 0.05 0.52 0.601

a Opposed to worker.

326 E. Kyndt et al.

. . . It’s always nice to get a financial bonus for attending job-related training, but for me that doesn’t matter so much. I consider it more important to learn new things and update my knowledge in order to grow.

Other employees disagreed and stated that they would participate in more job-

related training activities if they received financial rewards. When the interviewee was

asked if that meant that money was a motivator, he answered: ‘Yes, of course. If you

know what you are studying for, because you get a financial reward, then I think that

you would also try harder’.

In terms of our research questions, it can be concluded that employees with a

high sense of self-directedness also demonstrated higher learning intentions. Pay

satisfaction did not significantly predict learning intention; while financial rewards

for following training seemed to be welcomed, they are not essential motivators for all employees. In addition, the more time-management activities employees under-

took, the higher their learning intention was. Finally, perceived organisational

support was identified as a positive predictor for employee learning intentions.

Exploring other factors (RQ4)

The interviews showed that several different factors are important for the learning of

low-qualified employees. Several interviewees frequently mentioned five of these

factors.

The factor most mentioned was work relevancy; 13 of 15 participants mentioned

this as important for training activities. Work-related training means that the

training activity is related to the work activities of the participants. Interviewees said

that it was important for them that the training could be applied to their job

activities. This can be demonstrated by a quote from one of the participants that was

given as an answer to the question if he/she could think of a reason not to participate

in training activities: ‘If training does not apply or does not look interesting for my

job I think I might consider refusing this training’. A sub-factor of work relevancy

was the importance of training for their job retention. Some of the participants

mentioned that they would be more motivated to participate in a learning activity if

their job was dependent upon it: ‘I would always participate in training activities and

most certainly if my job was depending upon them’.

The second factor that was frequently mentioned was knowledge acquisition.

During the interview, many interviewees mentioned that when considering

participation, it was important to them that they could gain new knowledge. Twelve of 15 interviewees referred to this factor as important for learning.

Knowledge acquisition was important to them because, by participating in learning

activities, they could learn new skills. As one respondent said: ‘I’ve learned a lot of

new things during a training activity and I think that’s important, gaining new

knowledge and being able to use that knowledge during work activities’. Others

also mentioned the importance of learning new skills and gaining knowledge due to

the fast changing knowledge in society: ‘Because you learn new things, because

you’re not standing still and I think that is very important nowadays, with all the

knowledge evolving so quickly’.

Another important factor derived from the qualitative analysis was the usefulness

of the training; this was considered important by 11 participants. This factor is

Studies in Continuing Education 327

closely related to the factor pertaining to the work relevance of the training, but can

be distinguished because of the practical usefulness mentioned by employees. It was

important for participants that they were able to put the new knowledge to use

during job activities. A quote from the analysis demonstrates the meaning of

usefulness: ‘I think it’s important that I can use the knowledge I have gained during

training activities so that it’s not useless and I never use it again after the training has

finished’. A fourth reason that was important for learning, according to the low-qualified

employees who were interviewed, was personal development. When asked if they

could provide additional reasons for participation in learning that were important to

them, one of the participants replied, ‘maybe the development as a person, well I

think that that is important’.

Within this factor, two aspects can be distinguished: the first is competence

development, the second self-empowerment. Some of the participants mentioned

that training helped them to develop their competences and that by doing so the

efficiency of their work improved:

We used to just sweep and mop, just clean, we didn’t really know what we were doing, but now that we have done some training it’s not just cleaning anymore, we have a system for it and the jobs gets done better and on time, it’s just more efficient this way.

Regarding self-empowerment:

Participating in training activities can give me more self-confidence, you might not feel this straight away, but with every little bit that you learn your confidence increases, both at the job and personally. You gain knowledge, you transfer this to your work activities, you feel that your work is improving and when your work improves you’ll feel better about yourself, so I think self-confidence is also important.

The final motivational factor for learning found in this research was career

development:

That I gain knowledge and by doing so growing further in my job and taking that knowledge with me for a potentially different function; You can’t grow in your job without gaining new knowledge; If you can get promoted by participating in learning, I think that’s important, right? To grow in your job.

Besides these five most frequently mentioned factors, other reasons for participating

in learning activities were provided by the participants. The other factors and the

number of sources and references for each factor can be found in Table 5.

From learning intention to actual participation (RQ5)

The final research question focused on the factors that could inhibit a learning

intention evolving into actual participation. The results for this research question

were slightly different from what was expected. The expectation was that the nature

of jobs of low-qualified employees would inhibit them from participating in learning

328 E. Kyndt et al.

activities because employers are less eager to offer training activities to employees in

lower positions (Asplund and Salverda 2004; Burdett and Smith 2002). The results

show that this is not necessarily so.

Participants working in the hospital group mentioned a lot of opportunities and

support for participating in learning activities, in comparison with employees from

the government organisation. This statement can be clarified by using quotes from

employees in both organisations. Participants from the government organisation

mentioned the following regarding opportunities to participate in training and

learning activities:

I think it’s ridiculous, I understand that people at the lowest level of the organisation usually don’t expect much and just want to do their jobs, but there are also others who do want to build a career or want to try something different, but they are just left in the dark.

Participants from the hospital on the other hand told a different story. What follows

are some quotes made by workers of the hospital group:

We have quite often team meetings and we can tell them what we would like to, for example, when we want to follow a certain type of training we can just tell them and they try to work it out for us. Normally the management tells us what type of training is available but you can give suggestions to them as well. They do ask that everybody participates in learning activities, but you can retain work hours for this, I really don’t think we can complain about this here.

These answers show that it is not necessarily the job characteristics that influence the

way low-qualified employees look at learning, but rather the amount of support for,

and the way the organisations organise, training activities.

Table 5. Qualitative coding scheme for motivating factors.

Factor Interview sources References

Career development 7 14

Promotion 3 4

Expected return on investment 3 3

Interest 7 7

Financial rewards 8 17

Informal learning 1 1

Work relevancy 13 23

Job retention 6 7

Knowledge acquisition 13 24

Personal development 10 14

Competence development 3 3

Self-empowerment 3 4

Social contact 1 1

Training content and execution 6 9

Transfer 7 11

Usefulness 11 22

Work�life balance 5 10

Studies in Continuing Education 329

Discussion and conclusion

This study investigated several factors that relate to the learning intentions of low-

qualified employees. A learning intention was defined as an individual’s will to

participate in a learning activity in order to reach a desired goal. Prior research

(Kyndt et al. 2011; Maurer et al. 2003) showed that the learning intention is a robust

predictor for actual participation. Boeren et al. (2010) have found that the actual

participation rates of low-qualified employees are low. These rates can potentially be

influenced by the fact that low-qualified employees are given fewer opportunities for

participation by their employers. By focussing on the learning intention, this research

can shed light on why the participation rate among low-qualified employees is low,

apart from the fact that they are given fewer opportunities.

The results of this research showed that individual characteristics, such as self-

directedness and time management activities, influence the learning intention. Self-

directedness appeared to be the strongest influential factor. Prior research has also

shown that self-directedness is an important predictor for work-related learning

behaviour (Gijbels et al. 2010). Unfortunately, self-directedness is usually not

associated with low-qualified employees (Kyndt et al. 2011); moreover, it could be

argued that a low self-directedness could have contributed to the fact that these

employees are low-qualified in the first place. Future research is needed to explore

this hypothesis. In line with prior research, undertaking time-management activities

was found to be a significant individual characteristic (e.g., Britton and Tesser 1991).

As shown in the qualitative part of this research, employees are supported by their

organisation to participate in work-related courses, but they still have to complete all

their tasks by the end of the week. This requires employees to undertake time-

management activities in order to be able to participate.

Looking at the perception of organisational characteristics, the results showed

that the more employees perceive their organisations to be supportive, the higher

their learning intention will be. This result is in line with the research of Tharenou

(1997) that showed that participating in learning activities is linked to the perception

of how supportive an organisation is towards learning and development. However,

prior research has also argued that lower-qualified employees are offered fewer

opportunities for learning (Asplund and Salverda 2004; Hazelzet, Oomens, and

Keijzer 2009), indicating that this particular group of employees might be less

supported when it comes to learning and development. In line with the research on

the participation in work-related learning, this research study also shows that

employees with a higher function within the organisation (clerks versus workers)

demonstrated a higher learning intention (e.g., Forrier and Sels 2003; Salas-Velasco

2009; Xiao and Tsang 2004).

This research study did not find a significant relationship between pay

satisfaction and employees’ learning intentions. This result is in contrast with the

study of Kyndt et al. (2011) who found a significant positive relationship between

financial satisfaction and the learning intention of low-qualified employees, but in

line with the research of Taylor and Evans (2009) stating that low-literate workers

were not motivated to learn for monetary rewards. A possible hypothesis as to why

this research does not support the findings of Kyndt et al. (2011) is that many of the

respondents in this research were employed by the government where pay is fixed and

wages cannot be influenced by participating in training activities. Also, promotion

330 E. Kyndt et al.

opportunities are complex and rare, so training has little influence on their chances

of getting promoted and receiving a higher salary. Future research could investigate

whether different types of reward and wage systems influence the learning intention

of employees. In contrast, the qualitative data of this study suggested that employees

who are satisfied with their pay do not favour the financial rewards for participating

in a learning activity, while employees who needed money were happy to receive the

financial reward and even participated in training to receive this financial benefit. In addition, it can be noted that some interviewees indicated that they participate in

training solely to receive the financial benefit, even if they could not use the training

in their daily work.

The qualitative part of this research offers some remarkable conclusions. When

looking at the factor knowledge acquisition, one of the participants mentioned the

concern for constantly having to gain new knowledge in the fast changing knowledge

in society. This shows that low-qualified employees are aware of the continuously

changing knowledge, and that they are motivated to keep up with these changes.

Further research could investigate how low-qualified employees handle the pressure

of the fast changing knowledge in society and how their lower level of participating

in training activities influences their way of handling this (Boeren et al. 2010).

Even though this research provides interesting conclusions, some limitations

should also be considered. A first limitation is that this research focuses solely on

formal work-related learning activities because these can be described and under- stood in a very clear way. For low-qualified employees these kinds of activities are

more easily identified as learning. However, informal learning was briefly mentioned

by one of the interviewees who stated that they sometimes learn during the working

activities, without learning being a main goal. However, informal learning in general,

but specifically for low-qualified employees, is still under-researched. Prior research

focusing on people with low-literate ability has already showed that these individuals

are interested in learning but have a negative attitude towards formal learning

(Vermeersch and Vandenbrouck, 2010). In addition, Vermeersch and Vandenbrouck

(2010) stated that learning through social interaction was especially important for

low-literate adults. Continued future research could provide valuable insights into

learning activities at the workplace and the potential benefits of this informal

learning for low-qualified employees (e.g., Taylor and Evans 2009).

Another limitation of this research is the fact that it only provides a snap shot of

the learning intention and actual participation among low-qualified employees. A

longitudinal research could possibly investigate whether or not employees with

higher learning intentions will also participate more in future learning activities than their low-qualified colleagues, who have a lower learning intention.

A final limitation of this research concerns the various participating organisa-

tions and their different kinds of activities, which make generalisations difficult. A

lot of our data were collected in a government organisation, which has a different

structure than, for example, an automotive, cleaning or call centre organisation.

Further research could focus on the different learning conditions in these different

types of organisations. Prior research has shown that different types of learning

conditions exist in different types of organisations (Kyndt, Dochy, and Nijs 2009).

This can be supported by the research of Salas-Velasco (2009) that indicates that the

employees in the public sector participated more than the employees in the private

sector. Future research could investigate if there are different learning conditions

Studies in Continuing Education 331

typical for different kinds of sector and organisations, and how they influence the

learning intention of employees. Finally, the results from the qualitative part of this study need to be generalised

with caution, as they were derived from a limited sample.

The importance of enhancing participation in learning and training activities for

low-qualified employees cannot be stressed enough. By focusing on these employees,

this study hopes to contribute to the field of research on professional learning. The

current study was able to show that low-qualified employees are concerned with

changes in the knowledge in society and how to handle them. It is important for low-

qualified employees to improve their vulnerable position on the labour market. For

organisations, it is important to consider several factors when offering educational

programmes to low-qualified employees. This research has shown that prior

participation, self-directedness, time-management activities and perceived support

positively influence the learning intention. When offering educational programmes

these factors should be taken into account. Furthermore, it is important that the

content of training offered is closely related to, and useful for, the job low-qualified

employees execute. Finally, organisations can offer more guidance pertaining to the

personal development of low-qualified employees, since participating in training can

help employees grow in both their career and personal life.

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Appendix

Factor analysis learning intention

Factor 1: Learning intention (54.27% explained variance) Loadings

I intend to look for information about job-related courses and learning activities

that I could participate in.

0.816

I intend to participate in a work-related learning activity within the next year. 0.779

Sometimes I think about following a job-related training within the next year. 0.722

I intend to talk with my executive about job-related courses or trainings that I

could follow.

0.691

I Intend to talk with persons in my surroundings about job-related courses or

trainings that I could follow.

0.665

Note: Extraction method: maximum likelihood.

Studies in Continuing Education 335

Factor analysis independent variables

Factors, items, factor loadings, explained variance and reliability

Factor loading

Factor 1: Self-efficacy (12% explained variance; a �0.81) I will be able to successfully overcome many challenges. 0.82

I will be able to achieve most of the goals that I have set for myself.

Even when things are tough, I can perform quite well. 0.64

I am confident that I can perform effectively on many different tasks. 0.55

When facing difficult tasks, I am certain that I will accomplish them. 0.54

In general, I think that I can obtain outcomes that are important to me. 0.57

I believe I can succeed in practically any challenge I take on. 0.80

I set and honour priorities. 0.47

I have a clear idea of what I want to accomplish during the next week. 0.52

Factor 2: Perceived organisational support (10% explained variance; a �0.79) My organisation is willing to help me if I need a special favour. 0.73

My organisation cares about my opinion. 0.72

My organisation strongly considers my goals and values. 0.64

My organisation shows little concern for me (R). 0.71

Those who do well have a fair chance for promotion here. 0.53

People in this organisation are being promoted equally fast as in other

organisations.

0.56

Factor 3: Time management (10% explained variance; a �0.84) I plan my day before I start it. 0.81

I make a list of the things I have to do each day. 0.81

I make a schedule of the activities I have to do on workdays. 0.79

I spend time each day planning. 0.73

I write a set of goals for myself for each day. 0.62

Factor 4: Self-directedness (9% explained variance; a �0.76) I find it important to think about the progression of my career. 0.80

I find it important to get in touch with people who can be of importance to

my career as much as possible.

0.69

I keep myself informed on new possibilities to develop my career. 0.73

I find it important to consider if my present position in the department and

the organisation is the right one.

0.55

I find it important to think about what I want to realise in my career during

the following years.

0.51

Factor 5: Pay satisfaction (9% explained variance; a �0.81) I am being paid well for the work I am doing here. 0.78

In my company the salaries are good. 0.79

I can manage easily on my wage. 0.75

I think my salary is fair in comparison with my colleagues. 0.70

Factor 6: Perceived promotion opportunities (5% explained variance; a �0.56) Regular promotion is a rule within this organisation. 0.64

Promotion here is based on ability. 0.62

In my current job, there a litte promotional opportunities (R). 0.48

Note: Extraction method: maximum likelihood, cut-off factor loadings �0.40; rotation method: Varimax with Kaiser normalisation.

336 E. Kyndt et al.

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