Informal workplace learning: Development and validation of a measure

• Published date: 01 December 2019
• Author: Andreas Seifert,Niclas Schaper,Julian Decius
• Date: 01 December 2019
• DOI: http://doi.org/10.1002/hrdq.21368

QUANTITATIVE STUDY

Informal workplace learning: Development

and validation of a measure

Julian Decius | Niclas Schaper | Andreas Seifert

Department of Work and Organizational

Psychology, University of Paderborn,

Paderborn, Germany

Correspondence

Julian Decius, University of Paderborn,

Warburger Str., 100, 33098 Paderborn,

Germany.

Email: julian.decius@uni-paderborn.de

The copyright line for this article was changed

on 6 September 2019 after original online

publication.

Abstract

Informal workplace learning (IWL) is an important part of work-

related continuing education, especially in the case of blue-

collar workers. The current article presents a new measure of

IWL, which we developed based on the already existing

Dynamic Model of Informal Learning by Tannenbaum et al.

(2010). We extended the model to eight components by theo-

retical considerations, introducing a second-order structure.

Each component is represented on the IWL scale with three

items, the subscales have sound internal consistencies (αrange

between .76 and .92). The article also presents a short version

of the scale comprising eight items (α= .79). Study 1 describes

the process of item selection, while Study 2 deals with different

theoretically conceivable models comparing their model fits.

The predicted model with eight factors in a second-order struc-

ture achieves the best model fit. In addition, convergent, dis-

criminant, and criterion validity are demonstrated. Medium-

sized relationships of IWL components to conscientiousness

and learning outcomes confirm the nomological network we

developed previously in our study. The discussion provides limi-

tations and possible scientific and practical applications of the

IWL scale, for example, the transfer of the measure to other

contexts and target groups.

KEYWORDS

blue-collar workers, informal workplace learning, scale

development

DOI: 10.1002/hrdq.21368

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and

reproduction in any medium, provided the original work is properly cited.

© 2019 The Authors. Human Resource Development Quarterly published by Wiley Periodicals, Inc.

Human Resource Development Quarterly. 2019;30:495–535. wileyonlinelibrary.com/journal/hrdq 495

1|INTRODUCTION

1.1 |Relevance of informal workplace learning

Imagine that a factory worker is confronted with a problem in his work process: he notices that the metal parts pro-

duced by the machine he is working on obviously do not meet the requirements. Now the worker could think and

reflect about this challenge, look for a solution using a trial and error strategy, or ask more experienced colleagues

for advice. Therefore, he will presumably develop the intention to learn on his own informally about the specific

problem and possible solutions—instead of waiting for the next formal training on machine operation.

These strategies of the worker mentioned here are components of informal learning in the workplace that takes

place outside formal learning contexts and is predominantly self-directed, intentional, and field-based (Cerasoli et al.,

2018). Indeed, the majority of learning in the modern workplace takes place informally; literature indicates a range of

70–90% for the degree of informality of learning (Eraut, 2011; Noe, Tews, & Marand, 2013). Even in areas in which

formal continuing education plays a major role (e.g., security issues), employees use competencies acquired infor-

mally in the working process more frequently than those formally acquired (Burns, 2008). Informal learning that takes

place in the workplace—or short Informal workplace learning (IWL)—is, therefore, an effective supplement to formal

learning for the development of work-related skills (Ellström, 2001; Kyndt & Baert, 2013; Slotte, Tynjälä, & Hytönen,

2004), because it occurs in an authentic setting that supports learning transfer (Billett, 1995).

Research on IWL has already shown positive learning outcomes of this kind of learning, for example, higher task

performance, personal development, or better team work results (Tynjälä, 2013), which provides benefits for individ-

uals, teams, organizations, and society (Aguinis & Kraiger, 2009). Even if there isa lack of characteristics of a learning

supportive organization (e.g., learning culture), employees seem to learn informally (Berg & Chyung, 2008). IWL might

also have possible dark sides, for example, passing on bad habitsand unprofessional behavior to new colleagues in an

informal way. So far, there exists not a single empirical investigation on these bad outcomes (Cerasoli et al., 2018).

Overall, however,IWL seems to have predominantlypositive outcomes on employees, teams, and organizations.

Formal continuing education programs are often generically structured and not tailored to the needs of individual

employees. In addition, they can hardly keep up with the rapidly changing demands on competence development:

what is learned today in a training course can be outdated tomorrow. The situation is different with IWL, where the

employees themselves decide during the work process when and what they learn. Therefore, especially in times of

changing job requirements, flexible work structures, and digitalization processes, IWL has great potential to enable

employees to acquire the necessary skills in their daily work and to ensure long-term employability (Froehlich,

Beausaert, Segers, & Gerken, 2014; Kyndt & Beausaert, 2017).

However, companies can only realize this potential if they are aware of the extent of IWL among their employees

and know how they can foster it. Human resources managers should have the opportunity to support their workers'

learning in the workplace, to use the positive link between work-related learning and personal career development

(van der Sluis & Poell, 2003). To enable this, human resources managers must find out which employees learn infor-

mally and in what way, to optimally promote IWL; e.g., they can identify work areas in which employees learn partic-

ularly much or little informally to evaluate the individual and organizational conditions for a supportive learning

environment. In this way, they can use the leverage of IWL to achieve desired effects such as higher job satisfaction

and task performance (Cerasoli et al., 2018). Employees also benefit directly: using a scale to measure IWL, they can

receive feedback on their personal IWL behavior—e.g., in employee development interviews with their superiors—

and could agree with reference to this feedback on a continuing training strategy adapted to their individual learning

preferences.

To provide human resources managers with recommendations for promoting informal learning, researchers need

to conduct further studies on the relevant antecedents and outcomes of IWL. Thus, a valid instrument is needed to

measure IWL. Previous attempts to operationalize IWL are based on rather explorative approaches without following

a conceptual framework (see Section 2). Therefore, recent reviews call for the development of a profound scale to

496 DECIUS ET AL.

operationalize IWL (Cerasoli et al., 2018; Jeong, Han, Lee, Sunalai, & Yoon, 2018). Thus, the aim of this study is to

develop a scale to measure IWL using a holistic and theoretically driven framework approach—with a focus on a spe-

cial target group (as we explain later).

1.2 |Target group

However, IWL cannot be studied without considering the circumstances of learning context, learning conditions, and

situations (Ellinger, 2005). Research should focus on specific jobs and industry sectors, because there is no “one-

size-fits-all”approach of workplace learning (Manuti, Pastore, Scardigno, Giancaspro, & Morciano, 2015)—employees

do not learn in the same informal way in the workplace in all sectors and professions. For this reason, we concentrate

in the IWL scale development process on the special target group of blue-collar workers mentioned in the introduc-

tory example.

These employees often dobasic manufacturingtasks in industrial companies of low-technology sectors, but contrib-

ute crucially to theeconomy, even the unskilled andsemiskilled workers (Hirsch-Kreinsen, 2015). In contrast to white-

collar workers or executives, this targetgroup learns more through informalon-the-job trainingsand by trial and errorin

the daily routine than by formal training. Onereason for this are individual learningbarriers: formal training often has a

bad reputation for these workersas it triggers formerschool experiences.Furthermore, fearsabout continuing education

and training are much more pronounced for people with low or no vocational qualifications doing simple work tasks

(Tippelt, Reich, & Panyr, 2004). Blue-collar workers doing simple work tasks are also characterized by a relatively high

migration rate of 20% compared to only 10% in the entire industry (Ittermann, Abel, & Dostal, 2011). We considered

these characteristics when developingthe new measure for blue-collar workers, for example bypiloting and evaluating

the contentof the questionnaire ininterviews with peoplefrom the target group (seeSection 5). However, theworking

methods of blue-collar workers may also differ in various industries. To take this into account and develop a measure

that canbe used as universallyas possible, we conducted the interviews in companiesof various industries: metalrefine-

ment, electrical industry, mechanicalengineering, andfurniture manufacturing.

In contrast to formal le arning, IWL has a low thresho ld for blue-collar worker s and offers direct benefit s for

the working process, for example, if a problem in the workplace can be solved after the learning. Furthermore,

most of the small-sized an d medium-sized enterpr ises that employ most of the blue-collar workers hav e little

financial and time resources for personnel development (Decius & Schaper, 2017). These are important workplace

learning barriers (Crouse, Doyle, & Young, 2011), which occur mainly in smaller companies, so in terms of voca-

tional learning, thes e companies may “not [simply be regarded as] small versio ns of large businesses”(Per kins,

2018, p. 3). Small-sized and medium-sized enterprises usually offer their low-end workers only basic trainings, like

health and safety brief ings, which are required by law. In situat ions where logistical, financial, or pe rsonnel restric-

tions contradict forma l training, IWL thus can be a cost-effective, al ternative approach to competency acquisiti on

and an important additio nal component of personnel d evelopment and supplemen t to formal learning (Ceraso li

et al., 2018; Jones, Beynon, Pickernell, & Packham, 2013). In contrast to other target groups such as managers

(Enos, Kehrhahn, & Bell, 2003; Noe et al., 2013), research results on IWL of blue-collar workers are scarce—despite

the importance of IWL for t hese people. This may also be explained beca use learning behavior and learning stra te-

gies in several other targ et groups differ substantially and there is no spec ific measure for IWL among blu e-collar

workers yet.

1.3 |Contributions

Regarding all these points, our study is supposed to contribute to research and practice in three aspects: first, we

operationalize IWL of blue-collar workers in a conceptually well-grounded manner using the Dynamic Model of Infor-

mal Learning (Tannenbaum, Beard, McNall, & Salas, 2010) as a framework approach. Second, we enlarge this model

and subdivide the model factors to get a more specific operationalization of IWL, driven by theoretical

DECIUS ET AL.497