=Paper=
{{Paper
|id=Vol-2128/industrial6
|storemode=property
|title=Adaptive Learning Design in Corporate Education: Bolstering Leadership Readiness for Organizational Change
|pdfUrl=https://ceur-ws.org/Vol-2128/industrial6.pdf
|volume=Vol-2128
|authors=Tomoko Mikawa,Youngjin Ju,Dongwon Roh
}}
==Adaptive Learning Design in Corporate Education: Bolstering Leadership Readiness for Organizational Change==
https://ceur-ws.org/Vol-2128/industrial6.pdf
Adaptive learning design in corporate education: Bolstering
leadership readiness for organizational change
Tomoko Mikawa, Youngjin Ju, Dongwon Roh, Samsung Electronics Co., ltd.,
t.mikawa@samsung.com, youngjin.ju@samsung.com, dw.roh@samsung.com
Abstract: This case study describes the application of learning science research to customize
the learning interventions for a company-wide change management initiative at Samsung
Electronics Co., ltd., a diversified global technology company. The adaptive approach (a)
measured the learning needs of participants and (b) effectiveness of learning methods, (c)
applied qualitative data to inform the design of initial and subsequent learning interventions
and (d) advanced the practice of progressive learning methods within the organization. The
results demonstrated significant positive impacts both in change readiness at an organizational
level and change engagement at an individual level.
Introduction:
Digital technologies have revolutionized societies, transforming the needs and expectations of learners,
especially those in the technology industry who invent, design, develop and deliver those technologies. Digital-
age consumers demand innovation, agility and customization from their products. In turn, employees of
technology companies demand these same characteristics from their learning function. Not only is this in the
form of what is learned, but also in terms of where, when and how learning occurs. Information today is
abundant, readily available, but often rapidly obsolete. Consequently, the role of a corporate Learning and
Development (L&D) function has transformed from content creator and lecturer to strategic business partner
that curates, measures, adapts and guides learning. At Samsung Electronics Co., ltd (hereafter, Samsung), our
L&D function plays a crucial role in ensuring that the organization is equipped with the technical, functional
and leadership skills required to succeed in the complex, dynamic and competitive business environment of
global technology. Our investments in L&D are considered and assessed like any other business resource.
Digital content delivery technologies (e.g., video, virtual reality, augmented reality), learning methods (e.g.,
blended learning, micro-learning, self-directed learning) and processes (e.g., assessment, evaluation,
customization) have enabled our L&D team to adapt to the learning needs of our employees and meet the
ultimate goal of driving business results.
One area of the learning function that is critical to Samsung is to facilitate the creation and
dissemination of our enterprise strategy in order to move the large global organization (over 300,000 employees
across 79 countries) quickly in one direction. The company relies on our L&D team to provide forums where
business leaders can share ideas, concerns and plans for the future. Each year, all corporate executives
participate in a seminar focused on identifying business needs and priorities, and finding ways to respond to
them. The outcomes of this seminar are consolidated into a unified set of strategies focused on the most pressing
business challenges. Then, L&D takes ownership of educating the entire workforce on these strategic priorities
through an internally-developed change leadership program.
In 2017, a company-wide organizational transformation was initiated to shift the job architecture
globally to job-based HR. While the transformation affected the career trajectory of our entire workforce, it
directly impacted the roles and responsibilities of mid-career employees, particularly in Korea due to the
country and company’s specific business culture. To effectively align (Armenakis & Harris, 2002) and upskill
our diverse stakeholders (Nathan, 2008), the change leadership program targeted three unique groups to address
their specific needs: (a) the Team Leader Course for all people managers in Korea below the executive level, (b)
the Self Leader Course for all individual contributors in Korea, and (c) the Global Change Leadership Course
for all global employees. The focus of this case study is on the adaptive learning strategy used in designing the
Team Leader Course.
Theoretical Background:
The most widely used definition of change readiness was developed by Armenakis, Harris, and Mossholder
(1993). They defined the concept as a combination of beliefs, attitudes and intentions of organizational members
regarding what change effort their organization needs and how they perceive the capability of the organization
to execute the needed change. Among many studies focusing on factors related to change readiness as a
predictor of the level of employee resistance to or support for change, this study opted for the widely cited
factors suggested by Holt et al (2007): change appropriateness (members believe the direction of change is
appropriate); management support (members feel management supports the change); self-efficacy (members
believe they have the capabilities to successfully implement the change); and personal valence (members
perceive the change to be personally beneficial).
Change engagement consists of change commitment, organizational members’ resolve to implement a
change, and change efficacy, the feeling of having the capabilities to implement the change. The most often
cited definition of commitment to organizational change is from Herscovitch and Meyer (2002): the drive or
attitude that pushes individuals to do what is necessary to successfully implement organizational change.
Change efficacy is the feeling of possessing the ability to effectively realize and manage the change. Conner &
Patterson (1982) emphasizes that without the sense of confidence about their capabilities, organizational
members would not be able to implement and manage changes.
Since micro-learning is still a relatively new concept, a comprehensive definition of it is yet to be
formed through academic consensus (Zhang & Ren, 2011). The most often cited definition of micro-learning is
from Hug (2005), which was also cited by Lindner & Bruck (2007): a learning approach designed to help
learners learn in the process of taking actions to solve problems and find and enjoy fun factors in the learning
content. According to Hug (2005), features of micro-learning include: 1) short duration 2) small learning units
(micro-content) 3) modular curriculum 4) episode-based activities 5) refreshing effect 6) mixed modality 7)
emphasis on repetition and reflection. The 2017 January issue of TD at Work describes micro-learning as a tool
to quickly respond to employee needs and to improve their learning satisfaction and sense of control. Micro-
learning was positively described also by Paul (2016) that it is effective for teaching new information based on
the pre-existing knowledge of learners and for solidifying what has been learned.
Methods and Results:
The Team Leader Course (TLC) targeted team leaders (n = 2,366) across a diversity of businesses and consumer
product lines. There were two phases to TLC, both of which used quantitative measurements to inform
subsequent interventions. In phase 1, we assessed the learning need and impact (i.e., change readiness at the
organizational and individual level) before design, and after completion of the course using the readiness-for-
change instrument developed by Holt, Armenakis, Field and Harris (2007). In phase 2, we harnessed the results
from the phase 1 post-course survey to develop customized follow-up content, and measured its learning impact
(i.e., change engagement on an individual level) based on a variation of the organizational readiness for
implementing change measure from Shea, Jacobs, Esserman, Bruce and Weiner (2014). Although the Shea et al.
study focused on the supra-individual level (e.g., team, department, or organization) and items were group-
referenced (e.g., ‘We are ready to…’), we focused on the individual level in order to measure personal readiness
(Bouckenooghe & Devos, 2007; Eby et al., 2000) rather than collective readiness. Items were changed to self-
reference (e.g., ‘I am ready to…’) and we call this measure change engagement.
Phase 1: Change Readiness
In order to gauge the initial change readiness of the target audience, randomly selected participants (n = 274)
were asked via online survey (see Table 1) 25 questions to identify if they (a) felt the change was appropriate
(appropriateness factor), (b) believed management supported the change (management support factor), (c) felt
capable of making the change successfully (self-efficacy factor), and (d) believed the change was personally
beneficial (personal valence factor) (Holt et al., 2007; Holt & Vardaman, 2013). All items used a seven-point
Likert scale (ranging from 1 = strongly disagree to 7 = strongly agree). The survey results uncovered that before
any learning intervention, managers ranked their personal valence highest, followed by change self-efficacy,
then appropriateness and management support lowest. Managers felt more positive about their individual change
readiness (i.e., personal valence and self-efficacy factors) than the organization’s (i.e., appropriateness and
management support factors). This may be due to survey respondents’ assumptions based on the company’s pre-
TLC communications, as well as the higher locus of control they felt in their own readiness versus the
organization’s readiness.
Table 1: t-test results for change readiness factors (n = 274, *p < 0.05, scale ranging from 1 = strongly disagree
to 7 = strongly agree)
Pre Post
Factor (No. of questions) t p
Mean SD Mean SD
Appropriateness (10)
e.g., I think the organization will
5.49 0.76 5.76 0.70 -6.95* 0.00
benefit from the change to job-
based HR.
Organizational
Management support (6)
e.g., Every senior manager has
5.17 1.02 5.38 1.08 -3.84* 0.00
stressed the importance of job-
based HR.
Self-efficacy (6)
e.g., I have the skills necessary
5.52 0.72 5.57 0.80 -1.51 0.13
to make the change to job-based
Individual HR work.
Personal valence (3)
e.g., My future in this job will be 5.60 1.03 5.62 1.08 -0.38 0.70
limited because of this change. ®
Equipped with the data generated through the first survey, curriculum designers developed a
customized 2-day course blending instructional methods and media, and hosted 17 sessions at our L&D campus.
An average of 139 people attended each session, who were then divided into two smaller groups for workshops
and activities. While the sessions were designed to improve all four factors, strongest emphasis was placed on
improving the management support factor because it was ranked the lowest on the survey. The first day was
dedicated to changes on the macro and organizational level, and the second day drilled down into the individual
level. Kicking off the course was a lecture-based lesson from our internal subject matter expert (SME) and
senior leader, Samsung’s Chief Human Resources Officer (CHRO), covering both the management support
factor as well as the appropriateness factor from an internal perspective. Following CHRO’s address was an
interactive workshop facilitated by an external SME to build on the appropriateness factor from a global
perspective. The workshop solidified the participants’ declarative knowledge (i.e., defining job-based HR,
reason for changing the job architecture of the organization) and elaborated on the implications of the change in
the context of participants’ day to day reality (i.e., expansion of leaders’ roles, potential challenges) using a
collaborative, inquiry-based approach. The second day was designed to increase the participants’ personal
valence factor and change self-efficacy factor by developing procedural knowledge (e.g., overcoming challenges,
finding opportunities, building a growth-oriented culture) and practicing skills (e.g., evaluation, feedback,
development) using experiential and action learning approaches.
After the 2-day course, the same participants were again given the ready-for-change survey online (see
Table 1), which revealed an increase in change readiness across all four factors, but only a statistically
significant increase on the appropriateness factor and management support factor. The good news was that, after
the in-person course, participants increasingly believed that the change was necessary and beneficial to the
organization and that organizational leaders were committed to the change. Unfortunately, on the individual
level, there was no significant increase in participants’ belief that the change would benefit them or that they had
the capabilities to successfully implement the change. This survey data, as well as informal qualitative feedback
provided during the course, informed the content, method and design of succeeding TLC learning interventions.
Phase 2: Change Engagement
In order to continuously reinforce the learning (ATD, 2017; Hug et al., 2005) from the 2-day course and address
the individual change readiness gap, course designers developed three 5-minute videos to engage and empower
managers to change on an individual level. Each video chunked an area of concern identified during phase 1,
most significantly developing the participants’ competencies to implement the change and less significantly on
gaining further commitment to the change (i.e., leaders fostering individual and team learning, viewing failure
as an opportunity for development and growth-promoting feedback). Over a duration of 21 days, in 10 day
intervals, emails were sent to all TLC participants (n = 2,366) encouraging – but not requiring – them to access
the successive micro-learning content on the learning management system (LMS), our internal online learning
portal. The LMS recorded viewing rates (i.e., the number of videos the participants watched) and, at the end of
the 21-day period, administered an additional online survey that measured two determinants of change
engagement: change commitment (i.e., resolve to implement a change) and change efficacy (i.e., capability to
implement a change) (Shea et al., 2014; Weiner, 2009; Herscovitch & Meyer, 2002). Participants were asked a
total of 9 questions, four measuring change commitment (e.g., I want to implement this change to job-based HR)
and five on change efficacy (e.g., I can coordinate tasks so that implementation of job-based HR goes smoothly).
For the same randomly selected survey participants from phase 1 (n = 274), the average viewing rate of
the three micro-learning content was 54% (i.e., 152 people, see Table 2). Although the viewing rates decreased
with each video, out of the 64% of participants (i.e., 174 people) who viewed the first video, 86% (i.e., 150
people) of them engaged with at least one other subsequent micro-learning content. This may suggest that those
who were self-driven to explore the first micro-learning content found the learning content sufficiently relevant
and/or valuable to continue engaging.
Table 2: micro-learning content viewership (n = 274, Note: Video 3 was inadvertently sent out before a major
national holiday, which is may have reduced viewership)
Video 1 Video 2 Video 3 Average
No. of viewers 174 154 127 152
% of total 64% 56% 46% 54%
Survey data showed a statistically significant increase in change engagement relative to viewing rates
(see Table 3). The more micro-learning content the participants watched, the higher they rated their overall
change engagement. Using the Scheffe post-hoc test, we confirmed that those who watched two videos showed
a higher level of change engagement than those who did not watch any videos, and that those who watched all
three reported a higher level of change engagement than those who engaged with one or none of the content.
However, there was no significant difference between viewing none and one or between one and two or two and
three viewings, respectively.
Table 3: ANOVA test on the relationship between micro-learning video viewership and change engagement
Viewing rate n Mean SD F p Post-hoc
None 85 5.26 1.01 2>0
Change 1 out of 3 33 5.37 1.17 3>0
8.71 0.00
engagement 2 out of 3 46 5.88 0.83 3>1
All 3 110 5.94 0.91 (Scheffe)
Furthermore, the more videos the participants watched, the smaller the gap between their commitment
and efficacy became (see Figure 1). For the 41% of participants (i.e., 111 people) who watched all three
contents, the self-perception of their capabilities to change surpassed their willingness to change. In addition to
watching all three videos, these highly engaged members expressed their continued interest through various
channels (e.g., repeated views, posting relevant questions to the online TLC participant community, requesting
permission to download videos).
Figure 1. Change factor impact of viewing rate.
As the survey results from phase 1 indicated and as course designers intended, the micro-learning
content focused more on developing participants’ change efficacy factor than their commitment factor. Even for
those who did not watch the micro-learning content, the change commitment factor was rather high (5.56),
which may suggest that the in-person course in phase 1 sufficiently developed the participants’ personal resolve
to implement the organizational changes. Although this study cannot prove causality, the measure used in phase
2 correlates the increase in change engagement to watching the micro-learning content.
Conclusion and implications:
Overall, leveraging technology and learning science research to quantitative measure learning needs, assess
effectiveness of learning interventions and adapt subsequent efforts based on those results was an informative
approach to increase the change readiness and engagement of TLC participants. In addition, leveraging micro-
learning content (Paul, 2016; Zhang, 2010), empowering participants to self-direct (Boyer et al., 2012) their on-
going learning and utilizing technology platforms that employees are familiar with likely enhanced the learning
experience and effectiveness of the course.
One opportunity identified by the success of the micro-learning content is attracting more learners to
engage with the content while fostering a self-directed learning culture. Additionally, a general limitation to
applying research to the corporate setting is the uncontrollable nature of our fast-paced, multifaceted business.
As with this case study, research informed the various inferences and directional insights (e.g., self-evaluation
was the appropriate quantitative measure, a blended learning environment with bite-size digital content for
reinforcement met the learning needs and preferences of the target participants), however many variables could
not be controlled to fully establish validity or repeatable reliability for future programs.
As advances in research and sophistication of technology improve data collection, mining and
application, it will be critical for L&D functions to integrate these innovations into the practice of talent
development. Capability enhancements (e.g., computer generated learning recommendations, automatically
capturing and analyzing learner data) to our internal LMS are already under way, which will increase the sample
sizes and provide more statistically significant results for future research-based activities. The insights from
these measures will continue to inform the content, method and process of the learning interventions at Samsung
as well as provide opportunities to offer “on the ground” evidence to the research community.
References
Armenakis, A. A., Harris, S. G., & Mossholder, K. W. (1993). Creating readiness for organizational change.
Human Relations, 46(6), 681-703.
Armenakis, A. A., & Harris, S. G. (2002). Crafting a change message to create transformational readiness.
Journal of Organizational Change Management, 15(2), 169-183.
Associate for Talent Development[ATD]. (2017). Microlearning: Delivering bite-sized knowledge. Atd press
Bouckenooghe, D., & Devos, G. (2007). The role of process, context and individual characteristics in
explaining readiness to change: a multilevel analysis (No. 2007-12). Vlerick Leuven Gent
Management School.
Boyer, S. L., Artis, A., Solomon, P., & Flemming, D. E. (2012). Improving sales performance with self-directed
learning. Marketing Management Journal 22, (22), 61-75.
Conner, D. R., & Patterson, R. W. (1982). Building commitment to organizational change. Training &
Development Journal.
Eby, L. T., Adams, D. M., Russell, J. E., & Gaby, S. H. (2000). Perceptions of organizational readiness for
change: Factors related to employees' reactions to the implementation of team-based selling. Human
Relations, 53(3), 419-442.
Herscovitch, L., & Meyer, J. P. (2002). Commitment to organizational change: extension of a three-component
model. Journal of Applied Psychology, 87(3), 474.
Holt, D. T., Armenakis, A. A., Feild, H. S., & Harris, S. G. (2007). Readiness for organizational change: The
systematic development of a scale. The Journal of Applied Behavioral Science, 43(2), 232-255.
Holt, D. T., & Vardaman, J. M. (2013). Toward a comprehensive understanding of readiness for change: The
case for an expanded conceptualization. Journal of Change Management, 13(1), 9-18.
Hug, T., Lindner, M., & Bruck, P. A. (2005). Microlearning: Emerging concepts, practices and technologies
after e-learning. Proceedings of Microlearning,5(3).
Nathan, E. P. (2008). Global organization and e-learning: Leveraging adult learning in different cultures.
Performance Improvement, 47(6).
Paul A. M. (2016). How to Make Microlearning Matter. HR Magazine. Retrieved from
https://www.shrm.org/hr-today/news/hr-magazine/0516/Pages/0516-microlearning.aspx
Shea, C. M., Jacobs, S. R., Esserman, D. A., Bruce, K., & Weiner, B. J. (2014). Organizational readiness for
implementing change: a psychometric assessment of a new measure. Implementation Science, 9(1), 7.
Zhang, H. F., Zhu, X. M., & Xia, X. R. (2010). Research on the application of integrated micro learning. In
Knowledge Acquisition and Modeling, 2010 3rd International Symposium (pp. 199-201). IEEE.
Zhang, X., & Ren, L. (2011). Design for application of micro learning to informal training in enterprise. In
Artificial Intelligence, Management Science and Electronic Commerce, 2011 2nd International
Conference (pp. 2024-2027). IEEE.