9
Lies About Learning Technology
Elliott Masie
Lies are everywhere when the conversation turns to learning technology. They are natural and, perhaps, unavoidable effects of the excitement and buzz around new technologies. Something new is invented or discovered, and we start to dream of innovation and improvement. But the lies go even deeper when it comes to learning technology.
The lies about learning technology have had some fascinating—and disastrous—effects. We’ve adopted immature technologies long before they are ready, often causing confusion and leading to disappointment over undelivered promises. We’ve implemented learning technologies before learning methods for using them have been developed, which leads to little or no impact. We’ve failed to test new technologies against current approaches, sometimes leaving the organization without any evidence of success (or failure). We’ve bought into overpriced and overstated new technologies; few learning products enter the market at an affordable level, and their value is often exaggerated.
We’ve fallen in love with buzzwords like “mobile learning” without there being models that work with today’s technologies. We’ve embraced technology-leveraged approaches, such as big learning data, without having the skills in the learning organization to fully understand or implement the changes identified through the data analysis. And we’ve created a usability void by showing rapid affection for technologies before systemically assessing their impact on users.
Many players in our changing field tell, retell, or at least tolerate these learning technology lies. Learning technology providers, IT departments, learning departments, learning magazines and analysts, and even users—they all lie about learning technology.
And for the record, I’m guilty of spreading some of these lies. I’ve spent more than 30 years covering the world of learning and technology, and my track record includes some amazing whoppers along the way. While I may have gotten it right when we first started to use “e-learning” in the mid-1990s to describe the application of the emerging Internet to computer-based training, I whiffed on my excitement over the impact of the virtual world of Second Life. I imagined classrooms across the world shifting into digital, animated meeting places. I even spent $60,000 on a Second Life MASIE Center and a digitally enhanced Elliott avatar. Yes, even I have told some big—but well-intentioned—lies along the way.
Affordance—A Key Phrase
The one term that could help frame our thinking about learning technology is “affordance.” It has been applied to design and technology, but it can also be adapted to learning technology. Affordance is the potential or actual ability of a technology to supply a designer, organization, or learner with an expanded skill in the learning process. It can be a powerful way to honor the flow of new technologies, while acknowledging that we may not yet know how they can enhance the learning process.
Using affordance as a framework can provide structure to how an organization approaches each new technology or learning technology methodology:
Designer affordance. How would this learning technology provide affordances in designing a learning activity? Would it help make the design faster, more agile, more adaptive, more reusable, more user friendly, or more shareable?
Organization affordance. How would this learning technology provide affordances to the organization in developing, delivering, assessing, and managing learning? Would it make learning management more responsive, less costly, more enterprise ready, more easily updatable, or more learner adaptive? Does it yield a benefit for the organization as a customer of the technology?
Learner affordance. How would this learning technology provide affordances to learners while they learn? Would it make the learning faster, easier, deeper, more rigorous, more supportive of performance, or more portable?
Affordances force us to ask deeper and more specific questions about how an exciting new or improved technology will affect designers, managers, learners, and other stakeholders in the learning process. Sure, the ads and articles about learning technologies describe improvements or enhancements. But excitement often overrides looking at the technologies from a critical affordance perspective. We must overcome our excitement in order to make wise business decisions about which learning technologies to invest in.
Let’s now examine the lies being told about new learning technologies, particularly smartphones, learning apps, our old models and new technologies, and massive open online courses (MOOCs).
Lie #1: Smartphones Will Radically Change Learning
On June 29, 2007, Apple introduced the iPhone, the first device that would allow users to move their fingers across a handheld screen to access information. This triggered many thoughts and fantasies among learning professionals of how smartphones could offer infinite affordances to radically change learning.
I fantasized about how the iPhone could be a personalized learning world—a handheld device for every worker that enabled content, performance support, collaboration, and more. And I predicted that all of this would be just a year or two away. I imagined an affordance and a timeline that did not resonate with reality.
I imagined the death of the laptop, because the iPhone fit easily in pockets and purses. One affordance that continues to evolve is the “phablet,” a combination between phone and tablet. I recalled the introduction and excitement around earlier handheld devices, including Newton, Slate, and Palm. But they didn’t easily apply to workplace technology because of technology, business, design, and even branding issues that slowed workplace adoption.
After I picked up my new iPhone on my way to deliver a speech at West Point, I passed it around to several military and police officers in attendance, asking them to imagine how it might be used. Dozens of ideas flowed about how a soldier or police officer might use it, including being able to deliver mobile courses easily and seamlessly to the iPhone. I left the speech thinking that the iPhone would radically change work and learning for the military and police—and soon.
Smartphones were no doubt radical innovations. But have they radically changed learning? That is still an open question wrapped up in some lies:
Smartphones have taken seven years to evolve, adding more functionality along the way, including cell-based Internet, two-sided cameras, GPS, and higher definition screens. Affordances have increased as each of these functions has been added.
Mobile learning was announced as the future of learning when smartphones were launched. I remember 12 press releases from companies debuting “world-changing” e-learning courses as mobile learning courses. Taking a course on a three-inch screen in nine-point type, with limited graphical ability and restricted input options, might be interesting, but it has been far from world changing.
Google searches by learners from their smartphones were missing from most of the early reports about mobile learning. It took time and increased bandwidth to harvest search as a key affordance.
Enterprise affordances from smartphones were blocked right from the start. Organizations were frustrated in their desire to allow secure access to workers within enterprise security frameworks.
BYOD (bring your own device) issues took years to address. At many organizations, workers have distinctly different access on their desktops compared with their smartphones, often requiring two searches on two devices to get a learning perspective from both internal and external knowledge sources.
Are mobile devices going to play a larger role in workplace learning? Of course. But technologies and methodologies take time to evolve, and our ability to envision and harvest the affordances for designers, managers, and learners requires experimentation, analysis, collaboration, benchmarking, and evidence. So allow me to summarize our experience with leveraging smartphones for workplace learning.
Smartphones:
were exciting from the start
had unlimited futures imagined
were announced as ready and fully able to provide learning affordances in 2007
experienced many learning innovation failures related to readiness and usability
appeared to be more useful at home than in the workplace
forced changes to enterprise security and business processes
evolved with time, reflection, and experience
may even be more exciting in 2015 than they were in 2007.
Lie #2: Learning Apps Are the Future for Workplace Learning
With the advent of smartphones came apps, which many learning professionals and organizations have promoted as the future for workplace learning. However, it remains to be seen whether this pronouncement about learning apps will eventually be more truth or lie.
The average smartphone user has downloaded some 40 apps, most of which were free or purchased for under $10 (Sawers 2012). These apps provide users affordances for travel, news monitoring, communication, gaming, hiring a car service, and much more. But what about apps for learning? There are translation apps for accessing literature and communication from global sources, note-storage apps that allow cutting and saving snippets from websites, and collaboration apps that allow real-time communication with teammates in other locations. Many of these are what I would call learning apps, in that they provide improved and expanded capabilities for learners in specific situations.
Yet, there are not many learning apps in the corporate marketplace. In 2014, I visited hundreds of booths at the Association for Talent Development’s International Conference & EXPO in Washington, D.C., looking for some low-priced-per-user learning apps. And while there were loads of $100,000–$10,000,000 learning systems, I couldn’t find a single $1.99 app that would help a learner acquire a new skill or develop a new competency.
Interestingly, learning apps have popped up in other learning fields:
K–12 education. Kahn Academy and TED Ed have offered apps and mobile access that provide affordances for teachers, by helping them create custom lessons, and learners, by allowing them to build and participate in communities around content.
Higher education. Companies are producing learning apps that provide affordances for college students (such as RescueTime and RefMe). Others are in the emerging MOOC space. (More about MOOCs later.)
Health and wellness. Weight Watchers has radically redesigned its services around online and mobile apps.
In reality, learning apps are just starting to emerge—with some hesitancy—in corporate learning. This may be for several reasons. They’re too cheap: Learning programs offered for free or very inexpensively represent a threat to the higher-priced content providers. They’re too open: Learning apps that provide more affordances to the learner, including using nontraditional resources, are perhaps somewhat threatening to highly controlled organizations. And they’re too new: Organizations don’t have good usability models for assessing their efficiency or effectiveness on workplace productivity or time to competency.
But the learning industry has a wonderful opportunity to experiment, benchmark, and explore innovation in the world of learning apps as well as other areas.
Lie #3: We Can Apply Our Old Models to the New Technologies
Another important lie about learning technology is that we immediately understand new technologies and can easily imagine the ways in which we can apply old models to new platforms. Yet that instant analysis may not yield real innovation.
Think back to when webinar technology emerged. In the mid-1990s, the speed and functionality of webinar platforms, most of which were still in beta, was exciting—and yet limited. The first webinar affordances to develop were about replicating lecture- and classroom-based PowerPoint delivery to learners in distributed locations. In other words, the affordances were distributing lectures to a wider audience and not having to travel. Not exactly groundbreaking.
As is often the case with new technologies, we take our models from the previous technology and apply them to the new one—television was radio with a picture for many years. But as learning technologies evolve, there is a window for exploring new and different affordances for designers, organizations, and learners. Webinar tools today provide for more video, interaction windows, and engagement capabilities, but most webinars are far from engaging for learners, and many are still real-time lectures with the occasional opportunity for audience participation. The lie is thus not in the learning technology tool, but in our slowness to discover and experiment with new affordances for design and delivery. As a result, webinars are the fastest growing element of technology-based learning delivery, but which also allow for the highest levels of learner multitasking and distraction.
The lies about learning technology do not come just from technology providers—they also come from our own self-limiting design perspectives. Learners themselves are redesigning many of our webinars by participating while simultaneously working on other tasks (and eating lunch) or by not showing up at all (many webinars have a no-show rate as high as 40 percent of preregistered learners). Learners are adapting for their own affordances. Perhaps managers and designers need to take a fresh, evidence-based look at webinars to discover new design and delivery models with increased affordances for everyone.
Affordances are really in the mind of the beholder. Each player in the learning world sees a technology from his own perspective, with his own affordances. We often don’t apply an industry-wide perspective to learning technology. The learner may view it as a personalization tool, the designer may view it as a depth and alignment tool, and the manager may view it as a cost-avoidance tool.
Our learners are agile. In fact, they are more agile than most learning designers and managers. To keep up, we need to create an evidence-based, usability-rich approach for exploring each new learning technology, rather than continuing to apply our old, often-out-of-date approaches.
Lie #4: MOOCs Can Be Easily Translated From Higher Education to the Workplace
Beware of some of the new acronyms coming our way in learning technology. Several letters forming a cute new term, like MOOC, often reflect a new technology or a new learning methodology that has hit a level of shared curiosity. We need to be both curious and smart.
MOOCs are high on my radar at the moment—four letters, each exploring an affordance or extension of learning design and delivery:
M—Massive. These programs allow for access to hundreds, thousands, or even hundreds of thousands of learners, without radically expanding the number of teachers or coaches.
O—Open. These programs use open content, where much of the material comes from external and often free sites like TED and YouTube, and offer open access, where learners of all types can enroll. For example, a leadership program open to all employees, not just those who are currently, or expected to become, managers.
O—Online. These programs facilitate learning primarily through online content, context, collaboration, and assessment. The learner can access a MOOC from anywhere, anytime, and with personalized scheduling.
C—Course, community, credit, collaboration, or certification. These programs can serve a variety of different purposes for learners, whether it is acquiring credits for a degree or earning a certificate to widen their knowledge base.
MOOCs are new. They’re popular with many in higher education. They’re presented as a disruptive force in learning. And they’re perceived as a technology for learning innovators to watch. But there is confusion in translating them from higher education to the workplace. While colleges see MOOCs as not only open-access courses, but also pathways to awarding academic credits, many employers see them more as focused on providing a community of content or leading to a badge or certification.
So how should learning directors and professionals approach MOOCs for the corporate workplace? First, a few lies that you will hear about MOOCs:
They work great (tens of thousands take a program with limited costs and faculty time). Or they don’t work (80 percent of participants never complete them).
They can be purchased for employees from branded universities at a relatively low cost.
They are highly attractive to workers, who can learn based on their own needs and schedules.
They are very collaborative; learners help one another in online communities. Or they are not collaborative, because online community designs are not scalable without leaders and facilitators.
They are the future of learning technology. Or they are just a hot item.
In many ways, each of these items isn’t a lie, but rather just a slice of the MOOC conversation. MOOCs are, thus, a great example of how learning leaders and organizations should rise above the hype.
To do this, I recommend that learning professionals learn more about learning and MOOCs. They should take a few MOOCs from colleges, for-profit businesses, and other sources. Find out what works and what doesn’t from a learner’s perspective.
They should deconstruct the acronym and ask if they can implement a stretched version of a single letter, without the full MOOC. Is there a way to add open content to existing face-to-face and e-learning programs? Is there a way to take a program from small to massive?
They should look at MOOCs not just as the impetus for new learning assets, but also as a trigger for reducing or ending some current offerings. If MOOCs work, what can learning organizations stop delivering? If MOOCs work, what can designers stop designing?
And they should evaluate usability and listen to their audience—the learners. Some learners may enjoy MOOCs that are structured like a multiweek class, building toward a final at the end. But others may want to have all the sessions ready for them to take at their own pace, perhaps even in one gigantic weekend MOOC marathon. How do learners evolve or shift their learning behaviors in a MOOC?
So, take that term MOOC, along with all its excitement, and explore it for workplace affordances. Beware the supplier who tells you that they have it solved and are the “leading number one creator of MOOCs, with 72 percent of the Fortune 500 as customers.” Some of that might be true, but you want to partner with explorers and evidence-based designers for this process. I still don’t know the answer, for example, to these questions:
If 3,000 people sign up for a MOOC and only 300 finish, are the other 2,700 failing, or are they getting just enough of what they want? Some would argue that a MOOC is like an article in USA Today, where some will read just the headline, others the first paragraph, still others the whole article, and some will go online for even more depth.
Are MOOCs about completion or learner-directed participation?
And I’m sure that I don’t know the answers to several other questions, which I also don’t yet know.
Learning leaders need to embrace the excitement behind MOOCs and explore what workplace affordances they may provide. But they need to acknowledge that different organizations require different affordances—that there is no one-size-fits-all model. Don’t be afraid to deconstruct the acronym and apply the letters you need to your workplace learning.
More Lies About Learning Technology
The conversation around the lies about learning technology could go on for days and fill its own book. So let’s quickly review some other important learning technologies in the corporate learning field and the lies surrounding them.
Video. More web activity means that learners are consuming more learning materials through short videos, and learning leaders are designing more courses with video content. And more content is flowing from user-created videos. But most learning systems are not ready or cannot adapt to video content. Many organizations have to place their videos outside their learning management systems and are unable to collect critical data, such as at what point do users close out of a video. Learning technology providers must rapidly accept the growth of video and provide better tools and systems to organizations.
Search. Learners want to search for answers. They want to search content in the wide reaches of the organization, even for older PowerPoints that might just be on a co-worker’s laptop. One of the lies from IT is that they are providing the search capabilities that learners need.
Big learning data. There is a big appetite for big data in the learning world, based on high-level executives’ ever-increasing interest in analytics. Beware of big learning data. (I say this even though I authored the ATD book on the topic.) The caution is to not fall for a lightweight view of a very deep topic. In many ways, big learning data is a learning technology that can provide affordances for designers, managers, and learners. Do some research and then sit with learning professionals in other organizations to figure out which aspects of big learning data can be leveraged now and which may be available downstream. And be sure to keep the learner as one of the top customers for big data.
Application programming interfaces (APIs) and interactivity. Some day learning technologies will just work together, when colleagues can participate in a meeting through Skype, WebEx, Telepresence, and FaceTime, along with a few by phone. These technologies should work together. It gets even more frustrating if an organization wants to integrate multiple technologies, especially when suppliers say that it is all possible. What learning leaders need are APIs that allow for the low-cost integration and connectivity of multiple learning technologies.
BYOD. Organizations and technology providers, including mobile and cell companies, need to find ways for workers to use privately owned devices in more secure and corporately comfortable ways. Imagine having a button on a smart device that flips the use from home to work through, for example, a GPS location allowing for at-work access.
Conclusion
I’d like to advocate for the creation of a public list of “we were wrong” statements. Innovation requires that we fail our way to success. Many of us will make pronouncements about learning technology that will become lies only through the passage of time and experimentation. I was wrong about Second Life. I was wrong about the speed of laptop demise. And I’m sure I was wrong about many other learning technologies. Let’s do a better job of conducting and sharing our predictions and statements about learning technology—the good and the bad.
Some Future Learning Technologies
Here are five learning technologies that I am experimenting with as well as seeking the affordances they may provide:
Drones. My four-blade helicopter drone has a GoPro high-definition camera that takes amazing video from hundreds of feet above the ground. I am seeking affordances for how it might be used for insurance inspector training or other applications.
Wearables. I have my Google Glass, Nike Band, and smartwatches. I bet these devices and other wearables could yield some incredible affordances for learners—perhaps not yet, but they are intriguing and deserve experimentation.
Neuroscience sensors. We are exploring the role that neuroscience sensors might play by providing feedback on brain scans and the physical reactions of learners to new content.
Crowd-sourced design. Imagine harnessing 100 colleagues from around the enterprise to do a rapid, crowd-sourced design of a learning activity.
Multilanguage webinar. When learners from five countries, all of whom speak different languages, are on a webinar together, how does language translation provide an affordance?
Will any of these technologies and methodologies provide real affordances to designers, managers, and learners? Time and experimentation will tell. I am excited about each one, but I will try to contain my excitement. Time to be a bit more careful with lies about learning technology.
Reference
Sawers, P. 2012. “Nielsen: US Smartphones Have an Average of 41 Apps Installed, Up From 32 Last Year.” The Next Web, May 12. http://thenextweb.com/insider/2012/05/16/nielsen-us-smartphones-have-an-average-of-41-apps-installed-up-from-32-last-year.