Conference PaperPDF Available

Learning What you Really, Really Want: Towards a Conceptual Framework of New Learning in the Digital Work Environment

Authors:
  • Niedersächsischer Fußballverband

Abstract

Digitization and globalization are leading to changing demands in the world of work. To cope with these, employees must constantly learn and develop. Analogous to the New Work movement, the future of learning seems to belong to New Learning, in which protean and empowered learners pursue learning opportunities to achieve subjectively valuable learning outcomes and personal growth. This meaningful and socially-embedded kind of learning enables learners to learn what they really, really want to learn. In the literature, however, there is a lack of models and theories on New Learning. The present paper introduces a conceptual framework of New Learning building on psychological theories in terms of a causal chain whose ten propositions can be empirically examined in future studies. An important premise is that, in addition to personal characteristics of the learner, the socio-technical environment and (digital) tools and methods play an important role for New Learning. The paper concludes by setting a future research agenda and discussing the practical implications of New Learning.
Learning What you Really, Really Want: Towards a Conceptual Framework
of New Learning in the Digital Work Environment
Julian Decius
Paderborn University
julian.decius@upb.de
Timo Kortsch
Denkverstärker
kortsch@denkverstaerker.de
Hilko Paulsen
BWZ
hilko.paulsen@gmail.com
Anja Schmitz
Pforzheim University
anja.schmitz@hs-pforzheim.de
Abstract
Digitization and globalization are leading to
changing demands in the world of work. To cope with
these, employees must constantly learn and develop.
Analogous to the New Work movement, the future of
learning seems to belong to New Learning, in which
protean and empowered learners pursue learning
opportunities to achieve subjectively valuable learning
outcomes and personal growth. This meaningful and
socially-embedded kind of learning enables learners to
learn what they really, really want to learn. In the
literature, however, there is a lack of models and
theories on New Learning. The present paper introduces
a conceptual framework of New Learning building on
psychological theories in terms of a causal chain whose
ten propositions can be empirically examined in future
studies. An important premise is that, in addition to
personal characteristics of the learner, the socio-
technical environment and (digital) tools and methods
play an important role for New Learning. The paper
concludes by setting a future research agenda and
discussing the practical implications of New Learning.
1. Introduction
The world of work is changingnot just in recent
years, but the pace of change has accelerated throughout
the last decades [1]. Technologization, digitalization
and globalization shape modern work environments and
have an enormous impact on the what, where and how
of working. At the same time, questions concerning
meaningful work and autonomy gained in importance
[2, 3]. Reflecting these changes, the term New Work has
received attention in practice and research. Bergmann
[4], taking a critical look at the previous understanding
of employment, introduced the term and characterized
New Work as needing to contain "work that you really,
really want to do." In organizational psychology
research, Schermuly [5] picked up on the concept and
related New Work to empowerment research [6]. He
assumed that psychological empowermentthe
experience of meaning, competence, self-determination,
and impactmediates the relationship between New
Work activities and positive outcomes for performance
and health [5].
It is not only work that is changing, however, but
also why and how employees acquire competencies [7,
8]. Continuous and lifelong learning through and for
work becomes more important to meet the challenges of
the changing world of work [1, 9, 10]. At the
organizational level, companies must remain flexible
and adaptive to keep pace with global competition; at
the personal level, employees must therefore also
expand their knowledge to actively shape change and
not be replaced by other employees. But the “half time
of knowledge” has decreased in recent decades,
rendering professional knowledge obsolete more
quickly [11]. In addition to training-based formal
learning, more flexible learning forms such as informal
learning [12] and self-regulated learning [13] thus
attracted research attention. Individuals, however, have
always been learning informally, through trial and error,
feedback, and reflection; or in a self-regulated way
through setting their own learning goals, monitoring and
regulating the learning process. Thus, just as work is
changing into New Work, we assume that learning is
also evolving into New Learning. What does New
Learning look like, whichin the spirit of Bergmann
[4]emphasizes the autonomous role of the learner but
also considers the increasing demands of the volatile
world of work?
New in the world of work is, above all, associated
with the term “digital”. Digitalization offers an
incredible number of opportunities to acquire job-
relevant skills. However, digital tools are not sufficient
to already speak of New Work [5]. Equally, we cannot
reduce New Learning to the use of digital learning
toolslearners are part of social groups, and their needs
must become the focal point [14]. In the current
dynamic and volatile context, organizations do not
knowor only with delaywhich learning content is
Proceedings of the 55th Hawaii International Conference on System Sciences | 2022
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URI: https://hdl.handle.net/10125/79975
978-0-9981331-5-7
(CC BY-NC-ND 4.0)
needed, and when and where an individual should learn
best. It makes sense to shift the decision about the what,
when, and where of learning to the entity that has
enough information to make a meaningful decision: the
learner. If the learner has a high level of autonomy and
responsibility, following Bergmann [4], we thus might
conceptualize learning what you really, really want as
an essential component of New Learning.
However, the term "new" is currently used in an
undifferentiated and proliferating manner [5, 15].
Specifically, in the field of learning it lacks a clear
conceptualization. We therefore develop a conceptual
framework of New Learning to delineate the learning
process and influencing variables. We consider New
Learning as a process started by the perception of
learning opportunities by empowered learners [6] with
a protean career orientation (i.e., an agentic orientation
toward their own career [16]). The perception of
learning opportunities leads to the formation of a
learning intention, which in turn leads to learning
behaviors, resulting in learning outcomes. This process
is reinforced by the socio-technical work
environmentemphasizing the social embeddedness of
learningand respective (digital) work and learning
tools, as well as personal attitudes of the learner. These
influencing factors are represented as moderators in our
framework. We deduct New Learning from Bergmann’s
[4] socio-philosophical concept of New Work as well as
Schermuly’s psychological New Work theory, focusing
on empowerment. To further specify and extend these
approaches, we base our conceptualization of New
Learning on other established psychological theories
and models: Theory of Planned Behavior [17], Rubicon
Model of Action Phases [18], and Regulatory Focus
Theory [19].
Against this background, New Learning refers to
learning as a socially-embedded process in which the
protean and empowered learner seeks and utilizes
learning opportunities to engage in meaningful formal,
informal and self-regulated learning to achieve
subjectively valuable learning outcomes and personal
growth. New Learning takes place in a new societal and
organizational context brought forth by digitalization
and characterized by dynamic change, uncertainty, and
complexity. This definition underscores the importance
of balancing social and technological aspects in digital
work contexts [20, 21].
Our theoretical paper provides for the first time a
conceptual psychological framework of New Learning,
structured in ten propositions. We set the stage for future
empirical research on the concept, which has so far been
considered mainly from a practical point of view [14,
15, 22]. We also present a future research agenda that
includes possible facilitating factors for New Learning,
as well as implications from the model for practice.
2. Framework Development
We started the development of our conceptual
framework with a literature review for the term "new
learning." The search yielded a few practice-based
articles, articles from neuropsychological learning
research, and frequent use of "new" as a merely
descriptive adjective (e.g., new learning challenges).
Theoretically sound contributions on the future of
learning at work were not present. The search did,
however, reveal a first psychologically grounded
approach to “new work” [5]. We therefore decided to
take the concept of "new work" [4, 5] as the starting
point for our considerations. In setting up our
framework, we therefore followed the basic
assumptions that the empowered learner is at the center
of learning and learns things he or she wants to learn,
rather than primarily following external requirements.
Based on these rationales, we sought psychological
theories and models that would explain human attitudes,
motives, and behaviors in this specific work context. We
then established the basic conceptual chain from the
new learner’s prerequisites to the learning outcomes.
Subsequently, strove to identify possible moderators of
the specified relationships. This deductive process
resulted in ten propositions.
3. Conceptual Psychological Framework of
New Learning
The following ten propositions form the causal
chain of the conceptual psychological framework of
New Learning as shown in Figure 1. Each proposition is
introduced in sequence below.
Proposition 1. There are two important antecedents
of New Learning: protean career orientation and
psychological empowerment. High levels of protean
career orientation and psychological empowerment
increase the potential to perceive learning opportunities.
By doing so, they build a formative construct, that we
call learning opportunities perception potential (LOPP).
Protean career orientation. The concept of a protean
career addresses the employee’s long-term
development: Hall [23] conceptualized protean career as
"a process which the person, not the organization, is
managing". Central to this process is "an agentic
orientation toward one's career" (p. 201). Individuals
differ in their protean career orientation, an attitude that
comprises two central facets: self-direction and
orientation toward intrinsic values [24]. That is,
employees feel responsible for their careers, career-
related decisions, and actions. Intrinsic values such as
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autonomy, meaning and growth guide the career pursuit.
Self-direction also results in volition to pursue long-
term career goals. High levels of protean career
orientation should result in an increased awareness of
career development opportunities and employability
[25]. These career opportunities may also require
learning something [26]. High levels of protean career
orientation sharpen the lens through which individuals
perceive their environment including its offer of
learning opportunities. Consequently, high levels of
protean career orientation should increase the LOPP.
Empowerment. While protean career orientation
focuses on individual differences, empowerment is
rather linked to job characteristics, though it is just a
subjective reflection of objective job characteristics
[27]. Contrary to a widespread belief, however, New
Work is not achieved by organizations equipping their
employees with mobile technologies and providing
home office facilities. Schermuly [5] notes that sending
employees home with a smartphone for paid work is
fundamentally
contrary to the understanding and spirit of Bergmann's
concept [4] of work-related freedom of choice. In this
organization-driven structural empowerment approach,
the focus is on the macro level, i.e., on the company's
structures. However, since employees interpret their
work environment and work processes individually and
independently of collective structures [5], the
psychological empowerment approach is preferable for
New Work and New Learning. According to Spreitzer
[6], this multi-faceted approach includes the facets
meaning, competence, self-determination, and impact
(see also [28]). Employees with high levels of
psychological empowerment perceive their work as
valuable, experience competence and autonomy. So,
they may enrich their work with learning opportunities.
Consequently, psychological empowerment should
increase the potential to perceive learning opportunities.
Proposition 2. It is important to note, that neither
protean career orientation nor psychological
empowerment provide learning opportunities. Both are
personal characteristics that are antecedents of the
LOPP. We conceptualize the LOPP as a stable but still
malleable personal factor, which serves as a cognitive
and motivational filter. This filter shapes the
individual’s perception within their work environment
and helps to identify attractive learning opportunities in
specific situations. More specifically, self-direction
leads to a proactive seeking for learning opportunities,
value orientation leads to recognizing attractive learning
opportunities, and empowerment leads to evaluating the
feasibility of learning (cf. [6, 29, 30]). A high LOPP
increases the probability to recognize learning
opportunitiesbut in a situation without any objective
learning opportunities, an individual cannot perceive
any learning opportunity. However, in situations with an
average amount of learning opportunities, high levels of
LOPP will result in high levels of perceived learning
opportunities, whereas low levels of LOPP will result in
low levels of perceived learning opportunities.
Proposition 3. The socio-technical environment is
an important moderator in the relationship between
LOPP and perceived learning opportunities. As
described, the LOPP serves as a filter that allows
objectively available learning opportunities to become
perceived learning opportunitieshowever, how well
this filter works depends not only on the filter quality
Figure 1. Conceptual Framework of New Learning
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but also on whether it is used in a “filter-friendly” or
“filter-hostile” environment. One key aspect of the
environment's "filter-friendliness" is the digitalization
of work. The higher the digitalization within a socio-
technical system, the higher are learning demands and
opportunities. New technologies, for instance, require
the acquisition of new skills (cf. [31]). It is important to
note that digitalization is by far more than just the usage
of new technologies. Digitalization affects the broader
socio-technical system and has an impact on
organizational structures and processes, and in turn
requires new roles from employees [21, 32, 33]. That is,
with increased digitalization, working conditions (e. g.,
complexity, autonomy) and processes will change (e.g.,
new work tasks) and provide learning opportunities in a
broader way. The usage of digital information
technology enables collaboration between teams within
an organization and beyond organizational structures.
However, these changes are just perceived as learning
opportunities if LOPP is high. In contrast, in conditions
of lower LOPP due to low protean career orientation or
a lack of psychological empowerment, the same
changes may be appraised as hindering demands rather
than opportunities (cf. [34]). The socio-technical
environment also comprises social factors such as
organizational cultures [35] as well as supervisor and
co-worker support. A positive learning culture shapes
the values of and basic assumptions about learning and
facilitate individual learning [36]. Within organizations
that value learning, the link between LOPP and
perceived learning opportunities is higher. Supervisor
and co-worker support are important environmental
factors for learning and application of knowledge in
practice [37]. Furthermore, human resource
management and its practices influence the perception
of learning opportunities [38].
Proposition 4. Perceived learning opportunities
make the learner develop a learning intention, i.e., the
concrete behavioral intention to engage in learning
behavior. Perceived learning opportunities can be
considered affordances to learn (cf. [39]), i.e., perceived
learning opportunities encourage a person to learn. For
example, if someone perceives that coworker support is
available and that learning from errors is a desired
behavior, they are more likely to learn from them [40].
Following the action phase model, perceived learning
opportunities can be assigned to the predecisional phase
[18]. Encouraged to learn by a learning opportunity and
having formed a concrete learning intention, the learner
"crosses the Rubicon". The learner enters the
preactional phase, in which it is no longer a question of
whether something is learned, but how it is learned.
Proposition 5. As stated before, we assume that the
perception of learning opportunities leads to a learning
intention. However, the strength of this relationship
depends on one important factor: enthusiasm for the
learning topic. Building on Bergmann [4] who
proclaims in his book on New Work and new culture that
the future belongs to work "that we really, really want"
(p. 121), in our opinion the future of meaningful
learning belongs to learning what you really, really
want. This kind of learning does not only satisfy the
psychological need for competence but also the need for
autonomy, and therefore promotes intrinsic motivation
[41]. In other words: The effect of perceived learning
opportunities on learning intention is moderated by this
enthusiasm for the learning topic. These positively
experienced emotions not only push the motivational
process of intention formation but can also lead to a
positive upward spiral over time as stated in the
broaden-and-build theory [42]. That is, enthusiasm for
the learning topic fuels learning and growth. Learning,
application of what has been learned, and experiencing
competence are in turn the basis for increasing
enthusiasm for further learning topics.
Proposition 6. According to the Theory of Planned
Behavior [17], an intention leads to appropriate
behavior when normative beliefs and subjective norms
do not interfere, and the individual holds the belief of
being able to control the situation. A learner capacitated
by the LOPP should have appropriate control beliefs and
learning-enhancing values due to protean career
orientation and empowerment. Accordingly, learning
intention leads to learning behavior. Learning behavior
can be defined as follows:
Engagement in mental processeslearning
eventsthat result in the acquisition and retention
of knowledge, skills, and/or affect over time and
until needed, along with the capacity to identify
conditions of performance and respond
appropriately. More colloquially, learning is an
increased capacity to do the right thing at the right
time. (p. 3 [9])
Proposition 7. The relationship between learning
intentions and learning behavior is moderated by the
availability of tools and learning resources. We assume
that a high availability of tools and resources will
strengthen the relationship between learning intention
and learning behaviors. Digitalization has led to a shift
from instruction via conventional media and methods
(books, classroom-based lectures, or training) to
computer-based media or digital tools [43], such as
enterprise social networks, learning experience
platforms, search engines, wikis, podcasts, webinars,
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instructional videos, and virtual/augmented reality
applications. In digital work environments, these tools
can be flexibly accessed by the learner in the moment of
need (anytime, anywhere, with any device), point to any
content relevant for the learner’s current area of interest,
or even provide customized feedback through wearables
[21, 44, 45]. This access to digital tools as learning
resources increases the learner’s autonomy and is
assumed to consequently facilitate learning behaviors
(cf. [46, 47]). When different learning tools and methods
are available and easily accessible for learners, learning
intent is more likely to result in learning behaviors [48,
49]. New Learning thus manifests itself in empowered
learners who use a wide array of available (digital) tools
to attain their individual learning goals [14].
Proposition 8. In the preactional phase due to the
action phase model [18], the learner's focus is on how to
translate the learning intention into behavior. Three
pathways can be distinguished in work-related learning
contexts, which lead to different learning forms during
the subsequent actional phase (cf. [50]): on the job, near
the job, and off the job (also known as in work, at work,
and outside work [51, 52, 53]).
The "on the job" pathway leads to informal learning
behaviors occurring rather casually in the work process
(e.g., [12, 46]); the "near the job" pathway leads to
learner-planned self-regulated learning (e.g.., [13, 54]),
and the "off the job" pathway leads to more structured
and planned formal learning or training (e.g., [55, 56]).
Below, we describe the three learning forms in more
detail.
Formal Learning. Formal learning refers to high
structuring in terms of learning context, learning
support, learning time, and learning objectives [57].
Formal learning activities are curricular in nature and
have a discrete beginning and end [46]. This includes
training, instruction, and other formal education. The
effectiveness of these activities depends, among other
aspects, on the training method chosen, and the skill or
task characteristics trained [55]. Despite being highly
structured, training interventions should consider
individual learner differences, e.g., personality,
motivation, and self-efficacy [56].
Informal Learning. According to Decius (2020)
[50], work-related informal learning is a conscious
learning that takes place independently of external
structural constraints and directly at the workplace
usually as a spontaneous reaction to a problem or
challenge at work. Accordingly, the learner's intention
is directed towards action or problem solving. Even if
learning process responsibility and control lie with the
learner, an external stimulus determines the goal of
action (e.g., an error in the work process). Informal
learning occurs outside of formally defined learning
contexts or curricula and is characterized by a low
degree of planning and organization with respect to
learning context, learning support, learning time, and
learning objectives [46, 57]. The behavioral facets of
informal learning include trying and applying problem-
solving strategies, exchange with other people (e.g.,
obtaining feedback on one's own work performance),
and reflection on one's own work performance [12, 58].
Self-regulated Learning. Self-regulated learning is
"an active, constructive process whereby learners set
goals for their learning and then attempt to monitor,
regulate, and control their cognition, motivation, and
behavior, guided and constrained by their goals and the
contextual features in the environment" (p. 453 [54]).
Self-regulated learning thus refers to the "modulation of
affective, cognitive, and behavioral processes
throughout a learning experience to reach a desired level
of achievement” (p. 421 [13]). In contrast to informal
learning, the learner pursues a self-imposed learning
goal that does not have to be triggered by a problem
arising in the work process. Accordingly, there is no
action intention but an explicit learning intention [50].
In everyday work, often combinations of the above
learning forms (i.e., formal, informal, self-regulated)
occur. A problem or challenge in the work task, for
instance, may lead not only to informal learning but also
to the employee requesting and participating in training.
However, we consider the presented mapping of
learning forms to learning paths (i.e., on the job, near the
job, off the job) to be typical. New Learning combines
the three learning forms and harnesses their benefits
[14].
Proposition 9. Learning behavior leads to various
valued outcomes. Learning outcomes refer to the
relative permanent change in knowledge, skills, affect
and ability as well as other characteristics (KSAO; [9,
59, 60]). Formal as well as informal and self-regulated
learning have been shown to lead to positive outcomes
on the individual and organizational level [46, 55, 59,
61, 62]. Learning has been shown to be associated with
positive work attitudes, knowledge and skill acquisition,
and improvements in performance criteria (e.g., job
performance, team performance, problem solving,
effectiveness, and promotions) [46, 55, 56, 62].
Learning helps employees adapt to their work
environment and provides them with resources to cope
with work demands (e.g., through job crafting, when
employees adapt or “craft” the task, relational, or
cognitive boundaries of their work; cf. [63]). When
workers adapt their work according to their preferences,
their learning in turn may improve [64]. We ssume that
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learning is thus also associated with less stress and better
health. However, learning opportunities could increase
demands in the long-term and therefore result in more
strain (e.g., delegated tasks and responsibilities, cf.
[65]).
Proposition 10. According to Higgins' [19]
Regulatory Focus Theory, a promotion focus is
characterized by the individual's striving for positive
outcomes. In the New Learning framework, the effect of
learning behavior on learning outcomes is reinforced by
the promotion focus of the learner as a moderator. If the
learner pursues positive outcomes rather than just
learning something to avoid negative outcomes
(prevention focus), we expect more positive
consequences [66, 67]. Aiming for positive outcomes
should be more likely if the learner feels enthusiasm
about the learning content. Qualitative research has
shown that stress and errors enhance learning within the
prevention-focus system, whereas positive affect is a
typical motivator for the promotion-focus system [68].
4. Future Research Agenda
Introducing the conceptual framework of New
Learning we have built on psychological theories leads
to further questions that future research could address
(see Table 1). These questions can be divided into five
areas. The first area encompasses the learning process
as an entire chain of effectshere the focus is
particularly on triggers and learning behavior (mainly
related to proposition 8). The moderators of the
relationships can be divided into organizational and
personal moderators The former deal with the socio-
technical system (mainly related to proposition 3), the
latter with the individual characteristics of the learner
(mainly related to propositions 5, 6, 7, 10). Research
should address how the learning process can be best
designed and supported by the organizations and the
learners themselves. The fourth area addresses the
support provided by (digital) learning methods and tools
(mainly related to proposition 7). Finally, the fifth area
focuses on learning outcomes, taking into account both
the learner's and the organization's perspective (mainly
related to proposition 9).
Table 1. A New Learning Research Agenda
Area
Research Questions
Learning
process
In which situations or through which triggers does the learner choose which learning
path to follow (i.e., the formal, informal, and self-regulated learning path)?
How are the different learning forms interrelated?
Is the learning process linear (as presented in the model) or are there feedback loops
(e.g., “learn crafting” behavior)?
Socio-technical
environment/
organizational
moderators
Which role does social support play in New Learning compared to traditional learning
contexts?
What are the roles of Human Resources (HR) and line management in supporting New
Learning?
Are there work changes in a socio-technical environment that foster the perception of
learning opportunities in the short-term, but hamper it in the long-term (e.g., does change
lead to less autonomy)?
● Can social support be replaced by technical (robotic) support?
Which kind of technical or social support (e. g., organizational support, supervisor
support, peer support, feedback and guidance by technical systems) is most important for
the LOPP learning opportunities relationship?
How do social and technical support interact?
● How does the quality or quantity of learning opportunities affect their perception?
● How does New Learning enable the alignment of individual and organizational goals?
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Individual
characteristics /
personal
moderators
Are there additional factors that moderate the relationship between learning intention
and learning behavior (e.g., digital competency)?
Does the prevention focus have a negative effect, no effect at all, or only a less positive
effectcompared to the promotion focuson the relationship between learning
behavior and outcomes?
How does employee tenure affect the relationship between perceived learning
opportunities and learning intention?
● Which subjective norms and values, in the sense of the Theory of Planned Behavior, act
as most conducive to learning in the context of New Learning?
● How can enthusiasm for learning be awakened?
Learning tools
● Are analog or digital tools better suited to promote New Learning, or is there no
difference?
● How do analog and digital tools interact to promote New Learning?
● Which affordances of digital tools foster New Learning?
● How effective are learning tools (e.g., learning experience platform) and work tools
(e.g., collaboration software) in promoting New Learning? How do they interact?
Is there a "Dark Side of Technology" in digital-driven learning that could threaten
learner autonomy?
Learning
outcomes
● Which outcomes are the most important in New Learning (rather knowledge acquisition,
performance, or health)?
● Is there an adverse impact of New Learning?
● Which outcomes are most important to the learner?
● Which outcomes are most important for the organization?
5. Practical Implications, Limitations, and
Conclusion
Our conceptual framework of New Learning has
various practical implications at the levels of
organizations, teams (with the leaders as particularly
relevant team members), and individuals.
At the organizational level, the role of HR
departments needs to be further developed. In the spirit
of the New Learning model, which considers the
learner as the active designer of all learning, the HR
department must create its services in a learner-centric
way. The HR strategy therefore needs to consider the
individual goals of the employees or at least allow a
corridor for individual development. Here, the
reflection of the current learning culture can delineate
this corridor (cf. [14, 36]). The learning culture and the
associated basic assumptions (e.g., "learning moves
the company forward"), values ("making mistakes is
valuable"), and artifacts (e.g., allowing time for
learning, providing easily accessible digital and non-
digital learning resources, cf. [35]) serve as a guide
that makes it clear to employees what learning is
desired and what fits the company's strategy.
Moreover, a positive learning culture leads to the
perception and creation of additional learning
opportunities. This can also be a response to the
problem that changes resulting from digitization might
lead to working conditions that offer fewer
opportunities for learning (e.g., high degree of
automation, less autonomy).
The team is an important context for New
Learning, since a large part of New Learning takes
place in the direct social work environment.
Colleagues are often sparring partners or sources of
learning, and they can also play a role in the
application of methods. It might also be helpful to
bring people with similar enthusiasm for learning
together in a team so that they can infect each other
with their enthusiasm.
From the team in general, leaders stand out as
particularly relevant for New Learning. Because
leaders act as role models and set the conditions under
which learning may occur (cf. [69]) it is important to
sensitize managers so that they shape the learning
environment of their employees. In addition, leaders
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can empower their employees and thus facilitate New
Learning by giving them meaningful tasks that enable
them to experience competence and allow them to
make choices [5, 6].
At the individual level, the framework suggests
that employees have a great deal of control over
whether they become New Learners. Here, we can
imagine many levers. Learners have the best
prerequisites for New Learning if they see their own
further development as meaningful and useful for their
own goals, can gain meaning from their learning
activity, strive for positive results, experience
competence, and have autonomy over what they do.
Even if this is only fulfilled to some extent, learners
could engage in the things they really, really want to
do to facilitate learning. The New Learning process
can also be strengthened by choosing tools and
methods that the learner feels are individually
appropriate.
In this paper, we have attempted to define the term
New Learning, link it to existing concepts, and
conceptualize it within a psychological framework.
However, a systematic literature review was not
possible due to the ambiguity of the term. Moreover,
due to space constraints, we had to limit the present
paper to a brief presentation of the relevant theories
and mechanismswe refer interested readers to the
cited sources instead. In this sense, we would like this
contribution to be understood as a starting point for
further research.
Concluding, the presented conceptual framework
of New Learning offers a human-centered approach to
learning in the digital work environmenta work
environment that challenges employees to learn
continuously (cf. [21]). A perspective focusing on
learner autonomy and enthusiasm is specifically
important in digital work contexts where rapid
advancements in technology, automation and analytics
pose the risk of decreased employee autonomy and
control. Our framework provides a building block for
creating a more human-centered work design, opening
an avenue for digital work contexts to turn into an
opportunity for augmenting learning instead of
reducing learner autonomy.
6. References
[1] Vial, G. (2019). Understanding digital transformation: A
review and a research agenda. The Journal of Strategic
Information Systems, 28(2), 118144.
[2] Grant, G. B. (2017). Exploring the Possibility of Peak
Individualism, Humanity's Existential Crisis, and an
Emerging Age of Purpose. Frontiers in Psychology, 8,
1478.
[3] Bailey, C., Lips‐Wiersma, M., Madden, A., Yeoman, R.,
Thompson, M., & Chalofsky, N. (2019). The Five
Paradoxes of Meaningful Work: Introduction to the
special Issue ‘Meaningful Work: Prospects for the 21st
Century’. Journal of Management Studies, 56(3), 481
499.
[4] Bergmann, F. (2019). New work, new culture: Work we
want and a culture that strengthens us. UK: John Hunt
Publishing.
[5] Schermuly, C. C. (2019). New Work Gute Arbeit
gestalten: Psychologisches Empowerment von
Mitarbeitern [New Work Designing Good Work:
Psychological Empowerment of Employees] (2. Ed.).
Freiburg: Haufe.
[6] Spreitzer, G. M. (1995). Psychological empowerment in
the workplace: Dimensions, measurement, and
validation. Academy of Management Journal, 38(5),
1442-1465.
[7] Noe, R. A., Clarke, A. D., & Klein, H. J. (2014). Learning
in the twenty-first-century workplace. Annual Review of
Organizational Psychology and Organizational
Behavior, 1(1), 245-275.
[8] Regan, E., & Delaney, C. (2011). Brave new workplace:
The impact of technology on location and job structures.
In M. Malloch, L. Cairns, K. Evans, & B. N. O'Connor
(Eds.), The SAGE handbook of workplace learning (p.
431-442). London: Sage.
[9] Kraiger, K., & Ford, J. K. (2021). The Science of
Workplace Instruction: Learning and Development
Applied to Work. Annual Review of Organizational
Psychology and Organizational Behavior, 8, 45-72.
[10] Nicolaides, A., & Poell, R. F. (2020). “The Only Option
Is Failure”: Growing Safe to Fail Workplaces for Critical
Reflection. Advances in Developing Human Resources,
22(3), 264-277.
[11] Arbesman, S. (2013). The half-life of facts: Why
everything we know has an expiration date. Penguin.
[12] Decius, J., Schaper, N., & Seifert, A. (2019). Informal
workplace learning: Development and validation of a
measure. Human Resource Development Quarterly,
30(4), 495-535.
[13] Sitzmann, T., & Ely, K. (2011). A meta-analysis of self-
regulated learning in work-related training and
educational attainment: What we know and where we
need to go. Psychological Bulletin, 137(3), 421-442.
[14] Kortsch, T., Decius, J., & Paulsen, H. (2021). „New
Learning“: Wie sich das Lernen bei der Arbeit verändert
["New Learning": How learning at work is changing].
Wirtschaftspsychologie aktuell, 2021(1), 44-48.
[15] Foelsing, J., & Schmitz, A. P. (2021). New Work braucht
New Learning [New Work needs New Learning].
Wiesbaden: Springer Gabler.
[16] Hall, D. T., Yip, J., & Doiron, K. (2018). Protean careers
at work: Self-direction and values orientation in
psychological success. Annual Review of Organizational
Psychology and Organizational Behavior, 5, 129-156.
[17] Ajzen, I. (1991). The theory of planned behavior.
Organizational Behavior and Human Decision
Processes, 50(2), 179-211.
[18] Heckhausen, H., & Gollwitzer, P. M. (1987). Thought
contents and cognitive functioning in motivational versus
Page 5238
volitional states of mind. Motivation and Emotion, 11(2),
101-120.
[19] Higgins, E. T. (1997). Beyond pleasure and pain.
American Psychologist, 52(12), 1280-1300.
[20] Bennett, E. E. (2014). Introducing New Perspectives on
Virtual Human Resource Development. Advances in
Developing Human Resources, 16(3), 263280.
[21] Parker, S. K., & Grote, G. (2020). Automation,
Algorithms, and Beyond: Why Work Design Matters
More Than Ever in a Digital World. Applied Psychology:
An International Review (online first).
[22] Hagen New Learning Manifesto (2021). Retrieved from
https://www.fernuni-hagen.de/english/university/hagen-
manifesto.shtml [last access: 01.06.2021].
[23] Hall, D. T. (1976). Careers in organizations. Glenview,
IL: Scott, Foresman.
[24] Gubler, M., Arnold, J., & Coombs, C. (2014).
Reassessing the protean career concept: Empirical
findings, conceptual components, and measurement.
Journal of Organizational Behavior, 35(1), 23-40.
[25] Lin, Y. (2015). Are you a protean talent? The influence
of protean career attitude, learning-goal orientation and
perceived internal and external employability. The
Career Development International, 20(7), 753-772.
[26] Van Der Heijden, B., Boon, J., Van der Klink, M., &
Meijs, E. (2009). Employability enhancement through
formal and informal learning: an empirical study among
Dutch non‐academic university staff members.
International Journal of Training and Development,
13(1), 19-37.
[27] Spreitzer, G. M., Cameron, L., & Garrett, L. (2017).
Alternative work arrangements: Two images of the new
world of work. Annual Review of Organizational
Psychology and Organizational Behavior, 4, 473-499.
[28] Thomas, K. W., & Velthouse, B. A. (1990). Cognitive
elements of empowerment: An “interpretive” model of
intrinsic task motivation. Academy of Management
Review, 15(4), 666-681.
[29] Gijbels, D., Raemdonck, I., & Vervecken, D. (2010).
Influencing work-related learning: The role of job
characteristics and self-directed learning orientation in
part-time vocational education. Vocations and Learning,
3(3), 239-255.
[30] Hirschi, A., Jaensch, V. K., & Herrmann, A. (2017).
Protean career orientation, vocational identity, and self-
efficacy: An empirical clarification of their relationship.
European Journal of Work and Organizational
Psychology, 26(2), 208-220.
[31] Van Laar, E., van Deursen, A. J., van Dijk, J. A., & de
Haan, J. (2020). Determinants of 21st-century skills and
21st-century digital skills for workers: A systematic
literature review. Sage Open, 10(1), 215824401990017.
[32] Strohmeier, S. (2020). Digital human resource
management: A conceptual clarification. German
Journal of Human Resource Management, 34(3), 345-
365.
[33] Trenerry, B., Chng, S., Wang, Y., Suhaila, Z. S., Lim, S.
S., Lu, H. Y., & Oh, P. H. (2021). Preparing Workplaces
for Digital Transformation: An Integrative Review and
Framework of Multi-Level Factors. Frontiers in
Psychology, 12, 620766.
[34] Meyer, S. C., & Hünefeld, L. (2018). Challenging
cognitive demands at work, related working conditions,
and employee well-being. International Journal of
Environmental Research and Public Health, 15(12),
2911.
[35] Schein, E. H. (2010). Organizational culture and
leadership (Vol. 2). John Wiley, & Sons.
[36] Kortsch, T., & Kauffeld, S. (2019). Validation of a
German Version of the Dimensions of the Learning
Organization Questionnaire (DLOQ) in German Craft
Companies. Zeitschrift für Arbeits- und
Organisationspsychologie A&O, 63(1), 15-31.
[37] Botke, J. A., Jansen, P. G., Khapova, S. N., & Tims, M.
(2018). Work factors influencing the transfer stages of
soft skills training: A literature review. Educational
Research Review, 24, 130-147.
[38] Bednall, T. C., & Sanders, K. (2017). Do opportunities
for formal learning stimulate follow‐up participation in
informal learning? A three‐wave study. Human Resource
Management, 56(5), 803-820.
[39] Gibson, J. J. (2014). The Ecological Approach to Visual
Perception: Classic Edition. London; New York:
Psychology Press.
[40] Decius, J., Schaper, N., & Seifert, A. (2021). Work
Characteristics or Workers’ Characteristics? An Input-
Process-Output Perspective on Informal Workplace
Learning of Blue-Collar Workers. Vocations and
Learning, 14(2), 285-326.
[41] Ryan, R.M., & Deci, E. L. (2000). Self-determination
theory and the facilitation of intrinsic motivation, social
development, and well-being. American Psychologist,
55(1), 68-78.
[42] Fredrickson, B. L. (2001). The role of positive emotions
in positive psychology: The broaden-and-build theory of
positive emotions. American Psychologist, 56(3), 218.
[43] Mayer, R. E. (2019). Thirty years of research on online
learning. Applied Cognitive Psychology, 33(2), 152159.
[44] Cojocariu, V.‑M., Lazar, I., Nedeff, V., & Lazar, G.
(2014). SWOT Analysis of E-learning Educational
Services from the Perspective of their Beneficiaries.
Procedia - Social and Behavioral Sciences, 116, 1999
2003.
[45] Gegenfurtner, A., Schmidt‐Hertha, B., & Lewis, P.
(2020). Digital technologies in training and adult
education. International Journal of Training and
Development, 24(1), 14.
[46] Cerasoli, C. P., Alliger, G. M., Donsbach, J. S., Mathieu,
J. E., Tannenbaum, S. I., & Orvis, K. A. (2018).
Antecedents and outcomes of informal learning
behaviors: A meta-analysis. Journal of Business and
Psychology, 33(2), 203230.
[47] Damnik, G., Proske, A., Narciss, S., & Körndle, H.
(2013). Informal learning with technology: The effects of
self-constructing externalizations. Journal of
Educational Research, 106(6), 431440.
[48] Hurtz, G. M., & Williams, K. J. (2009). Attitudinal and
motivational antecedents of participation in voluntary
Page 5239
employee development activities. Journal of Applied
Psychology, 94(3), 635653.
[49] Maurer, T. J., Barbeite, F. G., & Mitchell, D. R. D.
(2002). Predictors of attitudes toward a 360-degree
feedback system and involvement in post-feedback
management development activity. Journal of
Occupational, & Organizational Psychology, 75(1),
[50] Decius, J. (2020). Informelles Lernen im Kontext
industrieller Arbeit Konzeptualisierung,
Operationalisierung, Antezedenzien und Lernergebnisse
[Informal learning within the context of industrial work:
Conceptualization, operationalization, antecedents, and
learning outcomes]. Paderborn University.
[51] Jacobs, R. L., & Park, Y. (2009). A proposed conceptual
framework of workplace learning: Implications for
theory development and research in human resource
development. Human Resource Development Review,
8(2), 133-150.
[52] Kyndt, E., & Beausaert, S. (2017). How do conditions
known to foster learning in the workplace differ across
occupations? In J. E. Ellingson & R. A. Noe (Eds.),
Autonomous learning in the workplace (p. 201-218).
New York: Routledge.
[53] Sambrook, S. (2005). Factors influencing the context and
process of work-related learning: Synthesizing findings
from two research projects. Human Resource
Development International, 8(1), 101-119.
[54] Pintrich, P. R. (2000). The role of goal orientation in self-
regulated learning. In M. Boekaerts, P. R. Pintrich & M.
Zeidner (Eds.), Handbook of self-regulated learning (p.
451-502). San Diego: Academic Press.
[55] Arthur, W., JR., Bennett, W., JR., Edens, P. S., & Bell, S.
T. (2003). Effectiveness of training in organizations: A
meta-analysis of design and evaluation features. Journal
of Applied Psychology, 88(2), 234-245.
[56] Ford, J. K., Baldwin, T. T., & Prasad, J. (2018). Transfer
of Training: The Known and the Unknown. Annual
Review of Organizational Psychology and
Organizational Behavior, 5(1), 201-225.
[57] Kyndt, E., & Baert, H. (2013). Antecedents of
Employees’ Involvement in Work-Related Learning: A
Systematic Review. Review of Educational Research,
83(2), 273-313.
[58] Tannenbaum, S. I., Beard, R. L., McNall, L. A. & Salas,
E. (2010). Informal Learning and Development in
Organizations. In S. W. J. Kozlowski & E. Salas (Eds.),
Learning, training, and development in organizations (p.
303-332). New York: Routledge.
[59] Baldwin, T. T., Kevin Ford, J., & Blume, B. D. (2017).
The State of Transfer of Training Research: Moving
Toward More Consumer-Centric Inquiry. Human
Resource Development Quarterly, 28(1), 17-28.
[60] Kraiger, K., Ford, J. K., & Salas, E. (1993). Application
of cognitive, skill-based, and affective theories of
learning outcomes to new methods of training evaluation.
Journal of Applied Psychology, 78(2), 311-328.
[61] Blume, B. D., Ford, J. K., Baldwin, T. T., & Huang, J. L.
(2010). Transfer of training: A meta-analytic review.
Journal of Management, 36(4), 1065-1105.
[62] Tynjälä, P. (2013). Toward a 3-P Model of Workplace
Learning: A Literature Review. Vocations and Learning,
6(1), 11-36.
[63] Bakker, A. B., & Demerouti, E. (2018). Multiple levels
in job demands-resources theory: Implications for
employee well-being and performance. In E. Diener, S.
Oishi, & L. Tay (Eds.), Handbook of well-being. Noba
Scholar.
[64] Van Ruysseveldt, J., van Wiggen-Valkenburg, T., & van
Dam, K. (2021). The self-initiated work adjustment for
learning scale: development and validation. Journal of
Managerial Psychology (online first).
[65] De Lange, A. H., Taris, T. W., Jansen, P., Kompier, M.
A., Houtman, I. L., & Bongers, P. M. (2010). On the
relationships among work characteristics and learning‐
related behavior: Does age matter? Journal of
Organizational Behavior, 31(7), 925-950.
[66] Lanaj, K., Chang, C. H., & Johnson, R. E. (2012).
Regulatory focus and work-related outcomes: a review
and meta-analysis. Psychological Bulletin, 138(5), 998-
1034.
[67] Wolfson, M. A., Tannenbaum, S. I., Mathieu, J. E. &
Maynard, M. T. (2018). A cross-level investigation of
informal field-based learning and performance
improvements. Journal of Applied Psychology, 103(1),
14-36.
[68] Federman, J. E. (2020). Regulatory focus and learning.
European Journal of Training and Development, 44(4/5),
425-447.
[69] Hannah, S. T., & Lester, P. B. (2009). A multilevel
approach to building and leading learning organizations.
The Leadership Quarterly, 20(1), 34-48.
Page 5240
... Self-actualization is promoted through the scope for action and the use of one's own skills and potential [11]. The factor of self-actualization also moves further into focus in the context of New Work [9] and New Learning [46] in the sense of doing "what you really really want". Freedom of action concerning work location and working hours supports self-actualization in the context of work. ...
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This study brings attention to the determinants of 21st-century skills and 21st-century digital skills. The following skills are investigated: technical, information, communication, collaboration, critical thinking, creativity, and problem-solving skills. To understand differences in the level of these skills among workers, we need to know the factors that determine an individual’s skill level. A systematic literature review was conducted to provide a comprehensive overview of empirical studies measuring skill determinants. The results show that there is strong need for research on determinants of communication and collaboration skills. In a digital context, determinants for creativity and critical thinking are hardly studied. Furthermore, the identified determinants of 21st-century skills studies are limited to personality and psychological determinants, neglecting, for example, social determinants such as social support. Although digital skills studies show more variety, they mostly cover demographic and socioeconomic determinants.
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Purpose The purpose of this study is to understand how regulatory focus influences informal learning behaviors. A growing body of research indicates that regulatory focus has significant consequences for goal pursuit in the workplace, yet it has not been readily studied or applied to the field of human resource management (Johnson et al. , 2015). This is one of the few studies to examine the relationship between informal learning and regulatory focus theory that can be applied to the training and development field. Design/methodology/approach Using a qualitative research design, a semi-structured interview was used to increase the comparability of participant responses. Questions were asked in an open-ended manner, allowing for a structured approach for collecting information yet providing flexibility for the sake of gaining more in-depth responses. An interview guideline was used to standardize the questions and ensure similar kinds of information were obtained across participants. A typological analytic approach (Lincoln and Guba, 1985) was used to analyze the data. Findings In a sample of 16 working adults, (44% female and 56% male), participants who were identified as having either a promotion- or prevention-focus orientation were interviewed about types of informal learning strategies they used. The results revealed that performance success and failure have differential effects on learning behaviors for prevention and promotion-focus systems. Stress and errors motivate informal learning for the prevention-focus system, whereas positive affect motivates informal learning for the promotion-focus system. Prevention-focus participants articulated greater use of vicarious learning, reflective thinking and feedback-seeking as methods of informal learning. Promotion-focus participants articulated greater use of experimentation methods of informal learning. Originality/value This study provides an in-depth understanding of how regulatory focus influences informal learning. Few studies have considered how regulatory focus promotes distinct strategies and inclinations toward using informal learning. Performance success and failure have differential effects on informal learning behaviors for regulatory promotion and prevention systems. This has theoretical and practical implications in consideration of why employees engage in informal learning, and the tactics and strategies they use for learning.