21 November 2017
Søren Blem Bach, Senior Consultant at Mannaz and David Pontoppidan
As companies and organisations try to adjust to a changing concept of careers lasting up to 60 years, meet the rapidly accelerating need to acquire new knowledge, and build the capacity to face exponential technological change, learning technology is also changing radically to keep up with demand.
But new technology in itself will not solve the overarching problem that is puzzling executives and HR departments alike: How do we efficiently scale knowledge and training while retaining impact?
Until now, a pure reliance on e-learning has not solved the puzzle of creating sustainable learning experiences, which are anchored in participants and applied continuously with excellence after a training is complete.
Originally, e-learning was seen as a sort of deus ex machina solution. The seemingly unsolvble problem of scaling impactful learning across borders and time zones, without an explosion in cost, was suddenly resolved by the intervention of learning technologies.
However, any miraculous solution to the problem is still outstanding. While technological developments has given us the capability to scale, most learners agree that the impact is just not the same as sitting in a classroom.
Why is it that technology, which has liberated so many people and made our life so much easier in other aspects, has yet to crack the code on delivering learning with sustainable impact? In this article we outline why most digital learning propositions so far have fallen short in delivering the desired outcome, and present our belief in the future of sustainable digital learning.
For a very long time, learning technologies have solely approached the concept of learning as an acquisition of knowledge by participants. Size and variety of the knowledge offered have been the primary drivers of value, as learners on a global scale have clicked through a vast array of online courses and built capabilities from A-Z by being exposed to bulk learning at wholesale prices.
However, much like you do not become an athlete by going to the gym once a week, you do not learn a complex topic by sitting in front of your screen for a brief period of time. Humans cannot simply download a new piece of knowledge and install it into their biological hardware. This transfer of new knowledge and behaviours to your own context does by no means happen automatically.
In fact, much research points to learning as also being a participatory process, rather than only a process of acquisition. While learning-as-acquisition is primarily focused on the subjective consciousness and the learning elements it acquires, learning-as-participation focuses on the actual learning and the relation that is developed between the individual and others (Sfard, 1998).
At ViSiR we believe that in order to crack the code of digital learning, and train for long-term impact, the learning delivered needs to be based on participation as well. We simply cannot rely on the acquisition metaphor alone. This is unfortunately the case for much of traditional e-learning that is mistakenly believed to shape new behaviours automatically.
Perhaps surprisingly, there is not much research available that discusses the disadvantages of traditional e-learning and why we typically forget the things, we learn in this context. Little attention has been paid to really understand how we create a lasting impact through online learning (Islam, 2015; El-Seoud et. al, 2014).
More than 60 years ago, Benjamin Bloom presented a taxonomy that has since become a foundation for the educational community in how learning is approached. According to Bloom, there are multiple stages of learning. We progress from acquiring knowledge to comprehending it, applying it, evaluating it, and finally creating new things based on this knowledge. The lowest level of Bloom’s taxonomy is reached through the actual learning assets – books, lectures, videos and so forth. In order to reach higher levels of learning, however, collaboration, games, and mentoring are needed in an interactive and engaging format.
The problem with e-learning has been that the modules rarely move beyond a data dump of knowledge on students who are assumed to be blank slates or empty hard drives, where you can upload knowledge and then test for the success in comprehension immediately afterwards. In other words, traditional e-learning trains people to primarily acquire knowledge and reach a basic level of knowledge. It does not help them to develop an understanding and comprehension of what to do with that knowledge. Traditional e-learning thereby fails to incorporate what Bloom and his colleagues already realised about the levels of learning some 60 years ago.
Figure 1: There are multiple steps in learning that require different methods, modalities, and approaches to go progress the lowest level of understanding to the highest level of mastery.
The effect of traditional e-learning is, at best, questionable. We are now globally starting to see that the belief in the return on investment from e-learning is fading. In 2016, global revenues for self-paced e-learning reached $46.6 billion (Ambient Insight, 2016), a stagnant development from $46.9 billion in 2015. By 2021, worldwide revenues for e-learning are expecting to decrease to $33.4 billion (Ambient Insight, 2016). To support the theory about a decreasing confidence in traditional e-learning, we see that the negative growth rate is especially present in countries that currently have some of the highest spends on e-learning.
In order to design sustainable learning experiences you need to carefully consider both the format, the context where the learning should take place and perhaps most importantly the people who are learning for mastery. Learning is not a destination. It is a journey.
We believe that future sustainable digital learning should focus on social, collaborative and interactional elements. Learning as acquisition and learning as participation are not mutually exclusive approaches to learning. At ViSiR we believe it should always be a mix to ensure that we learn for mastery and get coaching and support just in time. We need the right help and flexibility to link new knowledge and behaviours to our own context. Otherwise, we risk learning just for the sake of acquiring knowledge briefly and meeting compliance requirements.
The Ebbinghaus Forgetting Curve tells us that up to 90% of everything we learn can be lost within a week after we have learned it. In order to combat this loss of knowledge, you need to reinforce it continuously – and this is where traditional e-learning often falls short.
We believe that the lasting impact comes when digital learning is anchored in your daily life in your own context. It should be available in an interactive format that allows you to customize and collaborate your way to potential solutions and new behaviours. This is by no means only possible in face-to-face situations. We believe that this could just a well happen through digital and virtual learning designed for impact.
Figure 2: Up to 90% of learned content is forgotten within a week. Contrary to e-learning, we propose specific methods to anchor the learning experience and build a sustainable path for learning retention.
There seems to be a tendency to use e-learning, virtual learning, digital learning and blended learning almost synonymously. In our opinion, this is a big mistake and part of the reason why digital learning often fails.
In our opinion, it makes sense to distinguish among four different types of learning that involve technology:
Built on the assumptions that individuals can sustainably acquire knowledge by clicking their way through a fixed monologue online. A large amount of content is presented to you over the course of several lessons, either in written form or as a spoken monologue. Some mild form of engagement is mimicked by simple tests such as clicking and dragging boxes from one place to another. When you have clicked through a fixed number of modules you reach the final test, to see if you paid attention to the one-way lecture. More than often, feedback is limited to the accuracy of your final result – not the process through which you reached your answers.
Online, interactive learning facilitated by technology. It is typically built and customized over several learning modules. The modules are personalized based on mastery level, a flexibility in learning styles and motivation. The digital learning environment uses multiple learning instruments, that allows for instant interaction, questions and group reflections. All of the modules are designed to create engagement, interaction and a lasting impact that can be transferred to their everyday context. Analytics, gamification and coaching and mentoring could be core elements.
Much like the digital learning approach in terms of flexibility and opportunities to personalize the learning journey. The virtual learning approach furthermore has live classroom sessions happening real time, whereas digital learning has recorded sessions, where the facilitators are trained in facilitating in a dynamic way where they take into consideration the questions the group would typically ask.
Online learning (virtual and digital) supported by traditional classroom meetings and or other opportunities to train new approaches and behaviours back in the organisation.
Rather than seeing these elements as competing and mutually exclusive components, why not see them as modules that can be combined to create engaging digital learning journeys? The elements mentioned above should always be critically evaluated to decide which combination of the elements are most suited for the successful transfer of the new behaviours you are trying to implement.
Figure 3: We distinguish between four different ways of applying technology in learning that can be combined in modular learning journeys.
In the midst of discussions about e-learning, face-to-face or digital learning, we can take some comfort in knowing that the basics of learning are still to a large extend the same in all the settings. The tools you use and the way you facilitate the learning journey will, however, have great impact on the learning experience and the sustainability of it. It is important that we understand the basics of learning and how this could be approached. This includes a number of elements that we believe will be key in future of digital learning. The first element we need to consider is the 70:20:10 principle that applies to all kinds of sustainable learning.
Figure 4: Where traditional e-learning disregards 90% of successful learning and development, we suggest applying use of technology to support both learning through informal exposure and learning on the job.
The 70:20:10 principle tells us that only 10% of the elements that leaders contribute to their successful learning and development come from coursework and training (Lombardo & Eichinger, 1996). The last 90% of successful learning and development is typically disregarded in traditional e-learning. Lombardo & Eichinger (1996) found that 20% of this was due to developmental relationships and the last 70% was – and still is, due to challenging assignments that give you opportunities to practice the new skills and behaviours. If we link this back to Sfard’s writings about learning as acquisition and participation, it shows us, that neither learning metaphor will provide optimal results on its own.
Many e-learning modules are great for giving huge amounts of facts, but the approach is too closed and lacks flexibility if it is to provide sustainable learning that goes beyond the 10% from coursework and training. The traditional modules are great for compliance, but if they are not meaningful the chance of people remembering the details a few weeks on, is close to none. This is why we believe future digital learning should always remember to focus on relevant assignments and developmental relationships.
This shift in focus is also a shift towards an employee-centric learning approach that follows Blooms taxonomy. In this approach, individuals should be able to access and “pull” online learning just-in-time. This should be at their own pace, where they get personalised coaching and advice on how to use the knowledge going forward. This requires dynamic and flexible learning approaches, both in terms of technology, but most importantly also in terms of a design mind-set that allows for self-directed learning that gives you unique learning experiences that transcends the learning platform.
Technology can help facilitate the learning journey as it also allows us to screen the learners’ level of mastery and motivation before and after their learning experience. Much too often the online learners are exposed to an overwhelming amount of learning journeys they can access. Even though we see that many organisations are starting to shift towards this more employee-centric learning approach, many learning and development organizations still report that they are struggling with internally focused and outdated platforms with static learning approaches (Deloitte, 2016). These kinds of platforms typically do not pay sufficient attention to the employee’s current level of mastery and motivation. Changing this is a simple pedagogical element that could have a huge impact on the motivation of the learner.
The importance of people analytics. The intelligent use of technology and analytics allows us to pre-assess the learners’ mastery level and design the learning journey that fits them both in terms of learning style, motivation and pace. The assessment should also take into consideration the learner’s existing ability to learn online. In other words, first we must become able to learn how to learn online and know what kind of opportunities as well as challenges this carries for us personally.
This also includes getting advice on how to obtain the learning experiences you need. This could be learning from both inside and outside the company and hence the company must be ready to support and allow employees to seek the needed learning support and potentially also connect with “outside” networks of other learners who are in a similar position. This flexibility and openness could increase the likelihood of succeeding with the last 90% of the learning potential.
When used correctly there is also a huge potential in using analytics from the online learning process. Currently there is an increasing demand for people analytics that can help clarify what drives organizational results (Deloitte, 2017). Consequently, the employee learning infrastructure must be able to handle relevant data, both for the sake of the individual learner, but also to help the organization make sense of all of the hidden potential in the data. Just like the personalized learning paths should allow for flexibility and just-in-time learning, analytics should also provide the organization with just-in-time data. All of this data could, in part, be produced by the numerous individual and personalized learning paths. The data must be used proactively to see how the competencies, behaviours, motivation and skills look like across the entire organization. Does this match the organizations expectations and how could people analytics be used to inform the strategic direction?
The analytics could be used in multiple ways, including to create an overview of the support the learner could be able to get internally in the organization. It is important to keep in mind that learning is no longer just the formal training, but very much an ongoing experience, where the entire environment in the organization is supporting the journey. Furthermore, the analytics could also be used to create an overview of whether there is a need for a greater cognitive diversity to stimulate the learning environment.
This flexibility together with the opportunity to personalize interaction and get timely feedback is core in ViSiR. We allow for a high degree of self-directed learning. In traditional e-learning there is often the danger that we get too preoccupied with technology and forget about the diversity of the people who are attending the programmes. Technology should never become the key topic and make us forget about the people in the room (be it virtual or physical). What is their motivation to learn new behaviours and how could this be supported throughout the journey through the intelligent use of analytics? Technology should support and facilitate the learning. It should never become an end in itself.
It is obvious that the digital learning puzzle is still not coming together after so many years. We strongly believe it is time to come up with new flexible and sophisticated pieces if we are to create a sustainable, and long-lasting impact of digital learning.
Ambient Insight
Bersin, J.
(2017, March 28) Watch Out, Corporate Learning: Here Comes Disruption. Retrieved from: https://www.forbes.com/sites/joshbersin/2017/03/28/watch-out-corporate-learning-here-comes-disruption/#746f42ebdc59
Deloitte
(2016) Global Human Capital Trends 2016: The New Organization – Different by Design by Deloitte University Press. https://www2.deloitte.com/content/dam/Deloitte/global/Documents/HumanCapital/gx-dup-global-human-capital-trends-2016.pdf
Deloitte
(2017) Rewriting the rules for the digital age. 2017 Deloitte Global Human Capital Trends https://www2.deloitte.com/content/dam/Deloitte/global/Documents/HumanCapital/hc-2017-global-human-capital-trends-gx.pdf
El-Seoud, S., Taj-Eddin, I., Seddiek, N., Ghenghesh, P. El-Khouly, M.
(2014). The Impact of E-Learning on Egyptian Higher Education and its Effect on Learner’s Motivation: A Case Study. In: Computer Science and Information Technology, 2 , 179 – 187. DOI: 10.13189/csit.2014.020307.
Islam, N., Beer, M., Slack, F.
(2015) E-Learning Challenges Faced by Academics in Higher Education: A Literature Review. Journal of Education and Training Studies Vol. 3, No. 5; September 2015, 102-112. https://www.researchgate.net/publication/281767697_E-Learning_Challenges_Faced_by_Academics_in_Higher_Education_A_Literature_Review
Lombardo, M., Eichinger, R.W.
(1996). The Career Architect Development Planner (1st ed.). Minneapolis: Lominger.
Sfard, A.
(1998). On Two Metaphors for Learning and the Dangers of Choosing Just One. In: Educational Researcher, Vol. 27, No. 2 (Mar., 1998) pp. 4-13
