Towards a tool mapping Organizational Readiness for Self-Directed Learning

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Towards a tool mapping Organizational Readiness for Self-Directed Learning

MARLOES H. GIESSELINK Master Thesis

Educational Science & Technology Human Resource Development

SUPERVISION DR. M.D. ENDEDIJK T. HIRSCHLER MSc University of Twente May 2017

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General information

Researcher: Marloes H. Giesselink

E-mail: m.h.giesselink@student.utwente.nl

Supervisor 1: Dr. M. D. Endedijk

E-mail: m.d.endedijk@utwente.nl Supervisor 2: T. Hirschler MSc

E-mail: t.hirschler@utwente.nl

External organization: UP learning

Supervision: Jeroen Oude Egbrink

E-mail: jeroenoudeegbrink@uplearning.nl

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Abstract

Since there is a growing interest in applying SDL at the workplace, organizations are asking how they could successfully stimulate SDL behavior of their employees. The goal of this study was to design a tool which helps organizations to develop their organizational readiness for Self-Directed Learning (SDL). The tool provides insights in important organizational factors, creates awareness about the current level of performance, and provides handles to get started. In order to answer the overall research question, an educational design based research with a qualitative basis was conducted. During three iterative phases, different experts and professionals from different organizations were involved to contribute in exploration of factors, development and evaluation of the tool. In order to ensure quality in terms of this research process, all steps were evaluated and verified by means of an audit procedure. After repetition of these iterative phases, a final tool was developed which is tested into practice of three different teams. It appeared that respondents consider the developed tool as helpful for its purpose. It does provide a starting point, a baseline on how organizations currently perform and provides insights in possible areas of attention.

However, if organizations want to become more ready for SDL, there is more needed than only the execution of the tool. Further research could focus on this area by developing concrete improvements for the different factors used in the tool, in order to improve effects.

Keywords: Self-Directed Learning, Organizational Readiness, tool.

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Acknowledgement (Dutch)

Tijdens mijn afstuderen, had ik een Bijbel. Nou nou ja, eigenlijk was het gewoon het meest goedkope notitieboekje van de HEMA. Je weet wel, eentje met van die nette blauwe lijntjes. Aan het begin van mijn studie schreef ik er een kort verhaaltje in op. Ik vond het laatst, tussen alle koffievlekken, bloed, zweet en tranen terug:

Zondag 21 juni 2015

Vandaag is de start van de zomer en voor mij ook de start van een nieuw hoofdstuk. Een hoofdstuk waarvan ik niet wist dat ik hem ooit starten zou. Na een jaar fulltime te hebben gewerkt, ga ik terug de schoolbanken in. Vanaf september 2015 zal ik beginnen aan de Universiteit Twente. En wel met de masteropleiding Educational Science and Technology. Je kunt het gerust een uitdaging van groots formaat noemen. Ik ben nog niet eens begonnen, maar het voelt nu al bevrijdend.

Nu, nog geen twee jaar later, is het notitieboekje bijna vol en mijn Master Thesis klaar. In het boekje staan allerlei krabbels en aantekeningen. Het is eigenlijk de externe back up van mijn hersenspinsels tijdens het afstuderen.

En hoewel het heel cliché is als ik zeg dat de tijd voorbijgevlogen is, heb ik mij in die gevoelsmatig korte tijd zo ontzettend snel ontwikkeld. Als persoon en als aanstormend professional. Ik had dit hele avontuur voor geen goud willen missen. Want dat was het. En gemakkelijk was het heus niet altijd. Ik zag soms door de self-direction het leren niet meer. Ook heb ik vaak gedacht dat het afstuderen het moeilijkste zou zijn wat ooit op mijn pad zou komen. Maar mede dankzij de mensen om mij heen en zij die along the way op mijn pad kwamen, kan dit avontuur de boeken in als zeer geslaagd. Daarbij zijn natuurlijk een paar mensen die ik in het bijzonder wil bedanken. En bij wie kan ik anders beginnen dan bij Maaike. Als afstudeerbegeleider heeft ze mijn afstudeeronderzoek naar een hoger level getild. Maaike, je was kritisch op de juiste momenten en gaf altijd precies de goede input om weer zelfstandig door te kunnen. Enorm bedankt voor je inzet en enthousiasme. Daarnaast wil ik ook Robert bedanken, mijn studiemaatje vanaf het eerste uur.

Jouw gedrevenheid werkte aanstekelijk. Ik vond het dan ook erg leuk toen bleek dat we allebei in hetzelfde intervisiegroepje zaten voor onze thesis. Samen kunnen sparren, werkte voor mij perfect.

Natuurlijk wil ik ook de mensen van UP learning bedanken en in het bijzonder Jeroen, Leonie, Sylvia en Ster, van de werkgroep SDL. In mijn master heb ik mijn ziel en zaligheid gestoken, maar jullie waren absoluut de spreekwoordelijke kers op de taart. Vanuit UP had ik mij geen betere begeleiding en support kunnen wensen. Altijd werd er tijd gemaakt, met ongekend veel energie en enthousiasme. Jullie zijn echt een clUP met elkaar om trots op te zijn. Ook alle respondenten die op enige wijze bij hebben gedragen aan mijn master thesis, wil ik langs deze weg toespreken.

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Bedankt voor het delen van jullie kennis, ervaringen en inzichten. Ja, en mijn familie en vrienden, waar was ik zonder hen geweest? Ik kon altijd bij jullie terecht om even stoom af te blazen, om te sparren of om te discussiëren. En last but not least, Stefan. Bedankt dat je mij altijd hebt gesteund.

Ik ben je heel dankbaar dat je me deze kans hebt gegund.

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1. Introduction

Due to the high pace in which new technologies develop, increased global competition, and growing emphasis on cost-efficiency, today’s labor market is changing fast (Ellinger, 2004). As a result of this, organizations are increasingly challenged to remain distinctive and adopt more flexible approaches to ensure a productive workforce and organizational effectiveness (Conn, 2000; Ellinger, 2004). The ability of an organization to create an environment which promotes learning and development, highly enhances individual and organizational performance (Ellinger, 2004; Watkins & Marsick, 1993). As a result of this, organizations nowadays explore and implement different strategies and initiatives to ensure their employees remain capable of coping with the challenges and inevitable change they encounter (Rana, Ardichvili & Polesselo, 2015). The implementation of Self-Directed Learning (SDL) at the workplace have been emerged as an effective organizational response to cope with these challenges (Park, 2008).

Several studies into SDL at the workplace recognized that a supportive work environment is an important facilitator to succeed with SDL at the workplace (e.g. Confessore & Kops, 1998;

Park, 2008; Rana, Ardichvili & Polesselo, 2015). These studies were descriptive, focusing on organizational conditions enhancing SDL within the workplace, such as a supportive management style, tolerance of errors, and an environment of trust. In line with this, Nemec (2011) found that characteristics to become self-directed learner dot not initially have to be present, but benefit from a structured environment in which SDL is stimulated. This suggests that the organizational environment can influence employees’ likeliness to self-direct their learning (Boyer, Edmonson, Artis & Fleming, 2014). However, the tools to map this organizational environment are lacking.

Research in the past mainly focused on the antecedents of individual learner behavioral intentions towards SDL and the development of tools to measure the readiness of individuals to engage in SDL (Ellinger, 2014). Readiness regarding to individuals refers to an internal state of psychological preparedness which is reliant on the notion of SDL as a personal attribute of learners (Nemec, 2011). Learners who are considered to be ready to engage in SDL show certain competencies, such as attitudes, knowledge, and skills (Nemec, 2011). In contrast to the missing tools in the area of assessing organizational factors for SDL, there are several tools developed which assess the individual readiness for SDL. Examples are the Self-Directed Learning Readiness Scale (SDLRS) of Guglielmino (1977), and the Oddi Continuing Learning Inventory (OCLI) of Bartlett and Kotrlik (1999).

The aim of this design based study is to develop a tool focusing on mapping the organizational environment and important influencing variables for SDL at the workplace. Because Park (2008) already stated the importance to recognize workplace factors and conditions which

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support SDL, in order to maximize and optimize individual readiness for SDL. The tool should help organizations to get insights in important organizational factors, create awareness of their current level of performance, and provide handles about where to focus on when developing the Organizational Readiness for SDL within a particular organization. Organizational Readiness is a new concept, which is coined by this study. The term refers to an organizational preparedness in which important organizational factors are present, from which is known that they support, facilitate and/or stimulate its employees to self-direct their learning. This term will be further elaborated during this study, and forms the basis of this research.

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2. Theoretical Framework

In the context of Human Resource Development (HRD), there are two parallel levels of SDL:

individual level, and organizational level (Daciulyte & Pinchuk, 2010). At individual level, SDL is associated with individual readiness, learner’s independence, and a personal approach to learning and its goals (Ellinger, 2004). At organizational level, SDL is mostly associated with factors such as organizational culture and leadership (Daciulyte & Pinchuk, 2010). An employee and its individual characteristics remain a key element of the success or failure of organizational performance at large (Wambugu, 2014). Each organization has a particular environment. A culture in which norms and procedures are developed and determine the atmosphere feeling (Wambugu, 2014).

Organizational cultures are important predictors of how organizations cop up with dynamic changes and meet the varying demand of employee expectations and satisfaction, which in turn influence the employee’s performance (Wambugu, 2014). It is believed that creating Organizational Readiness for SDL has a positive influence. Therefore, is study assumes that SDL in the workplace is a process of individual learners which can be positively influences by environmental conditions.

For the scope of this research does this mean that there will be a particular focus on organizational factors and conditions which support SDL. However, in order to develop the tool, mapping Organizational Readiness for SDL, it is important to get an overview of all influencing variables. Park (2008) already stressed the complex interactions between SDL on individual level and organizational level. Therefore, influencing individual factors of SDL will also be part of the literature review below. However, firstly it starts with a clear definition of SDL.

2.1 Self-Directed Learning

Self-Directed Learning (SDL) is an important and commonly used form of learning at the workplace, since it has to be shown that it is a highly effective method to engage and train adults (Ellinger, 2004). Malcolm Knowles (1975) provided a definition of SDL, which is still commonly used.

It will also be the basis of this research:

“Self-directed learning is a process in which individuals take the initiative, with or without the help of others, in diagnosing their learning needs, formulating learning goals, identifying human and material resources for learning choosing and implementing appropriate learning strategies and evaluating learning outcomes”.

(Knowles, 1975, p. 18)

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According to literature, SDL can be divided in three different perspectives (1) SDL as a process, focusing on learner autonomy in the learning process, (2) SDL as psychological aspect, focusing on the capabilities of a learner regulating the process, and (3) SDL in context, focusing on environmental conditions (Ellinger, 2004; Merriam, 2001; Park, 2008; Song & Hill, 2007). Although the latter mentioned perspective is of particular interest for this study, the other two will also be shortly discussed.

The first perspective is SDL as a process. SDL is often viewed as a method of learning or teaching (Ellinger, 2004). This is in line with the definition of Knowles (1975) that consists of six steps in which the learner has the lead: (1) climate setting, (2) diagnosing learning needs, (3) formulating learning goals, (4) identifying human and material resources for learning, (5) choosing and implementing appropriate learning strategies, and (6) evaluating the learning outcomes. From this perspective, SDL behavior is characterized by learners deciding for themselves what they want to learn and how they want to learn it by following the six steps previously described (Tobin, 2000).

The perspective of psychological aspects mainly refers to an attribute of personality (Brookfield, 1986; Cazan & Schiopca, 2014; Ellinger, 2004). From this perspective, an individual has particular characteristics which result in SDL behavior. Brookfield (1986) describes the self-directed learner as someone who pursues “an understanding and awareness of a range of alterative possibilities for learning and living” (p.58-59). Examples of personal attributes that stimulate SDL are a proactive personality and high levels of self-efficacy (Cazan & Schiopca, 2014; Ellinger, 2004;

Park, 2008).

The last, and reasonably new, angle of incidence in SDL is context. This approach received less attention from researchers (Song & Hill, 2007). Although, some researchers did recognize the importance of context for SDL (i.e. Candy, 1991). Research on the context of SDL focuses on environmental factors and how those factors impact the level of SDL behavior (Song & Hill, 2007).

They note that the context has an influence on employees, for example design elements of the learning landscape and the use of resources (Song & Hill, 2007). Examples of contextual factors that stimulate SDL behavior are continuous improvement, communication, and innovation (Baskett, 1993; Straka 2000).

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2.2 Organizational Readiness for SDL

Spear and Mocker (1984) were about the first that emphasized on the environmental conditions related to SDL. They conducted a qualitative analysis of adults’ descriptions of their learning activities, in order to learn more about the factors that organize non-formal learning.

Those factors lie beyond the consciousness of the learner, and suggested that organizing circumstances, rather than preplanning by the individual is the direct force behind self-directed learning (Spear & Mocker, 1984).

With SDL at the workplace, employees learn in practice, from their own learning experiences, so that they have the ability to apply new knowledge immediately into daily practices at the workplace (McNamara, 1999). Besides, it is thought that applying SDL is more effective in the development of employees, because they can assume responsibility towards their own learning and development and they can accommodate their own learning styles and preferences, which results in higher employee effectiveness (Conn, 2000; McNamara, 2011). Moreover, employees have an important role and influence on organizational effectiveness (Dobre, 2013). Employees who self-direct their learning demonstrate an increased confidence and problem solving capabilities (Durr, 1992), and an enhance performance in their jobs (Artis & Harris, 2007). They also adapt changes in their work environment better (Guglielmino, 1977), remain resilient in the face of challenges and obstacles (Zsiga, 2008), and show stronger emotional commitment toward the organization (Cho & Kwon, 2005).

Researchers offered interesting insights on the connection between SDL and the learning organization (Cho, 2002; Confessore & Kops, 1998; Ellinger, 2004). An organization which provides an environment that stimulates SDL, has many similarities with a learning organization (Confessore

& Kops, 1998). Additionally they found evidence that the “characteristics used to describe the learning organization are necessary ingredients for SDL to flourish” (Confessore & Kops 1998, p.

366). The similar variables described for both learning organizations and ingredients for SDL are:

(1) tolerance of errors, support of experimentation and risk taking, and an emphasis on creativity and innovation; (2) the use of a participative leadership style, and delegation of responsibilities to other organizational members, (3) support for learning initiatives which are linked to the organizations’ goals and values; (4) encouragement of open communication, transparent information systems, that provide for collaboration, teamwork, and interaction; (5) use of both internal and external learning resources; and, (6) providing chances for personal learning and development.

Organizational Readiness for SDL therefore, shows also many similarities with the ingredients necessary for being a learning organization. However, where the learning organization is about facilitating learning of its employees. An Organizational Readiness for SDL refers to a

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culture which facilitates learning of its employees in powerful learning environment that inspires, facilitates, and empowers particularly the self-directed learning of its employees in diagnosing learning needs, determine learning goals, choosing learning strategies, and evaluate the learning outcomes. The given definition of Organizational Readiness for SDL is in line with the definition of Sun (2003, 160) of an optimal environment: “An environment can been thought of as a climate, culture or a powerful learning environment that inspires, facilitates, and empowers the learning of its members so as to enhance its capacity for change, adaptability, improvement, and competition”. In order to get a clear overview of the most important organizational variables according to literature, the variables are divided into two distinctive perspectives: (1) Policy and culture, containing the business culture and the learning landscape variables within an organization, such as collaboration and innovation, and (2) work characteristics, containing data from organizations such as task variety and developmental opportunities. Additionally, individual factors that contribute to Organizational Readiness for SDL will be discussed in section 2.3, in order to provide a clear overview of influencing factors Organizational Readiness for HRD implications.

2.2.1 Policy and culture

In 1993, Baskett conducted an empirical study that explored organizational conditions that facilitate workplace learning. The study involved 35 resource development consultants and line staff from 22 organizations who participated in a participatory research workshop with different sessions for determining organizational enhancers of self-directed learning. The ten main enhancers of SDL at the workplace for the business culture appeared to be: (1) embracing a continuous improvement approach, (2) high individual involvement, (3) leadership which sets an example, (4) effective communications in the organization, and (5) teamwork.

More recent, extensive literature reviews largely supported the findings of Baskett. They stressed the importance of build and communicate shared vision and goals to employees at all levels, whereby employees get the opportunity to participate in and contribute to this process (Confessore & Kops, 1998; Rana, et al., 2016). Moreover, it is described as a fundamental characteristic of successful organizations, because it “provides focus and energy for learning”

(Senge, 2006, p. 192). Finally, it also contributes to a sense of commitment to the organization and higher employee involvement (Rana et al., 2016). Shared vision and goals could be built by create an open space for sharing feedback, reflection and mutual respect (Tsasis, Evans, Rush & Diamond, 2013).

Subsequently, policy of fostering collaboration, teamwork, and interaction is also stressed as an important variable (Confessore & Kops, 1998; Rana et al., 2016; Tsasis, et al., 2013).

Collaborative learning emphasizes on natural learning that occurs as an effect of community in

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which learners work in unstructured teams and create their own learning situation (Johnson, Johnson & Smith, 1998). Interaction refers to the relationships and communication between learners, as they exchange knowledge and experiences (Tsasis, et al., 2013). Collaboration, teamwork, and interaction support a means for renewed thinking and innovation (Tsasis, et al., 2013). Finally, deeper levels of interaction enables individuals to co-produce values, roles and relationships, which also contributes to a shared vision and goals (Tsasis et al., 2013) and also individual growth can best be nurtured by collaborative and cooperative learning environments (Elias & Merriam, 2005).

Management style is the third important condition according to literature (Ellinger, 2004;

Foucher, 1995; McNamara, 1999; Rana et al., 2016; Tobin, 2000). Policy should provide for supportive supervisors who encourage employees to be self-directed in their learning (Rana et al., 2016). In addition, Ellinger et al. (2002) identified several empowering behaviors of supervisors, including asking through-provoking, questions to encourage employees to come up with own solutions, transferring ownership of learning to employees, and serving as a valuable resource to employees. This is in line with findings from the survey study of Straka (2000) and the empirical study of Ellinger, Ellinger, Yang, and Howston (2002). Leadership should set an example for employees (Straka, 2000) and Ellinger et al. (2002) found support for a positive relationship between a supportive management in which employees are empowered for SDL. In other words, supervisors have a great influence on stimulating participatory work practices and in empowering employees (Rana et al., 2016). By creating partnership with employees, supervisors are able to supervise them in the process of SDL by negotiating a learning contract with goals, strategies, and evaluation criteria (McNamara, 1999). Finally, supervisors have a great influence on supporting risk taking, and innovation linked to the organization (Baskett, 1993; Rana et al., 2016). Those mentioned factors are also mentioned as important organizational SDL enhancers by the empirical study of Baskett (1993).

Finally, both supervisors and policy should support risk taking, innovation linked to the organization, learning and experimenting, and tolerate errors in order to stimulate individual and continuous learning (Rana et al., 2016; Tobin, 2000; Confessore & Kops, 1998; Baskett, 1993). Risk taking might be prone to potential mistakes, but also create valuable learning experiences (Watkins

& Marsick, 1993). It stimulates employees to be creative and think outside the fixed lines of an organization, which might result in innovative ideas (Amabile, 1988). Moreover, the stimulation of employees’ creativity, stimulating learning and experimenting, and the tolerance of errors, stimulation of creativity will lead to important another important precondition for SDL, an environment of trust (Confessore & Kops, 1998). Therefore, the preconditions of space for learning and personal development and an environment of trust are indispensable since it underlies the

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freedom and freedom of movement that is needed to experiment, make mistakes, evaluate, and develop (Confessore & Kops, 1998; Rana et al., 2016).

2.2.2 Job characteristics

Next to organizational characteristics, job characteristics also influence Organizational Readiness for SDL. Guglielmino et al. (1987) conducted an empirical study to determine the relationship of self-directed learning readiness and performance in an occupational setting. It was concluded that high levels of creativity in the job and having different tasks will lead to more SDL at the workplace. Hackman and Oldham (1980) advocated that if certain characteristics are present in the job, employees will be more internally motivated to perform well, and will be more likely to desire for personal growth and increased competence. And motivation plays a significant role in SDL on individual level (Ellinger, 2004; Park, 2008). More recent, Raemdonck (2006) and Raemdonck, Gijbels and Van Groen (2014) largely agree upon the findings of the earlier mentioned researches. They identified that employees who perceive more task variety, and growth potential will show more SDL behavior. In addition to this, Raemdonck (2006) mentioned the influence of autonomy and noted that employees who enjoy more job autonomy are more likely to show SDL behavior. Hereby, job autonomy refers to the “degree to which the job provides substantial freedom and judgement of the employee in scheduling work and determining the procedures to be used” (Raemdonck, 2006, p. 134). The importance of job autonomy was also stressed by Foucher (1995). He revealed through interviews with HR practitioners, that a supportive environment in which employees enjoy autonomy is essential for stimulating SDL in organizations.

2.3 Individual factors contributing to Organizational Readiness for SDL

This section will elaborate more upon individual factors that contribute to Organizational Readiness for SDL. In order to provide a clear overview, the individual variables are divided into three distinctive perspectives: (1) Demographics and human capital, (2) Personality, and (3) Psychological factors.

In the past, many researchers have tried to give an overview of influencing variables on SDL (e.g. Cazan & Schiopca, 2014; Ellinger, 2004; Guglielmino, 1977; Park, 2008) However, the scope and variables discussed often differ (Ellinger, 2004). The more influential characteristics are present, the more likely that employees learn in a self-directed way (Raemdonck, 2006).

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2.3.1 Demographics and human capital

Demographic variables affect many behavioral patterns, including the self-directedness of employees in the process of learning and development (Raemdonck 2006). Therefore, demographic variables need to be considered when examining the predictors for SDL (Raemdonck, 2006). Moreover, demographic variables also give an overview of the sample used for the study.

However, many variables should be taken into account, even though it is impossible to do so (Raemdonck, 2006). Perhaps this explains why several studies do not agree on human capital variables. A review of literature reveals that typical examples of demographic variables used in SDL studies are age, gender, occupation, and educational degree (Guglielmino, Klatt & Guglielmino, 1995).

Stockdale (2003) conducted an extensive literature review towards on studies which examined the relationship between age and SDL. Some researchers found a positive relationship between increased age and SDL readiness (i.e. Guglielmino, Guglielmino, & Long, 1987; Long &

Morris, 1996) but in 11 studies there was not significant association found. This contradiction makes it hard to decide for this research if this variable should be used or not.

The same holds for educational level. The importance of educational level as a variable is stressed in several studies (i.e. Cazan & Schiopca, 2014; Park, 2008; Guglielmino, 1977). According to those studies, a higher level of education could be related to a higher level of SDL behavior. In contrast, Durr, Guglielmino and Guglielmino (1996) found no significant differences in educational level and SDL during their study among 600 employees. In addition, no gender differences were found using Guglielmino’s self-directed learning readiness scale.

2.3.2 Personality

Another influencer of SDL behavior is personality. Kirwan, Lounsbur & Gibson (2014) conducted a study and looked at individual SDL specifically as a personality trait. They pointed out that SDL of individuals is positively and significantly related to four out of five personality traits of the Big Five: Agreeableness, Conscientiousness, Extraversion, and Openness to experience, and that both Big Five and the narrow traits accounts for 52% of the variance in SDL of individuals. The findings of the Big Five personality traits are in line with the findings of Cazan & Schiopca (2014) who analyzed the relationship personality traits, SDL, and academic achievement.

Another personality trait that significantly relates to SDL is proactive personality (Seiber, Kraimer & Crant, 2001; Raemdonck, 2006). With proactive personality is meant that an individual identifies opportunities, shows initiative, and takes action until meaningful changes occur (Bateman & Crant, 1993). In 2006, a survey study was conducted to investigate the links between the Big Five personality traits, proactive personality, and the motivation to learn (Major, Turner,

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Fletcher, 2006). Results demonstrated that proactive personality, openness, extraversion, and consciousness predicted employees’ motivation to learn. The latter is an important individual factor for showing SDL behavior (Bodkyn & Stevens, 2015).

2.3.3 Psychological factors

The last distinct perspective is closely related to personality. Psychological variables that received considerable attention in literature are motivation, internal locus of control, and self- efficacy. (Candy, 1991; Park, 2008; Brookfield, 2009; Boyer et al., 2014). In addition, Raemdonck (2009) pointed out that the pursuit of knowledge work (the extent to which the employee needs stimulating and challenging work), has influence on SDL behavior, as well as career satisfaction (satisfaction about career in the past), and mobility aspiration (how an employee wants a career to develop in the future).

An internal locus of control (ILOC) refers to the extent to which individuals believe they have actual control over events that influence them (Boyer, et al., 2014). Employees with higher levels of ILOC show a greater commitment towards their organization, have higher levels of job satisfaction, and believe that their efforts affect goal attainment (Boyer, et al., 2014). If employees take control for their own learning, they are more likely to engage in SDL (Boyer, et al., 2014).

With self-efficacy is meant that individuals believe in the ability to be successful in different situations (Boyer et al., 2014). Self-efficacy plays an important role in approaching challenges and goal setting, which suggests that employees with higher levels of self-efficacy tend to approach a task with the faith they are capable enough to fulfill it (Bandura, 1977). Challenging work in organizations require environments higher levels of self-efficacy. For example, Posner (1989) conducted a study among 575 employees across various industries and found that employees who scored lower levels of self-efficacy, were less likely to engage in SDL.

Furthermore, motivation has a significant direct effect on proactive personality and the willingness of individuals to learn and develop themselves (Major, Turner, & Fletcher, 2006). In addition, highly motivated individuals are more likely to assume responsibility for their learning and are more often internally motivated to set and achieve goals (Merriam, 2001; Park, 2008).

Motivation is described by Boyer et al. (2014) as the force that drives employees to set goals and pursue them. It should be stronger than all other factors of willingness due to the fact that motivation can subordinate all other influencing factors (Artis & Harris, 2007).

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2.5 Present study

As already stressed in the introduction, this research will be a design-based research. The figure below shows all influencing variables for SDL behavior discussed in paragraph 2.2 and 2.3.

Figure 1. Overview of variables influencing SDL behavior according to literature.

This is a relatively new method in educational sciences (Anderson & Shattuk 2012). Design based researches are characterized by multiple iterations of design, development, and evaluation over an extensive period of time (Pool & Laubscher, 2016). This kind of methodology fits the research goals of this study, since the aim is to develop a tool. The tool should be able to map the Organizational Readiness for SDL in an organization, according to different levels of performance.

There are several benefits to mention for describing different levels of performance, such as an increased consistency of scoring, the possibility to judge complex competencies in a valid way, and to promote learning (Jonsson & Svingby, 2007).

In order to develop the tool, this study will exist of three iterative phases. According to McKenney & Reeves (2012) a design based research exists of three iterative phases: (1) analysis and exploration, (2) design and construction, and (3) evaluation and reflection. These iterative phases are also the basis of this study. During the analysis and exploration phase will be which variables from the theoretical framework are suitable to include in the tool and how they could be distinguished in different levels of performance. Subsequently, during the second iterative phase there is room for the design and development of the tool, in which different experts will be involved in order to collect valuable information about design requirements. During the third phase, the developed concept tool will be evaluated an reflected on, in order to develop its final version.

During all three iterative phases will be space for implementation, spread, and evaluations. A more

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elaborated explanation about the iterative phases during this study can be found in section 4.1 about the research design.

During this study the terms individual readiness for SDL, organizational readiness for SDL, and a SDL environment will be used. To avoid confusion about these terms, here will be shortly explained what is meant with each term and how they relate to each other:

Individual readiness for SDL tells something about the complex attitudes, skills, and characteristics that comprise an individual’s current level of readiness to manage his or her own learning (Guglielmino, 1977).

Organizational readiness for SDL is about the presence of organizational factors which stimulate and facilitate the individual readiness for SDL.

SDL environment is an optimal milieu in which both the individual readiness for SDL and organizational readiness for SDL are both present. A SDL environment is therefore an umbrella term for both individual and organizational readiness for SDL.

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3. Research questions

During this design based research, several steps will be conducted in order to design a tool which helps organizations to get insights in their Organizational Readiness for SDL. This leads to the following research questions:

How could a tool be developed that provides a clear overview of the readiness of organizations to stimulate and facilitate its employees in SDL?

a) Which organizational factors should be included in a tool that maps the Organizational Readiness for SDL within an organization?

b) How can the organizational factors from research question a) be distinguished into different levels of performance?

c) What are the design requirements for mapping Organizational Readiness for SDL according to SDL experts and the HRD professionals?

d) To what extent do respondents from organizations consider the developed tool as helpful, for mapping their organizational readiness and as a usable to start with building a SDL environment?

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4. Method

In this section, the method of the study will be discussed. The aim of this chapter is to explicate the research design, instrumentation, procedure and the analysis of the gathered data.

4.1 Research design

In order to answer the overall research question, an educational design based research with a qualitative basis will be conducted. An educational design based research is a genre of research in which the iterative development of solutions to practical and complex situations provides the setting for scientific inquiry (McKenney & Reeves, 2012). In the scope of this research, a tool will be developed as a handle for the complexity of Organizational Readiness for SDL behavior. At the same time, educational design research tends to discover new knowledge that can help others with similar problems (McKenney & Reeves, 2012). During this research, there will be a particular interest for organizational factors that stimulate SDL behavior of employees and how those factors could be mapped and related to the Organizational Readiness for SDL. In order to reach this goal, this study is divided into three iterative phases: (1) analysis & exploration, (2) design & construction, and (3) evaluation & reflection. Each phase represent new steps in the research process and delivers a new concept version of the tool. The chronology of each iterative phase is summarized in figure 3 below, as well as the research questions that will be answered during a particular phase, respondents that were approached, and the intended outcomes.

Phase 1 – Analysis & Exploration

Phase 1a – Analysis and exploration of content

Step RQ Respondents Instruments Outcomes

A, B SDL experts Future users

Explorative expert interviews

Tally chart

Organizational factors that are suitable to get an overview of the Organizational Readiness for SDL.

Phase 1b – Analysis and exploration of design requirements

C SDL experts Explorative expert interviews

Distinction and description of different performance levels of an SDL environment within an organization that will be used.

Generating ideas of how to apply those levels in a tool.

General design requirements for a tool.

Output: Concept tool I 1

2

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Phase 2 – Design & Construction

Phase 2a – Construction for implementation

C HRD

professionals Semi-structured interviews

Practical requirements for

organizations in terms of outcomes and deliverables.

Adapting new ideas for the tool and its performance levels.

Phase 2b – Content design

D

HRD

professionals and future users

Semi-structured interviews

Evaluation of the first concept tool from phase 1 and exploration of improvements for the development of the second concept tool.

Output: Concept tool II

Phase 3 – Evaluation & Reflection

Phase 3a – Pilot and responsive evaluations

D Future users Survey

Open interviews

Evaluation of the second concept tool from phase 2 and exploration of improvements for implementation of the final tool.

Output: Final tool

Figure 3. Chronology of the research design.

During this study, the steps of a design research were followed as described by McKenney (2003). The first step in this process is an analysis of literature and concept validation (McKenney

& Reeves, 2012). Therefore, prior to the steps as described in figure 3, a literature review was conducted, which resulted in the theoretical framework of this study. It provided a starting point for the exploration phase. Subsequently, the model of McKenney and Reeves (2012) was also used as the basis of this research. All phases as described in the three different phases can be plotted in the following model:

3

4

5

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Figure 4. Model for design research in education according to McKenney and Reeves (2012) applied to this study

4.1.1 Phase 1 – Analysis & exploration

The aim of the first phase was to make a distinction of the most important variables required for mapping organizational readiness with a tool, and to distinguish how to describe distinctive performance levels. In order to reach these goals, two different steps were conducted, divided in phase 1a, which was about exploration of content, and phase 1b, which was about exploration of design requirements.

1a. Analysis and exploration of content

In order to answer research questions A, SDL experts were approached for explorative expert interviews. The aim of these interviews was twofold. On the one hand, it was an exploration of important variables, on the other hand it was explored how to describe the different performance levels in Organizational Readiness for SDL. The first goal was reached by presenting a list with variables derived from literature to all SDL experts. Subsequently, the SDL experts could support which variables they considered as most and least important to map the SDL readiness of organizations. At the end, they all made a list with the five most and the five least important variables. Secondly, the same variables as discussed with the SDL experts were presented to future users. All variables were explained on an additional paper, so that the meaning of each variable was clear. The future users could state in a tally chart if each particular factor contributes to their own level of SDL behavior by choosing for “Important variable”, “Neutral variable”, or “Unimportant variable”.

After completion of exploration of important variables, the interviews focused on distinguish and describe different performance levels of Organizational Readiness for SDL. The SDL experts got the assignment to think about 3-4 performance levels for the variables they earlier

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considered as most important. Hereby, ideas were generated about how to apply the different performance levels in a tool. The goal was to trigger a discussion and ask the experts for practical requirements for developing the scan.

1b. Analysis and exploration of design requirements

Prior to the design phase, the design requirements of the tool were discussed as a second subject during the explorative expert interviews. The SDL experts engaged in this phase of the process. The aim was to collect as much information as possible about how to design a tool for this subject. The experts were asked to about practical requirements of the tool and possible tips and pitfalls in designing such an instrument.

4.1.2 Phase 2 – Design and construction of the tool

The aim of the second phase was again to distinguish practical requirements for mapping organizational readiness, as described under phase 1b. However, this time the knowledge and experience of HRD professionals was used. Subsequently, theory and practice were brought together by improving the concepts derived from phase 1. Consequently, the second phase also consisted of two different steps:

2a. Construction for implementation

To make sure that the tool meets the needs of future users from practice, HRD professionals were approached to participate in semi-structured interviews. They were asked about their preferences when using a tool for mapping Organizational Readiness for SDL. Examples of subjects during this evaluation session were the amount of time the test might take, preferred outcomes and needs for organizations when they use the tool. Improved ideas and requirements for the tool were considered and translated into the practice of HRD professionals. Together with the insights derived from phase 1b, it provided an answer on research question C.

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2b. Content design

After execution of phase 2a, formative evaluation sessions were used to discuss concept tool I, which was the outcome of phase 1. The aim was to use the input gathered during this phase for the development and adaption of a second version of the tool. For this purpose, different stakeholders were approached. Firstly, HRD professionals from practice were approached to evaluate the tool. They all got randomly three different components from the scan and evaluated those on clearness, correctness, and usefulness. In addition, it was also evaluated if the distinction in levels were distinctive enough. Finally, there was also space for some additional comments. Data was gathered by recording the conversations and the respondents provided notes.

Afterwards, adaptions were made and the concept tool was assessed again, but this time by four practitioners from different organizations. This step contributed to answering research question D. However, this research question will also return in phase 3, since the scan will be evaluated and adapted until its final version. After this phase, there are two different versions of the tool. One is developed for employees, and one is for HR or supervisors. They got some additional questions in order to put the gathered data in the right perspective.

4.1.3 Phase 3 – Evaluation during a pilot study

During phase 3, the second concept tool, which was the outcome of phase 2, was tested into practice by means of a pilot study. For this purpose, two organizations participated, of which one healthcare and one transport and logistics organization. The healthcare organization participated with the department of education. The transport and logistics organization participated with the department of shipplanning and the department of order management.

There were two different clusters: HR/CEO or other supervisors, and employees, equal to the two different types of the tool which were developed after phase 2. The respondents received an email with a digital version of the tool. The pilot also consisted of an evaluation form which could be completed in Qualtrics after participants completed the tool. Afterwards, a presentation was prepared for each team separately in order to give the respondents insights in the most important findings of the scan. Secondly, there was also space for a responsive evaluation, which questioned quality of the tool and again by evaluating its clearness, correctness, and usefulness. Both the pilot, the evaluation form and the responsive evaluation sessions contributed to answering research question D. The evaluation form can be found in appendix E.

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4.2 Respondents

The goal of this research was to obtain insights into a particular setting, in order to extract meaning from the collected data. In order to answer the research questions and design the tool for Organizational Readiness for SDL, different types of respondents were approached, depending on the phase in the research: SDL experts, future users, and HRD professionals, were approached to give input for answering the research questions. All respondents participated voluntary and confidential. In this section, each group of respondents will be explained in more detail following the three phases during this research.

4.2.1 Phase 1 – Analysis and exploration SDL experts

Purpose sampling is used for the selection of the SDL experts. This is a non-probability sampling technique that is most effective when studying a certain cultural domain with knowledgeable experts within (Tongco, 2007). The SDL experts were involved in the first phase of this research. They were sampled by a search on the internet for professionals who have experience with SDL in organizations, consulting in SDL, or because of (scientific) publications about SDL. In total, five SDL experts were approached by letter for the participation of a semi- structured interview. Three out of five SDL experts were willing to participate. Expert A was a professor in HRD and participated in writing a book about the process towards SDL in a health care organization. Expert B was a consultant specialized in SDL. This expert advises and guides organizations in the process SDL for more than 15 years. Finally, expert C is an educationalist and independent advisor who wrote several articles and blogs about SDL. All SDL experts were men and over 50 years of age.

Future users

During the first phase of this research, future users were invited to give their opinions about factors that they consider as important for their own self-direction in learning. They were approached by a vlog, which was spread among via a video platform. 11 out of 34 approached future users responded by filling in a tally chart. Almost all respondents have at least a bachelor or master in education, business administration, I(C)T, HR or related study. The distinction between men and women and age is not known, because they responded anonymously.

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4.2.2 Phase 2 – Design & Construction HRD professionals

For the second phase of this research, HRD professionals of different organizations were approached by email. Those HRD professionals belong also to the group of future users, but have particular knowledge and experience about learning and development in organizations. Therefore, there position as an HRD professional was a particular sample requirement. The HRD professionals are asked if they were willing to participate in both semi-structured interviews and an evaluation session. Of the seven approached HRD professionals, four responded and agreed for participation, of which four men and one woman. Two out of seven respondents are responsible for the training offer within their organization, one is also specialized in HRM and the other HRD professional has led a research in developing measurement instrument for measuring individual SDL, called the iSelf.

Age of the HRD professionals ranged between 31 and 64 years of age. The sampling method that was used is convenience sampling, since the approached people that were willing and available to participate, participated (Onwuegbuzie & Leech, 2007).

Future users

During step 4 of the research process, a new group of four future users was approached in order to assess the concept tool. They all responded that they were willing to participate. Two of them had a management position and filled in the scan developed for HR/CEO or other supervisors.

The other two organizational members were part of the operational staff and completed the scan developed for employees.

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4.2.3 Phase 3 – Evaluation Future users

For the purpose of the final phase, organizations were needed which wanted to participate in the pilot study. Therefore, five different organizations were approached, which either were involved earlier in the research process or indicated their interest. Two organizations responded positively: Tjongerschans participated with the department of education and Timberland participated with the departments order management and shipplanning. In both cases, the used sampling method is purposive sampling, because the sample is selected based on characteristics of a population and the object of this study (Tongco, 2007).

Tjongerschans is a regional hospital with three locations in the Dutch province of Friesland.

4 out of 8 approached team members completed the tool and the additional evaluation form. One of them had a supervisory role, the other three were part of the operational staff. Their age varied between 38 and 57 years old.

Timberland is originally an American company, which sells mainly clothing and shoes. The European distribution center is located in Almelo, a city in the eastern part of The Netherlands. They are responsible for the distribution of their products in Europe, the Middle and Far East, and South America. From the department order management, all 6 approached respondents participated and additionally completed the evaluation form and participated in a responsive evaluation. Their age varied between 28 and 39 years old. From the department shipplanning, 4 out of 5 approached team members participated and additionally completed the evaluation form and participated in a responsive evaluation. Their age varied between 29 and 49 years old.

4.3 Instrumentation and procedure

The section below discusses the instruments used for each phase and the procedure of how the data is collected.

4.3.1 Phase 1 – Analysis and exploration Explorative expert interviews

In order to get more insights in important variables for mapping organizational readiness during the start of the research process, explorative expert interviews were used. This type of interviewing gives a researcher fast access to new or unknown knowledge, and it is less time consuming than other research methods (Van Audenhove, 2007). The experts provide insights in aggregated and/or specific knowledge regarding SDL (Van Audenhove, 2007). All SDL experts were interviewed in a face-to-face setting.

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Tally chart

The second instrument used during phase 1, was a tally chart. The same list with variables as presented to the experts, was presented to future users. They were instructed to determine for each variable whether it is important for their own SDL behavior or not. They could mark it either as really important, neutral, or not important.

4.3.2 Phase 2 – Design & Construction

Semi-structured interviews SDL experts and HRD professionals

This type of interview was used to explore the practical requirements of the tool. A semi- structured interview is a verbal interchange were the researcher attempts to elicit information from another person by asking questions (Clifford, French, & Valentine, 2010). The questions asked during these interviews differed. The SDL experts mainly focused on general design requirements, while the HRD experts mainly focused on implementation requirements.

Formative evaluation sessions

Formative evaluation sessions are rigorous assessments designed to identify potential and actual influences on the progress of the design process (Stetler, Legro, Wallace, Bowman, Guihan, Hagedorn, Kimmel, Sharp & Smith, 2006). It enables researchers to study the complexity of implementation projects and suggests ways to answer questions about context, adaptions and response (Stetler, et al., 2006).

4.3.3 Phase 3 - Evaluation

Pilot study and responsive evaluation

A pilot is a small scale study administered to reveal defects during the research project or in the developed tool by executing a train run (Fraenkel, Wallen & Huyn, 2012; Van Teijlingen &

Hundley, 2001). A pilot study help enlarge the quality of the tool, because it provides a clear overview of aims and objectives within a certain framework (Lancaster, 2002). Methodological rigor will be encouraged, and scientifically valid and publishable work will be ensured (Lancaster, 2002) The responsive evaluation, which took place after the pilot, is a perspective to evaluation that generates qualitative evidence about the value and meaning of developed programs, or tools (Abma, 2005). It is a disciplined form of inquire that enhances the understanding of human behavior, promotes holistic thinking, offers contextual information, and brings in the perspective of the target group (Abma, 2005).

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4.4 Data analysis

The section below discusses per phase how the gathered data is analyzed and processed.

4.4.1 Data analysis phase 1 – Analysis & Exploration

The explorative expert interviews are transcribed and the variables that the experts mentioned as the most and least important were compared to each other. On this basis, a picture emerged of the variables that the SDL experts considered as important and unimportant.

Afterwards, the transcript of the interview was coded axially, in which different fragments of the interviews were compared with each other, searching for similarities and discrepancies (Straus, 1987). The goal of the coding was to discover themes or patterns of practical requirements of the tool. In addition, there was a particular focus on distinguishing the different performance levels that the experts recommended in developing a tool. During the coding, conventional content analysis is used. This approach is generally used when the aim of a study is to describe a phenomenon and is usually an appropriate strategy when research literature on a phenomenon is limited (Hsieh & Shannon, 2005). The coding categories are derived from the main themes determined prior to the interviews. Therefore the analysis was inductive (Thomas, 2006). An inductive analysis provides an easily used and systematic set of procedures for analyzing qualitative data, which helps to produce reliable and valid findings (Thomas, 2006). The main themes during the coding were divided in two themes: (1) data about the development of the tool, and data about the execution of the tool within organizations. From bottom up, five codes were developed for de development of the tool. These codes are: (1) ideal situation, (2) clear descriptions, and (3) easy to understand, (4) number of performance levels, and (5) use of existing knowledge and resources.

For execution of the scan, the codes are: (1) learning about an organization, (2) process, (3) phenomena behind the facts, and (4) target group. All interviews were summarized on those codes and subsequently processed in the results section. Summaries of the interviews can be found in appendix B.

The knowledge generated from the content analysis are based on the unique perspectives of participants and grounded in the actual data (Hsieh & Shannon, 2005). The research team of educational scientists were responsible for this. The coded interviews and insights were presented to them, and they checked the validity of the coded content.

Data analysis of the tally chart is conducted by counting how many future users considered each variable as important or unimportant. It provided immediately insights in the most and least important variables according to the opinion of future users for their own SDL behavior. Neutral

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variables were seen as neither important nor unimportant. On the basis of these two types of data analyzes, the variables for the first concept tool were chosen by the researcher.

4.3.4 Data analysis phase 2 – Design & Construct

The semi-structured interviews with HRD professionals were recorded and transcribed.

Thereafter, the analysis of these data was similar to the analysis of the interviews with SDL experts.

The already developed coding categories were used as a starting point to code the transcribed data of the HRD professionals. However, there was some difference compared to the SDL experts.

Where the practical requirements of the SDL experts mainly focused on scientific requirements in developing a tool, the HRD professionals mainly focused on practical needs. Therefore, the coding theme ‘general requirements for a tool’ is supplemented with ‘practical needs of future users’. The interviews with the HRD professionals are, in line with the interviews of the SDL experts, summarized on those codes and subsequently processed in the results section.

The analysis of the formative evaluation session is conducted by means of discussing parts of the scan with different future users. During these discussions, all comments on the dimensions, descriptions, and content were collected verbally by the researcher, and if necessary, directly adapted, inserted or deleted. At the same time, both respondents and researcher wrote notes about possible improvements. The conversations are recorded and transcribed in order make sure that all discussed information is secured. The findings of the HRD professionals were adapted in the scan after the evaluation sessions and member-checked by the research group of educational scientists.

4.3.5 Data analysis phase 3 - Evaluation

The pilot study is analyzed on the basis of the evaluation form and the additional responsive evaluations during the team presentations. The outcomes of the evaluation forms were counted and compared, while during the responsive evaluation sessions, respondents were asked to give additional explanations and rate the tool with a number between 1 (=very bad) and 10 (=very good). The coding categories that were used are based on the design requirements clearness, correctness and usefulness, and the insights, awareness and handles it created with respect to important characteristics of Organizational Readiness for SDL. In addition, the analysis of the data revealed one new theme that are used during coding of the data.

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4.4 Quality assurance

The research conducted involved complex processes, facing interpretations of the researcher and participants, and different iteration. Whereas this type of research often uses less standardized procedures of data gathering and analysis, it is often not clear how the quality was insured or assured (Akkerman, Admiraal, Brekelmans & Oost, 2008). In order to ensure quality in terms of this research process, all steps were evaluated and verified by means of an audit procedure. An audit procedure consists of several stages, equal to the stages during the research process. During those phases, the position of the research and its assumptions, the transparency of decisions and assumptions held, the comprehensiveness of approach to the research questions, validity, used procedures, methods, and analyses are checked in order to ensure the quality of the research (Akkerman et al., 2008). In addition, there was a particular focus on the three core themes for the evaluation of the developed tool, namely (1) clearness, (2) correctness, and (3) usefulness.

The audit procedures were conducted by a group of five educational scientists and carried out after each step during the research process. Thus, there was a total of five audits. Outcomes of the audit procedure were discussed in planned evaluation sessions.

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5. Results

In this section the results will be discussed, structured by each phase in the research process.

Summaries of all interviews could be found in appendix B.

5.1 Phase 1 – Analysis & Exploration

Phase 1 contributed to answering the following research questions:

A. Which organizational factors should be included in a tool mapping the Organizational Readiness for SDL within an organization?

B. How can the organizational factors from research question A. be distinguished into different levels of performance?

C. What ere the design requirements for mapping Organizational Readiness for SDL according to SDL experts?

5.1.1a Important variables according to SDL experts

The figure below shows the overview of most and least important variables according to the SDL experts by the green checkmarks. Additionally, it shows which variables the experts did not mention as one of the most important variables, but which they still consider as important enough for the development of the tool. This is shown by a black checkmark. Variables considered as unimportant are shown by a red cross.

Expert 1 Expert 2 Expert 3

Individual variables

Demographics & Human Capital

Age & Gender x x x

Educational degree x x

Personality

Proactive behavior x x

Autonomy x x x

Psychology

Motivation √ √ √

Internal locus of control

Self-efficacy √ √ √

Pursuit of knowledge work √ √

Career satisfaction √

Mobility aspiration √

Organizational variables Job characteristics

Higher task variety √

Developmental opportunities

Job autonomy √

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Policy & Culture

Build and communicate shared vision

and goals √ √ √

Fostering collaboration, teamwork, and

interaction √ √

Supportive management style √ √ √

Risk taking √ √

Innovation √ √

Learning and experimenting √ √ √

Tolerance of errors √ √

Environment of trust √ √ √

Table 1. Most and least important variables according to SDL experts.

All experts considered ‘motivation’ and ‘self-efficacy’ as important variables. At the same time, they all mentioned that ‘age and gender’ are unimportant to measure for the purpose of the tool. Expert 3 particularly stressed the importance of all policy and culture variables: “Could I choose for all the policy and culture variables at once and mention them as important?” The importance of policy and culture variables is also recognized by the other experts, given the amount of check marks.

5.1.1b Important variables according to future users

The table below provides an overview of all votes on the behalf of the future users.

Level of importance Important Neutral Unimportant

Individual variables

Demographics & Human Capital

Age & Gender I III IIIII I

Educational degree IIIII I III I

Personality

Proactive behavior IIIII IIII I

Autonomy IIIII III I

Psychology

Motivation IIIII IIIII I

Internal locus of control IIII IIII

Self-efficacy IIIII IIIII

Pursuit of knowledge work IIIII I II

Career satisfaction IIIII I III

Mobility aspiration III III II

Organizational variables Job characteristics

Higher task variety IIIII IIII

Developmental opportunities IIII IIIII

Job autonomy IIIII IIII I

Policy & Culture

Build and communicate shared

vision and goals III IIIII I

Towards a tool mapping Organizational Readiness for Self-Directed Learning