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What Motivates Low-Qualified Employees to Participate in Training and Development? A Mixed-Method Study on their Learning Intentions

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Title: What Motivates Low-Qualified Employees to Participate in Training and Development? A Mixed-Method Study on their Learning Intentions
Language: English
Authors: Kyndt, Eva, Govaerts, Natalie, Claes, Trees
Source: Studies in Continuing Education. 2013 35(3):315-336.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 22
Publication Date: 2013
Document Type: Journal Articles
Reports - Research
Education Level: Adult Education
Descriptors: Adult Education, Motivation, Mixed Methods Research, Labor Market, Surveys, Semi Structured Interviews, Intentional Learning, Behavior Theories, Employee Attitudes, Time Management, Unskilled Workers, Gender Differences, Age Differences, Educational Attitudes, Student Characteristics, Measures (Individuals), Predictor Variables, Factor Analysis, Statistical Analysis, Reliability, Organizational Climate, Regression (Statistics), Influences, Questionnaires
DOI: 10.1080/0158037X.2013.764282
ISSN: 0158-037X
Abstract: 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.
Abstractor: As Provided
Number of References: 65
Entry Date: 2014
Accession Number: EJ1023186
Database: ERIC
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  Value: <anid>AN0091735420;36r01nov.13;2019Feb13.16:55;v2.2.500</anid> <title id="AN0091735420-1">What motivates low-qualified employees to participate in training and development? A mixed-method study on their learning intentions. </title> <p>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.</p> <p>Keywords: learning intention; low-qualified employees; theory of reasoned action</p> <p>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, [<reflink idref="bib22" id="ref1">22</reflink>]). The success or failure of an organisation depends on many factors. According to Schilling ([<reflink idref="bib51" id="ref2">51</reflink>]), 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 [<reflink idref="bib3" id="ref3">3</reflink>]; Schilling [<reflink idref="bib51" id="ref4">51</reflink>]).</p> <p>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 [<reflink idref="bib58" id="ref5">58</reflink>]), suggesting that these employees have a higher chance of unemployment. This can be supported by a Eurostat report ([<reflink idref="bib20" id="ref6">20</reflink>]) 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 [<reflink idref="bib18" id="ref7">18</reflink>]). According to Burdett and Smith ([<reflink idref="bib13" id="ref8">13</reflink>]) 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 [<reflink idref="bib4" id="ref9">4</reflink>]; O'Connell [<reflink idref="bib37" id="ref10">37</reflink>]; Taylor and Urwin [<reflink idref="bib54" id="ref11">54</reflink>]). Boeren, Nicaise, and Baert ([<reflink idref="bib11" id="ref12">11</reflink>]) showed that employees with a high level of education participate substantially more in learning activities than employees with a low initial level of education.</p> <p>The current study focuses on the low-qualified employees as this population has the lowest participation level (Boeren et al. [<reflink idref="bib11" id="ref13">11</reflink>]; O'Connell [<reflink idref="bib37" id="ref14">37</reflink>]; Taylor and Urwin [<reflink idref="bib54" id="ref15">54</reflink>]). Walberg and Tsai ([<reflink idref="bib61" id="ref16">61</reflink>]) 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 ([<reflink idref="bib56" id="ref17">56</reflink>]) indicated that participation 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 [<reflink idref="bib34" id="ref18">34</reflink>]). 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.</p> <p>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.</p> <hd id="AN0091735420-2">Theoretical background</hd> <p></p> <hd id="AN0091735420-3">Low-qualified employees</hd> <p>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).</p> <p>Table 1. International Standard Classification of Education.</p> <p> <ephtml> <table><tbody><tr><td>Level 0</td><td>Education preceding the first level (pre-primary)</td></tr><tr><td>Level 1</td><td>Education at the first level (primary)</td></tr><tr><td>Level 2</td><td>Education at the lower secondary level</td></tr><tr><td>Level 3</td><td>Education at the upper secondary level</td></tr><tr><td>Level 4</td><td>Education at the tertiary level, first stage</td></tr><tr><td>Level 5</td><td>Education at the tertiary level, first stage, leading to first degree</td></tr><tr><td>Level 6</td><td>Education at the tertiary level, second stage, leading to post-graduate degree</td></tr></tbody></table> </ephtml> </p> <p>According to Illeris ([<reflink idref="bib30" id="ref19">30</reflink>]), 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 ([<reflink idref="bib30" id="ref20">30</reflink>]) 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 [<reflink idref="bib30" id="ref21">30</reflink>]). 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 [<reflink idref="bib27" id="ref22">27</reflink>]). Following Illeris ([<reflink idref="bib30" id="ref23">30</reflink>]), 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.</p> <hd id="AN0091735420-4">Learning intention</hd> <p>In line with prior research (e.g., Sanders et al. [<reflink idref="bib50" id="ref24">50</reflink>]), the Theory of Planned Behaviour (Ajzen [<reflink idref="bib1" id="ref25">1</reflink>]) and the Theory of Reasoned Action (Ajzen and Fishbein [<reflink idref="bib2" id="ref26">2</reflink>]) will serve as the theoretical background for studying learning intentions. The Theory of Planned Behaviour (Ajzen [<reflink idref="bib1" id="ref27">1</reflink>]) is an extension of the Theory of Reasoned Action of Ajzen and Fishbein ([<reflink idref="bib2" id="ref28">2</reflink>]).</p> <p>According to Ajzen ([<reflink idref="bib1" id="ref29">1</reflink>]) the individual's intention to perform certain behaviours forms a central factor within the Theory of Planned Behaviour. Ajzen ([<reflink idref="bib1" id="ref30">1</reflink>]) 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 [<reflink idref="bib1" id="ref31">1</reflink>]). 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 [<reflink idref="bib1" id="ref32">1</reflink>], 181). This statement is confirmed by research in the field of employee learning. Maurer et al. ([<reflink idref="bib34" id="ref33">34</reflink>]) 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 (Maurer et al. [<reflink idref="bib34" id="ref34">34</reflink>]; Sanders et al. [<reflink idref="bib50" id="ref35">50</reflink>]). 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 [<reflink idref="bib8" id="ref36">8</reflink>]; Kyndt et al. [<reflink idref="bib32" id="ref37">32</reflink>]; Maurer et al. [<reflink idref="bib34" id="ref38">34</reflink>]; Renkema [<reflink idref="bib45" id="ref39">45</reflink>]). 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.</p> <hd id="AN0091735420-5">Factors influencing a learning intention</hd> <p>Baert, De Rick, and Van Valckenborgh ([<reflink idref="bib6" id="ref40">6</reflink>]) 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. [<reflink idref="bib6" id="ref41">6</reflink>]). 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.</p> <p>The second level at which Baert et al. ([<reflink idref="bib6" id="ref42">6</reflink>]) 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. [<reflink idref="bib6" id="ref43">6</reflink>]).</p> <p>The final level at which Baert et al. ([<reflink idref="bib6" id="ref44">6</reflink>]) 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. [<reflink idref="bib34" id="ref45">34</reflink>]; Sanders et al. [<reflink idref="bib50" id="ref46">50</reflink>]). Bates ([<reflink idref="bib8" id="ref47">8</reflink>]) 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. ([<reflink idref="bib32" id="ref48">32</reflink>]), 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 employer. In line with prior research (e.g., Maurer et al. [<reflink idref="bib34" id="ref49">34</reflink>]), this research study focuses on factors regarding the individual and organisational levels.</p> <hd id="AN0091735420-6">Prior empirical research</hd> <p>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 [<reflink idref="bib46" id="ref50">46</reflink>]), training intentions (e.g., Sanders et al. [<reflink idref="bib50" id="ref51">50</reflink>]) and learning intentions (e.g., Hurtz and Williams [<reflink idref="bib29" id="ref52">29</reflink>]; Kyndt et al. [<reflink idref="bib32" id="ref53">32</reflink>]). 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. ([<reflink idref="bib6" id="ref54">6</reflink>]).</p> <hd id="AN0091735420-7">Characteristics of the learner</hd> <p></p> <hd id="AN0091735420-8">Socio-demographic characteristics</hd> <p>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 [<reflink idref="bib54" id="ref55">54</reflink>]; Warr and Birdi [<reflink idref="bib62" id="ref56">62</reflink>]). Boeren et al. ([<reflink idref="bib11" id="ref57">11</reflink>]) 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 ([<reflink idref="bib24" id="ref58">24</reflink>]) indicate that the effects of negative stereotyping of older employees can cause lower learning intentions.</p> <p>The relationship between gender and learning intention has been researched by Sanders et al. ([<reflink idref="bib50" id="ref59">50</reflink>]) indicating that lower-educated women have a significantly higher learning intention than lower educated men. However, Kyndt et al. ([<reflink idref="bib32" id="ref60">32</reflink>]) did not find evidence to support this relationship, as they found no difference between males and females.</p> <p>The importance of the initial level of education has been suggested by Baert et al. ([<reflink idref="bib6" id="ref61">6</reflink>]) and Pierce and Maurer ([<reflink idref="bib41" id="ref62">41</reflink>]). They indicated differences in learning intention across the initial levels of education, proposing that the individuals with no diploma have the lowest learning intention.</p> <hd id="AN0091735420-9">Psychological characteristics</hd> <p>According to prior research, there is a relationship between several psychological characteristics and the learning intention of employees. A first personal characteristic 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. [<reflink idref="bib34" id="ref63">34</reflink>]; Maurer and Tarulli [<reflink idref="bib33" id="ref64">33</reflink>]; Renkema [<reflink idref="bib45" id="ref65">45</reflink>]). Self-efficacy was introduced by Bandura ([<reflink idref="bib7" id="ref66">7</reflink>]) 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 [<reflink idref="bib10" id="ref67">10</reflink>]; Chen, Gully, and Eden [<reflink idref="bib14" id="ref68">14</reflink>]; Gist [<reflink idref="bib26" id="ref69">26</reflink>]). Self-efficacy has been defined as 'beliefs in one's capabilities to mobilise the motivation, cognitive resources, and courses of action needed to meet given situational demands' (Wood and Bandura [<reflink idref="bib64" id="ref70">64</reflink>], 408).</p> <p>Another personal characteristic that has been investigated in relation to a learning intention is self-directedness in career processes (Raemdonck et al. [<reflink idref="bib44" id="ref71">44</reflink>]). Self-directedness was positively related to the learning intention of employees (e.g., Kyndt et al. [<reflink idref="bib32" id="ref72">32</reflink>]) and work-related development behaviour (e.g., Gijbels, Raemdonck, and Vervecken [<reflink idref="bib25" id="ref73">25</reflink>]). Miller, Kohn, and Schooler ([<reflink idref="bib36" id="ref74">36</reflink>]) describe self-directedness as the use of initiative, thought and independent judgement, focusing on the independence and autonomy of the individual. Raemdonck ([<reflink idref="bib43" id="ref75">43</reflink>]) has elaborated more by defining it as a 'characteristic adaptation to influence processes in life in order to be able to cope for oneself' (<reflink idref="bib61" id="ref76">61</reflink>). The definition is a general description of self-directedness as it includes all processes in life. According to Raemdonck ([<reflink idref="bib43" id="ref77">43</reflink>]) 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 [<reflink idref="bib43" id="ref78">43</reflink>], 61).</p> <p>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 [<reflink idref="bib39" id="ref79">39</reflink>]). While a lack of time is a frequently used excuse for not participating in education (Illeris [<reflink idref="bib30" id="ref80">30</reflink>]), 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 [<reflink idref="bib17" id="ref81">17</reflink>]). Undertaking time-management activities can play an important role in resolving these time conflicts. Britton and Tesser ([<reflink idref="bib12" id="ref82">12</reflink>]) 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.</p> <hd id="AN0091735420-10">Organisational context</hd> <p>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. [<reflink idref="bib19" id="ref83">19</reflink>]; Maurer and Tarulli [<reflink idref="bib33" id="ref84">33</reflink>]; Tharenou [<reflink idref="bib55" id="ref85">55</reflink>]). 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 [<reflink idref="bib48" id="ref86">48</reflink>]).</p> <p>Promotion and pay are ways to reward employees (Becker [<reflink idref="bib9" id="ref87">9</reflink>]; Wise [<reflink idref="bib63" id="ref88">63</reflink>]). According to Oshagbemi ([<reflink idref="bib38" id="ref89">38</reflink>]) these two concepts are related to each other because promotions often lead to increased pay. In addition, Raemdonck ([<reflink idref="bib43" id="ref90">43</reflink>]) 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 ([<reflink idref="bib42" id="ref91">42</reflink>]), 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 ([<reflink idref="bib42" id="ref92">42</reflink>]) 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.</p> <p>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 [<reflink idref="bib35" id="ref93">35</reflink>]). Research conducted by Kyndt et al. ([<reflink idref="bib32" id="ref94">32</reflink>]) 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. [<reflink idref="bib6" id="ref95">6</reflink>]).</p> <hd id="AN0091735420-11">Present study</hd> <p>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 ([<reflink idref="bib18" id="ref96">18</reflink>]) 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 ([<reflink idref="bib57" id="ref97">57</reflink>]) stated, 'while the organisation can create opportunities for learning, it is still the reciprocal relation between the organisation and the individual that determines learning' (<reflink idref="bib12" id="ref98">12</reflink>). 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. [<reflink idref="bib32" id="ref99">32</reflink>]). 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.</p> <p>The research questions for the quantitative part of this study are:</p> <p></p> <ulist> <item> RQ1: Does the learning intention of employees who did not participate in past learning activities differ from those who did participate?</item> <p></p> <item> RQ2: What is the relationship between a learning intention and the individual characteristics, self-directedness, self-efficacy and time management activities?</item> <p></p> <item> RQ3: What is the relationship between a learning intention and the perceived organisational characteristics of support, promotion possibilities and pay satisfaction?</item> </ulist> <p>In addition to the research questions stated above, two additional research questions were formulated for the qualitative part of this study:</p> <p></p> <ulist> <item> RQ4: Which other factors could enhance or discourage the learning intention of low-qualified employees?</item> <p></p> <item> RQ5: Which factors inhibit the learning intention to evolve towards actual participation?</item> </ulist> <hd id="AN0091735420-12">Method</hd> <p>This study uses a mix-method approach, combining quantitative and qualitative research methods. The quantitative part of the research adopted a cross-sectional survey design, while the cross-sectional qualitative data were gathered by means of semi-structured interviews.</p> <hd id="AN0091735420-13">Quantitative</hd> <p></p> <hd id="AN0091735420-14">Sample</hd> <p>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 (<emph>n</emph>=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).</p> <hd id="AN0091735420-15">Instrument</hd> <p>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 ([<reflink idref="bib21" id="ref100">21</reflink>]) 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. ([<reflink idref="bib32" id="ref101">32</reflink>]). The first independent variable, self-directedness, was measured by using seven items of the scale constructed by Raemdonck ([<reflink idref="bib43" id="ref102">43</reflink>]). The four items measuring pay satisfaction were derived from the research by Van Veldhoven et al. ([<reflink idref="bib59" id="ref103">59</reflink>]). The next variable, time management activities, was measured by seven items drawn from the research of Britton and Tesser ([<reflink idref="bib12" id="ref104">12</reflink>]). Organisational support was measured by five items that were derived from the research of Rhoades, Eisenberger, and Armeli ([<reflink idref="bib47" id="ref105">47</reflink>]). Promotion opportunities were measured by using five items derived from the research of Churchill, Ford, and Walker ([<reflink idref="bib16" id="ref106">16</reflink>]) and Spector ([<reflink idref="bib52" id="ref107">52</reflink>]). The last independent variable, self-efficacy, was measured by the scale from the research of Chen et al. ([<reflink idref="bib14" id="ref108">14</reflink>]). In total, 36 items measuring the independent variables were retained after the factor analyses (see Appendix).</p> <hd id="AN0091735420-16">Analysis</hd> <p>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 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.</p> <p>The items measuring the dependent variable learning intentions had a determinant equal to 0.128 and a significant Bartlett's test (<emph>p</emph><0.001). 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.</p> <p>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 ([<reflink idref="bib40" id="ref109">40</reflink>]) 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.</p> <p>Table 2. Covariance parameters: intercept model predicting learning intention.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td>Parameter</td><td>Estimate</td><td>SE</td></tr></thead><tbody><tr><td>Residual</td><td char=".">0.852690</td><td char=".">0.053795</td></tr><tr><td>Intercept (subject = variance organisation)</td><td char=".">0.057283</td><td char=".">0.040614</td></tr></tbody></table> </ephtml> </p> <hd id="AN0091735420-17">Qualitative</hd> <p></p> <hd id="AN0091735420-18">Sample</hd> <p>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 (<emph>n =</emph>6) and several employees from government services (<emph>n =</emph>9). The majority of the participants were female (<emph>n</emph>=11). Finally, participants were between 24 and 51 years old.</p> <hd id="AN0091735420-19">Instrument</hd> <p>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, 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.</p> <hd id="AN0091735420-20">Analysis</hd> <p>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 ([<reflink idref="bib15" id="ref110">15</reflink>]) 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.</p> <p>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.</p> <hd id="AN0091735420-21">Results</hd> <p>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-efficacy and self-directedness).</p> <p>The factor analysis for the dependent variable yielded a one-factor solution that explains 54.27% of the variance. The Cronbach's reliability coefficient (α) 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.</p> <hd id="AN0091735420-22">Learning intention and prior participation in learning activities (RQ1)</hd> <p>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 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).</p> <p>Table 3. Results of ANOVA – prior participation.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td /><td>Df</td><td><italic>F</italic></td><td>Sig.</td><td><italic>η</italic><sup>2</sup></td></tr></thead><tbody><tr><td>Participation, yes/no</td><td>1, 642</td><td>27.36</td><td><0.001</td><td>0.041</td></tr><tr><td>Participation, last five years</td><td>1, 642</td><td>28.94</td><td><0.001</td><td>0.043</td></tr><tr><td>Participation, last year</td><td>1, 642</td><td>18.93</td><td><0.001</td><td>0.029</td></tr></tbody></table> </ephtml> </p> <p>Table 4. Hierarchical regression predicting a learning intention.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td /><td>Predictors</td><td><italic>B</italic></td><td>SE</td><td><italic>t</italic></td><td><italic>p</italic></td></tr></thead><tbody><tr><td>Step 1</td><td>Constant</td><td char=".">1.57</td><td char=".">0.40</td><td char=".">3.91</td><td char="."><italic><0.001</italic></td></tr><tr><td /><td>Gender (female)</td><td char=".">0.09</td><td char=".">0.09</td><td char=".">1.06</td><td char=".">0.288</td></tr><tr><td /><td>Age</td><td char=".">0.005</td><td char=".">0.01</td><td char=".">1.01</td><td char=".">0.316</td></tr><tr><td /><td>Seniority</td><td char=".">−0.01</td><td char=".">0.01</td><td char=".">−2.38</td><td char="."><italic><0.05</italic></td></tr><tr><td /><td>Sector (public)</td><td char=".">0.33</td><td char=".">0.11</td><td char=".">3.05</td><td char="."><italic><0.01</italic></td></tr><tr><td /><td>Marital status (partner)</td><td char=".">0.09</td><td char=".">0.05</td><td char=".">1.73</td><td char=".">0.084</td></tr><tr><td /><td>Number of children</td><td char=".">0.07</td><td char=".">0.04</td><td char=".">1.61</td><td char=".">0.108</td></tr><tr><td /><td>First language (non-Dutch)</td><td char=".">−0.05</td><td char=".">0.08</td><td char=".">−0.59</td><td char=".">0.556</td></tr><tr><td /><td>Type of contract (full-time)</td><td char=".">−0.001</td><td char=".">0.001</td><td char=".">−1.06</td><td char=".">0.289</td></tr><tr><td /><td>Position in organisation (clerk)<xref ref-type="fn" rid="tfn1" /></td><td char=".">0.59</td><td char=".">0.13</td><td char=".">4.61</td><td char="."><italic><0.001</italic></td></tr><tr><td>Step 2</td><td>Constant</td><td char=".">1.67</td><td><sup>~</sup>40</td><td char=".">4.17</td><td char="."><italic><0.001</italic></td></tr><tr><td /><td>Gender (female)</td><td char=".">0.09</td><td char=".">0.09</td><td char=".">1.09</td><td char=".">0.279</td></tr><tr><td /><td>Age</td><td char=".">0.01</td><td char=".">0.01</td><td char=".">1.02</td><td char=".">0.310</td></tr><tr><td /><td>Seniority</td><td char=".">−0.01</td><td char=".">0.01</td><td char=".">−2.18</td><td char="."><italic><0.05</italic></td></tr><tr><td /><td>Sector (public)</td><td char=".">0.38</td><td char=".">0.11</td><td char=".">3.44</td><td char="."><italic><0.001</italic></td></tr><tr><td /><td>Marital status (partner)</td><td char=".">0.10</td><td char=".">0.05</td><td char=".">1.92</td><td char=".">0.055</td></tr><tr><td /><td>Number of children</td><td char=".">0.06</td><td char=".">0.04</td><td char=".">1.41</td><td char=".">0.161</td></tr><tr><td /><td>First language (non-Dutch)</td><td char=".">−0.05</td><td char=".">0.09</td><td char=".">−0.54</td><td char=".">0.591</td></tr><tr><td /><td>Type of contract (full-time)</td><td char=".">−0.001</td><td char=".">0.001</td><td char=".">−1.14</td><td char=".">0.257</td></tr><tr><td /><td>Position in organisation (clerk)</td><td char=".">0.37</td><td char=".">0.15</td><td char=".">2.48</td><td char="."><italic><0.05</italic></td></tr><tr><td /><td>Prior participation</td><td char=".">0.35</td><td char=".">0.12</td><td char=".">2.88</td><td char="."><italic><0.01</italic></td></tr><tr><td>Step 3</td><td>Constant</td><td char=".">−0.82</td><td char=".">0.46</td><td char=".">−1.80</td><td char=".">0.071</td></tr><tr><td /><td>Gender (female)</td><td char=".">0.02</td><td char=".">0.07</td><td char=".">0.25</td><td char=".">0.803</td></tr><tr><td /><td>Age</td><td char=".">0.01</td><td char=".">0.01</td><td char=".">0.90</td><td char=".">0.367</td></tr><tr><td /><td>Seniority</td><td char=".">−0.10</td><td char=".">0.004</td><td char=".">−1.63</td><td char=".">0.104</td></tr><tr><td /><td>Sector (public)</td><td char=".">0.09</td><td char=".">0.10</td><td char=".">0.93</td><td char=".">0.352</td></tr><tr><td /><td>Marital status (partner)</td><td char=".">0.04</td><td char=".">0.04</td><td char=".">0.95</td><td char=".">0.343</td></tr><tr><td /><td>Number of children</td><td char=".">0.05</td><td char=".">0.04</td><td char=".">1.45</td><td char=".">0.149</td></tr><tr><td /><td>First language (non-Dutch)</td><td char=".">−0.09</td><td char=".">0.08</td><td char=".">−1.14</td><td char=".">0.253</td></tr><tr><td /><td>Type of contract (full-time)</td><td char=".">−0.01</td><td char=".">0.001</td><td char=".">−0.70</td><td char=".">0.487</td></tr><tr><td /><td>Position in organisation (clerk)</td><td char=".">0.31</td><td char=".">0.13</td><td char=".">2.40</td><td char="."><italic><0.05</italic></td></tr><tr><td /><td>Prior participation</td><td char=".">0.23</td><td char=".">0.11</td><td char=".">2.16</td><td char="."><italic><0.05</italic></td></tr><tr><td /><td>Self-efficacy</td><td char=".">0.07</td><td char=".">0.07</td><td char=".">0.90</td><td char=".">0.367</td></tr><tr><td /><td>Organisational support</td><td char=".">0.21</td><td char=".">0.05</td><td char=".">3.67</td><td char="."><italic><0.001</italic></td></tr><tr><td /><td>Time management</td><td char=".">0.16</td><td char=".">0.04</td><td char=".">3.62</td><td char="."><italic><0.001</italic></td></tr><tr><td /><td>Self-directedness</td><td char=".">0.48</td><td char=".">0.06</td><td char=".">7.34</td><td char="."><italic><0.001</italic></td></tr><tr><td /><td>Pay satisfaction</td><td char=".">0.02</td><td char=".">0.05</td><td char=".">0.52</td><td char=".">0.601</td></tr></tbody></table> </ephtml> </p> <p>1 Opposed to worker.</p> <hd id="AN0091735420-23">Individual and perceived organisational characteristics (RQ2 and RQ3)</hd> <p>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 (<emph>F</emph><subs>Change</subs>(<reflink idref="bib1" id="ref111">1</reflink>,<reflink idref="bib434" id="ref112">434</reflink>) = 11.42, <emph>p</emph>>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% (<emph>F</emph><subs>Change</subs>(<reflink idref="bib5" id="ref113">5</reflink>,<reflink idref="bib429" id="ref114">429</reflink>) = 33.38, <emph>p</emph>>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.</p> <p>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:</p> <p>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.</p> <p>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 (<emph>n</emph>=10) responded that they think that their organisation valued continued training. In response to the question 'does your organisation consider training important?' participants responded: '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 example, not only for our job but also for ourselves, and yes I do think that a lot of importance is attached to it'.</p> <p>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:</p> <p>... 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.</p> <p>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'.</p> <p>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 undertook, the higher their learning intention was. Finally, perceived organisational support was identified as a positive predictor for employee learning intentions.</p> <hd id="AN0091735420-24">Exploring other factors (RQ4)</hd> <p>The interviews showed that several different factors are important for the learning of low-qualified employees. Several interviewees frequently mentioned five of these factors.</p> <p>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'.</p> <p>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'.</p> <p>Another important factor derived from the qualitative analysis was the usefulness of the training; this was considered important by 11 participants. This factor is 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'.</p> <p>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'.</p> <p>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:</p> <p>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.</p> <p>Regarding self-empowerment:</p> <p>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.</p> <p>The final motivational factor for learning found in this research was career development:</p> <p>That I gain knowledge and by doing so growing further in my job and taking that knowledge with me for a potentially different function;</p> <p>You can't grow in your job without gaining new knowledge;</p> <p>If you can get promoted by participating in learning, I think that's important, right? To grow in your job.</p> <p>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.</p> <p>Table 5. Qualitative coding scheme for motivating factors.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td>Factor</td><td>Interview sources</td><td>References</td></tr></thead><tbody><tr><td>Career development</td><td char=".">7</td><td char=".">14</td></tr><tr><td>Promotion</td><td char=".">3</td><td char=".">4</td></tr><tr><td>Expected return on investment</td><td char=".">3</td><td char=".">3</td></tr><tr><td>Interest</td><td char=".">7</td><td char=".">7</td></tr><tr><td>Financial rewards</td><td char=".">8</td><td char=".">17</td></tr><tr><td>Informal learning</td><td char=".">1</td><td char=".">1</td></tr><tr><td>Work relevancy</td><td char=".">13</td><td char=".">23</td></tr><tr><td>Job retention</td><td char=".">6</td><td char=".">7</td></tr><tr><td>Knowledge acquisition</td><td char=".">13</td><td char=".">24</td></tr><tr><td>Personal development</td><td char=".">10</td><td char=".">14</td></tr><tr><td>Competence development</td><td char=".">3</td><td char=".">3</td></tr><tr><td>Self-empowerment</td><td char=".">3</td><td char=".">4</td></tr><tr><td>Social contact</td><td char=".">1</td><td char=".">1</td></tr><tr><td>Training content and execution</td><td char=".">6</td><td char=".">9</td></tr><tr><td>Transfer</td><td char=".">7</td><td char=".">11</td></tr><tr><td>Usefulness</td><td char=".">11</td><td char=".">22</td></tr><tr><td>Work–life balance</td><td char=".">5</td><td char=".">10</td></tr></tbody></table> </ephtml> </p> <hd id="AN0091735420-25">From learning intention to actual participation (RQ5)</hd> <p>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 activities because employers are less eager to offer training activities to employees in lower positions (Asplund and Salverda [<reflink idref="bib5" id="ref115">5</reflink>]; Burdett and Smith [<reflink idref="bib13" id="ref116">13</reflink>]). The results show that this is not necessarily so.</p> <p>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:</p> <p>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.</p> <p>Participants from the hospital on the other hand told a different story. What follows are some quotes made by workers of the hospital group:</p> <p>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.</p> <p>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.</p> <p>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.</p> <hd id="AN0091735420-26">Discussion and conclusion</hd> <p>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. [<reflink idref="bib32" id="ref117">32</reflink>]; Maurer et al. [<reflink idref="bib34" id="ref118">34</reflink>]) showed that the learning intention is a robust predictor for actual participation. Boeren et al. ([<reflink idref="bib11" id="ref119">11</reflink>]) 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.</p> <p>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. [<reflink idref="bib25" id="ref120">25</reflink>]). Unfortunately, self-directedness is usually not associated with low-qualified employees (Kyndt et al. [<reflink idref="bib32" id="ref121">32</reflink>]); 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 [<reflink idref="bib12" id="ref122">12</reflink>]). 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.</p> <p>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 ([<reflink idref="bib55" id="ref123">55</reflink>]) 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 [<reflink idref="bib5" id="ref124">5</reflink>]; Hazelzet, Oomens, and Keijzer [<reflink idref="bib28" id="ref125">28</reflink>]), 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 [<reflink idref="bib23" id="ref126">23</reflink>]; Salas-Velasco [<reflink idref="bib49" id="ref127">49</reflink>]; Xiao and Tsang [<reflink idref="bib65" id="ref128">65</reflink>]).</p> <p>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. ([<reflink idref="bib32" id="ref129">32</reflink>]) 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 ([<reflink idref="bib53" id="ref130">53</reflink>]) 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. ([<reflink idref="bib32" id="ref131">32</reflink>]) 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 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.</p> <p>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. [<reflink idref="bib11" id="ref132">11</reflink>]).</p> <p>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 understood 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, [<reflink idref="bib60" id="ref133">60</reflink>]). In addition, Vermeersch and Vandenbrouck ([<reflink idref="bib60" id="ref134">60</reflink>]) 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 [<reflink idref="bib53" id="ref135">53</reflink>]).</p> <p>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.</p> <p>A final limitation of this research concerns the various participating organisations 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 [<reflink idref="bib31" id="ref136">31</reflink>]). This can be supported by the research of Salas-Velasco ([<reflink idref="bib49" id="ref137">49</reflink>]) 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 typical for different kinds of sector and organisations, and how they influence the learning intention of employees.</p> <p>Finally, the results from the qualitative part of this study need to be generalised with caution, as they were derived from a limited sample.</p> <p>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.</p> <hd id="AN0091735420-27">Appendix</hd> <p></p> <hd id="AN0091735420-28">Factor analysis learning intention</hd> <p></p> <p> <ephtml> <table><tbody><tr><td><bold>Factor 1:</bold> Learning intention (54.27% explained variance)</td><td>Loadings</td></tr><tr><td>I intend to look for information about job-related courses and learning activities that I could participate in.</td><td char=".">0.816</td></tr><tr><td>I intend to participate in a work-related learning activity within the next year.</td><td char=".">0.779</td></tr><tr><td>Sometimes I think about following a job-related training within the next year.</td><td char=".">0.722</td></tr><tr><td>I intend to talk with my executive about job-related courses or trainings that I could follow.</td><td char=".">0.691</td></tr><tr><td>I Intend to talk with persons in my surroundings about job-related courses or trainings that I could follow.</td><td char=".">0.665</td></tr></tbody></table> </ephtml> </p> <p>2 Note: Extraction method: maximum likelihood.</p> <hd id="AN0091735420-29">Factor analysis independent variables</hd> <p>Factors, items, factor loadings, explained variance and reliability</p> <p> <ephtml> <table><thead valign="bottom"><tr><td /><td>Factor loading</td></tr></thead><tbody><tr><td><bold>Factor 1:</bold> Self-efficacy (12% explained variance; α = 0.81)</td></tr><tr><td>I will be able to successfully overcome many challenges.</td><td char=".">0.82</td></tr><tr><td>I will be able to achieve most of the goals that I have set for myself.</td><td char="." /></tr><tr><td>Even when things are tough, I can perform quite well.</td><td char=".">0.64</td></tr><tr><td>I am confident that I can perform effectively on many different tasks.</td><td char=".">0.55</td></tr><tr><td>When facing difficult tasks, I am certain that I will accomplish them.</td><td char=".">0.54</td></tr><tr><td>In general, I think that I can obtain outcomes that are important to me.</td><td char=".">0.57</td></tr><tr><td>I believe I can succeed in practically any challenge I take on.</td><td char=".">0.80</td></tr><tr><td>I set and honour priorities.</td><td char=".">0.47</td></tr><tr><td>I have a clear idea of what I want to accomplish during the next week.</td><td char=".">0.52</td></tr><tr><td><bold>Factor 2:</bold> Perceived organisational support (10% explained variance; α = 0.79)</td></tr><tr><td>My organisation is willing to help me if I need a special favour.</td><td char=".">0.73</td></tr><tr><td>My organisation cares about my opinion.</td><td char=".">0.72</td></tr><tr><td>My organisation strongly considers my goals and values.</td><td char=".">0.64</td></tr><tr><td>My organisation shows little concern for me (<italic>R</italic>).</td><td char=".">0.71</td></tr><tr><td>Those who do well have a fair chance for promotion here.</td><td char=".">0.53</td></tr><tr><td>People in this organisation are being promoted equally fast as in other organisations.</td><td char=".">0.56</td></tr><tr><td><bold>Factor 3:</bold> Time management (10% explained variance; α = 0.84)</td></tr><tr><td>I plan my day before I start it.</td><td char=".">0.81</td></tr><tr><td>I make a list of the things I have to do each day.</td><td char=".">0.81</td></tr><tr><td>I make a schedule of the activities I have to do on workdays.</td><td char=".">0.79</td></tr><tr><td>I spend time each day planning.</td><td char=".">0.73</td></tr><tr><td>I write a set of goals for myself for each day.</td><td char=".">0.62</td></tr><tr><td><bold>Factor 4:</bold> Self-directedness (9% explained variance; α = 0.76)</td></tr><tr><td>I find it important to think about the progression of my career.</td><td char=".">0.80</td></tr><tr><td>I find it important to get in touch with people who can be of importance to my career as much as possible.</td><td char=".">0.69</td></tr><tr><td>I keep myself informed on new possibilities to develop my career.</td><td char=".">0.73</td></tr><tr><td>I find it important to consider if my present position in the department and the organisation is the right one.</td><td char=".">0.55</td></tr><tr><td>I find it important to think about what I want to realise in my career during the following years.</td><td char=".">0.51</td></tr><tr><td><bold>Factor 5:</bold> Pay satisfaction (9% explained variance; α = 0.81)</td></tr><tr><td>I am being paid well for the work I am doing here.</td><td char=".">0.78</td></tr><tr><td>In my company the salaries are good.</td><td char=".">0.79</td></tr><tr><td>I can manage easily on my wage.</td><td char=".">0.75</td></tr><tr><td>I think my salary is fair in comparison with my colleagues.</td><td char=".">0.70</td></tr><tr><td><bold>Factor 6:</bold> Perceived promotion opportunities (5% explained variance; α = 0.56)</td></tr><tr><td>Regular promotion is a rule within this organisation.</td><td char=".">0.64</td></tr><tr><td>Promotion here is based on ability.</td><td char=".">0.62</td></tr><tr><td>In my current job, there a litte promotional opportunities (<italic>R</italic>).</td><td char=".">0.48</td></tr></tbody></table> </ephtml> </p> <p>3 Note: Extraction method: maximum likelihood, cut-off factor loadings = 0.40; rotation method: Varimax with Kaiser normalisation.</p> <ref id="AN0091735420-30"> <title> References </title> <blist> <bibl id="bib1" idref="ref25" type="bt">1</bibl> <bibtext> Ajzen, I. 1991. 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  Label: Title
  Group: Ti
  Data: What Motivates Low-Qualified Employees to Participate in Training and Development? A Mixed-Method Study on their Learning Intentions
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  Data: English
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  Data: <searchLink fieldCode="AR" term="%22Kyndt%2C+Eva%22">Kyndt, Eva</searchLink><br /><searchLink fieldCode="AR" term="%22Govaerts%2C+Natalie%22">Govaerts, Natalie</searchLink><br /><searchLink fieldCode="AR" term="%22Claes%2C+Trees%22">Claes, Trees</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Studies+in+Continuing+Education%22"><i>Studies in Continuing Education</i></searchLink>. 2013 35(3):315-336.
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  Label: Availability
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  Data: Routledge. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 22
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2013
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Audience
  Label: Education Level
  Group: Audnce
  Data: <searchLink fieldCode="EL" term="%22Adult+Education%22">Adult Education</searchLink>
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Adult+Education%22">Adult Education</searchLink><br /><searchLink fieldCode="DE" term="%22Motivation%22">Motivation</searchLink><br /><searchLink fieldCode="DE" term="%22Mixed+Methods+Research%22">Mixed Methods Research</searchLink><br /><searchLink fieldCode="DE" term="%22Labor+Market%22">Labor Market</searchLink><br /><searchLink fieldCode="DE" term="%22Surveys%22">Surveys</searchLink><br /><searchLink fieldCode="DE" term="%22Semi+Structured+Interviews%22">Semi Structured Interviews</searchLink><br /><searchLink fieldCode="DE" term="%22Intentional+Learning%22">Intentional Learning</searchLink><br /><searchLink fieldCode="DE" term="%22Behavior+Theories%22">Behavior Theories</searchLink><br /><searchLink fieldCode="DE" term="%22Employee+Attitudes%22">Employee Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Time+Management%22">Time Management</searchLink><br /><searchLink fieldCode="DE" term="%22Unskilled+Workers%22">Unskilled Workers</searchLink><br /><searchLink fieldCode="DE" term="%22Gender+Differences%22">Gender Differences</searchLink><br /><searchLink fieldCode="DE" term="%22Age+Differences%22">Age Differences</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Attitudes%22">Educational Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Characteristics%22">Student Characteristics</searchLink><br /><searchLink fieldCode="DE" term="%22Measures+%28Individuals%29%22">Measures (Individuals)</searchLink><br /><searchLink fieldCode="DE" term="%22Predictor+Variables%22">Predictor Variables</searchLink><br /><searchLink fieldCode="DE" term="%22Factor+Analysis%22">Factor Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+Analysis%22">Statistical Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Reliability%22">Reliability</searchLink><br /><searchLink fieldCode="DE" term="%22Organizational+Climate%22">Organizational Climate</searchLink><br /><searchLink fieldCode="DE" term="%22Regression+%28Statistics%29%22">Regression (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Influences%22">Influences</searchLink><br /><searchLink fieldCode="DE" term="%22Questionnaires%22">Questionnaires</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1080/0158037X.2013.764282
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0158-037X
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: 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.
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  Data: As Provided
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  Data: 65
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2014
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  Label: Accession Number
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  Data: EJ1023186
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        Value: 10.1080/0158037X.2013.764282
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      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 22
        StartPage: 315
    Subjects:
      – SubjectFull: Adult Education
        Type: general
      – SubjectFull: Motivation
        Type: general
      – SubjectFull: Mixed Methods Research
        Type: general
      – SubjectFull: Labor Market
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      – SubjectFull: Surveys
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      – SubjectFull: Semi Structured Interviews
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      – SubjectFull: Intentional Learning
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      – SubjectFull: Behavior Theories
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      – SubjectFull: Employee Attitudes
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      – SubjectFull: Time Management
        Type: general
      – SubjectFull: Unskilled Workers
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      – SubjectFull: Gender Differences
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      – SubjectFull: Age Differences
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      – SubjectFull: Educational Attitudes
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      – SubjectFull: Student Characteristics
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      – SubjectFull: Measures (Individuals)
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      – SubjectFull: Predictor Variables
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      – TitleFull: What Motivates Low-Qualified Employees to Participate in Training and Development? A Mixed-Method Study on their Learning Intentions
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