10

Lies About Learning Pronouncements

Larry Israelite

I started my career in the field of learning and development in the early 1980s, working for a company that produced a high-end computer-based training system. At the time, we were one of several commercial enterprises that spawned from considerable investments in advanced research and development funded by the National Science Foundation and the military. The goal was to use computer technology to supplement (replace) classroom instruction.

Even in those days there was plenty of hype about the potential for computer-based training. Articles were written, papers were presented, and pronouncements were made—computer-based training will revolutionize classroom learning as we know it. Sound familiar?

This phenomenon didn’t start in the early 1980s. In fact, I recall something that occurred in the mid-1960s that predicted the experience I had almost 20 years later. I arrived on my first day of ninth grade only to find televisions hanging in every classroom. Instructional television was going to revolutionize public education as we knew it. But as it turned out, programming was complicated to produce and expensive to purchase, and teachers who were effective in the classroom weren’t so much on television. It didn’t take long to figure out that instructional television could be useful in some circumstances but that it wasn’t going to revolutionize learning.

To distill this issue down to its very essence, I would say we are suckers for a good pronouncement. They sound good, they give us hope, they are often made by people or institutions we respect, and they are hard to resist. But they also sometimes lead us to do things we later regret.

While going through some old files, I found a diagram I created in 1982. It shows what I described then as “the cycle of failure,” our all too common experience when we accept pronouncements without proper evaluation (Figure 10-1). To draw it again today, the words might change slightly, but the sentiment would be the same. And I find it both amusing and disheartening that not much has changed in the intervening years. We still tend to invest (emotionally and financially) in approaches, methods, technologies, and tools that don’t deliver the value they claim. We then live with the consequences of our misplaced confidence and enthusiasm and start all over again.

Figure 10-1. The Cycle of Failure

In this chapter, I will explore some pronouncements about learning that have had a major influence on the field of learning and development. What do I mean by pronouncement? For starters, it’s a formal or authoritative announcement or declaration. But I’d like to add that a pronouncement is made by someone who is in a position of respect and authority or who exudes a high degree of confidence in what he is saying. My goal is to make explicit some of the more interesting “truths” we’ve heard in the past—and, in turn, to change how we respond to these in the future.

Pronouncement #1: E-Learning Will Revolutionize Training and Replace Classroom Education

As early as the mid-1980s, people started to predict the end of the classroom or, at least, to imagine a vastly different learning landscape. First, it was computer-based training or computer-assisted instruction. This was followed by interactive video (12-inch disc), multimedia CD-ROMs, videoconference technology, and the Internet. Many people were convinced that the Internet, with all its wonderful features and capabilities, would enable e-learning to replace the classroom experience. Bricks-and-mortar classrooms and training centers would become a thing of the past.

Before the availability of web-based video, people relied heavily on the virtual classroom. This technology, now available at almost no cost from hundreds of cloud vendors, allows learners to see instructors and watch their material in real time. This was just as good as being in a classroom—at least in theory.

At that time, we ignored the fact that much of the learning that takes place in a classroom involves interaction with other learners. So the early online virtual learning programs started to use discussion rooms and other tools to bring students together. Many even created breakout rooms where people could go to study or practice.

This virtual model still works pretty well. But it can’t replace being together in the same space. And it seems the more technology we have, the more we crave to put it away, just sit down, and talk with one another. We have a certain ability to connect and interact face to face, which technology can’t fully replicate. So even great video classrooms can’t replace the need for classroom experiences. Note how Deloitte, McDonald’s, GE, Unilever, and many other major corporations have recently built beautiful (bricks-and-mortar) corporate universities exactly for this reason.

While training continues to move online (today more than 30 percent of all corporate instructor hours are spent online; Bersin by Deloitte 2014), more than 50 percent of training is still spent in real classrooms, face-to-face with students. Clearly, the physical classroom remains a very important element of learning.

Each year will bring new and seemingly tradition-shattering learning technologies—tools that are more expressive (Google Hangouts, for example). But classrooms aren’t going anywhere anytime soon. Sure, what we do in classrooms may change (such as the flipped classroom), but we will still need classrooms with live real-time teachers for years to come. It turns out that we just like to spend time with one another, occupying the same space, interacting in real time, and being able to reach out and touch someone.

All of this said, it appears that technical training—meaning training consumed by software developers, IT administrators, and creative professionals—may have reached the tipping point with regard to replacing classroom learning with e-learning. There are, literally, tens of thousands of very high-quality programs available that cover an almost endless array of topics. The fact that most of these programs are highly modularized, which enables users to focus only on topics that interest them or will be useful for them, only serves to increase the popularity of this learning alternative. And perhaps more important, these programs are available directly to learners, completely eliminating enterprise control and oversight. As a result, surveys like the one just referenced may not capture this significant shift in approach. So, while it may, in fact, be true that e-learning really is revolutionizing training and replacing classroom education for technical subjects, it also is true that we have a very long and complex row to hoe when considering other content domains.

Pronouncement #2: Gamification Will Radically Change Corporate Learning

Learning leaders have also made many pronouncements about gamification in recent years, particularly about how it will radically change corporate learning. Remember Second Life? Many companies invested in this technology believing that our entire learning experience would turn into a game. And while gamification has become a crucial part of our online experience, the suggestion that learning as a game will transform learning has proved false. Instead, gamification has morphed into features and practices (affordances) embedded into many Internet applications.

Consider how gamification features now appear in social networks like Facebook, LinkedIn, and Twitter. Most other providers of apps and tools give people points, social cues, personal profiles, quests, reminders, and other forms of gaming that help hook people on their applications. Gamification is, truly, ubiquitous.

In learning, games and gaming are nothing new. Many of our earliest learning experiences involve receiving rewards for completing lessons or gold stars for perfect attendance. A gold star isn’t that much different from the badge you receive when you post to a social collaboration site or complete a learning module. And even the slider bar that shows progress or points received for completing a section of an online course qualifies as gamification. In classrooms, we have used games for as long as I can remember—to engage, motivate, and stimulate learners.

Gamification can play a meaningful role in learning. But we should treat it the same as we treat other instructional techniques intended to improve effectiveness. Games are tools in the instructional designer toolkit, not the toolkit itself. So learning and development professionals need to remember to use them appropriately.

But there is a dark side to the proliferation of gamification. Take LinkedIn, for example. My profile page lists the skills for which I’ve been endorsed and shows little pictures of the contacts whose endorsements I’ve received. That’s all very nice. Except for the fact that I have not met or ever worked with many of my endorsers, so they are in no position to fairly judge my capabilities. In the end, I’m largely suspicious of the endorsements other people receive, thus diminishing them as a recruiting tool. So I am forced to ask, “Does this process have any value?”

Pronouncement #3: Mobile Learning Will Replace [Insert Other Forms of Learning Here]

I can’t tell you how many times I have heard people say that they need to deliver their content through mobile devices. For many years that was both impossible and ill advised. Before smartphones and tablets, mobile devices were completely ill equipped for high-fidelity learning. Sure, learners could scroll through some text, attempt to look at very small graphics, listen to some audio files, and answer a few questions, but that was about it. Mobile learning was nothing more than a pipe dream.

But the iPhone, the iPad, and the Android operating system have dramatically changed the mobile environment. People of all ages spend hours on their mobile devices, finding information by searching on Google, browsing YouTube, or downloading any of the hundreds of apps and tools with content-designed specifically for mobile. And, of course, learning occurs.

There were two lies associated with the pronouncement about mobile learning. The first pronouncement was made far too early, long before the technology could actually deliver the well-designed, highly engaging experiences possible today. In 2015, most suppliers develop their programs so they run on all devices—desktop and mobile. And since we now spend 60 percent of our online time on a mobile platform (Lipsman 2014), it is clear that mobile has arrived.

The second lie involves what has almost become a learning anathema—the word “replace.” During the past 33 years, no new learning technology that I am aware of has ever fully replaced another. So while mobile learning will undoubtedly play a large role in learning, it likely won’t replace anything either, in the same way that e-learning never fully replaced classroom learning, pundit pronouncements notwithstanding. And we run the risk that, given the hype about mobile, designers will feel pressured to deliver solutions on mobile devices that have no business being there.

In the end, mobile has taken its rightful and, perhaps, long overdue place in the instructional designer toolkit. And ongoing advances in technology are likely to increase its importance as the tool of choice for addressing specific learning needs. But mobile won’t be replacing anything—at least from a learning perspective—anytime soon.

Pronouncement #4: Learning and Development Strategy Should Be Based on the 70-20-10 Model

People love simple models. And for better or worse the 70-20-10 model has captured the imagination of talent management professionals everywhere. The ratio suggests that people learn 70 percent from experience, 20 percent from other people, and 10 percent from formal training. And this model does have some validity. It makes sense that doing things results in more learning than talking about, hearing about, or reading about them does. But as near as I can tell, there is little sound empirical evidence backing up the ratio.

The real value of the model is that it depicts a comprehensive example of blended learning, a phrase that has been part of the learning vernacular since the turn of the century. Originally, blended learning described a program of both individual and group learning. For example, it included one or more e-learning modules and some form of classroom experience (live or virtual). Some of the programs designed this way were quite effective, but others were not.

The 70-20-10 model pushes the blended concept even further. Suppose a blended program included a formal learning component that was followed by specific on-the-job assignments, during which learners attempted to apply what they had learned. Then suppose we add a series of structured conversations with managers and peers about how they see the learners applying their new skills. Without over-engineering the exact time allocation, you can imagine something that approximates the 70-20-10 structure.

Within the 70-20-10 model, learning leaders often forget to account for reflection, even though research has concluded that it is critical to learning (Di Stefano et al. 2014). Learning from direct experience can be more effective if coupled with reflection—that is, attempting to synthesize, abstract, and articulate the key lessons taught by experience. And reflection builds one’s self-efficacy, which in turn translates into higher rates of learning. So just having an experience doesn’t mean that you will learn all you can from it unless you also reflect on it. And that is more difficult than it might seem.

When we apply 70-20-10 as a rule—when it drives strategic decisions, including staffing and budgets—it can force us to abandon those things that have proved necessary for learning to occur: motivated learners, an environment conducive to learning, relevant content, well-designed instruction, meaningful practice, and opportunities to reflect. And, simply, no good can come from that.

Pronouncement #5: Search-Enabled “Fingertip Learning” Will Replace More Traditional Forms of Learning

Search is a marvelous invention. Not a day goes by during which I don’t conduct at least a dozen Internet searches for all kinds of information. Many searches are for work, some are for pleasure, and some are for the information I need to run my life (such as, is my train running on time?). Access to this type of information has become indispensable.

Several years ago, the phrase “fingertip learning” emerged as a means of describing the impact that search was having (or could have) on how we learn. It developed out of the very thing search provides—instantaneous access to almost anything. The underlying theory was simple: If we search for something, find it, and act on it, learning has occurred. But are we not just confusing fingertip information with actual learning?

There are many theories about how learning occurs or how to create environments that promote or facilitate learning. So my question, then, is very simple: When I search, does learning occur? Did it result in “a persisting change in human performance or performance potential” (Driscoll 2004)? Let’s consider an example.

Like most people, I occasionally forget to periodically save my documents. And for reasons I can’t explain, I lose my latest versions. As result, I have to frantically look for the backups or temporary files that exist somewhere on my computer. So I enter a Google search for something like: “finding lost word files on my Mac.” Half a second later, I start to pick through the 2.4 million results to find the one that will best help me. In most cases, I find the information I need, follow the procedure, and recover my files.

The question is whether I learned anything from that experience—other than that I need to save my documents more often. For the most part, the answer is no. I certainly have not memorized the file-recovery process, which doesn’t worry me because the next time I can just conduct the same search or bookmark the webpage I need. So while search absolutely helped me solve my problem, it did not result in a persisting change in performance. It was not a learning device.

What my search actually gave me was fingertip information, and that is almost always incredibly valuable. The information I received enabled me to solve my problem quickly and efficiently. In essence, Google, Bing, and other search engines have become the world’s most powerful and comprehensive performance support systems. What they do so incredibly well is provide us with instantaneous access to information, pictures, videos, and other materials that might help us learn.

But it isn’t that simple. Search engines fail to provide context. Suppose we want to learn more about Alzheimer’s disease (5.5 million hits in just more than a quarter of a second). We could start by going to the Alzheimer’s Association website. Or instead, we could read Wikipedia to get some background and develop a plan of attack from there. But we must develop the plan, and we probably don’t know enough to do that very effectively.

All this is not to say that search engines don’t play an incredibly important role in learning. They do. But their role is based on what they do best—finding and displaying information quickly and efficiently. I suspect that Pluralsight, edX, Skillshare, and other online content providers would agree that search engines contribute greatly to their individual and collective success. So while it’s inaccurate to say that search-enabled fingertip learning will replace more traditional forms of training, it’s certainly true that search enables learning and has become an indispensable partner in the learning value chain.

Pronouncement #6: The Kirkpatrick Model Rules

In the early 1990s, I worked in the educational services department of a large computer company that offered training to employees and customers. Each quarter the vice president would hold a meeting to report on two results metrics—“butts in seats” and revenue. If both went up quarter over quarter, we were happy; if they didn’t, we weren’t. Those meetings sent a very clear message about what really mattered.

In 1994, Donald Kirkpatrick published his seminal book on measuring learning, Evaluating Training Programs. His four-level measurement model became the industry standard for evaluating the overall quality of the training offered in organizations everywhere. Kirkpatrick forced us to think differently about the questions we asked and how we asked them. We started to adjust our fixation on how many people attended a program and increase our concern about whether their attendance actually mattered. Did they learn anything? Did they apply it in their work? Did it have a positive influence on outcomes or results?

This shift to a more structured approach to the evaluation of learning has been, and continues to be, a slow process for many reasons:

   Lack of skill on the part of learning and development professionals—writing good measures of knowledge, skill, application, and impact is time-consuming and difficult; interpreting and acting on the results is, too.

   Organizational indifference or unwillingness to do the work required to identify the right metrics and collect the necessary data.

   Lack of institutional rewards for participating in a comprehensive measurement strategy—conducting evaluations, taking tests, and filling out observational checklists take time. And if employees and managers don’t believe there are any consequences for not participating, their interest in doing so diminishes greatly.

My point isn’t that the Kirkpatrick model, either the original or recently updated version, doesn’t work. To the contrary, I think they both make sense. I just think that they require a level of skill, discipline, and institutional will that is hard to find.

In addition, the world of learning differs drastically from the one Kirkpatrick experienced during most of his working life. Companies offer thousands of courses—classroom based, e-learning, internally developed, vendor provided, live, and virtual. And if we had the time to do the research, we probably would learn that average usage is very low and that we have almost no data that answer the very basic questions of value: Which programs drive the most value (assuming you can define it)? Which elements of these programs are the best? How can we make the best programs even better? On what objective basis can we eliminate, rationalize, or reduce the clutter in our training offerings? And we haven’t even touched how to measure the value of the vast content available outside our corporate firewalls.

Despite widespread understanding of the Kirkpatrick framework, it really doesn’t answer these questions. Perhaps the answer is in finding the right way to ask another question: How highly would you recommend this course to your peers? This question alone would tell us whether a course adds value and whether employees believe they are learning valuable things from it. Capturing, collecting, and analyzing answers to this simple question could be extremely useful.

Don’t mistake this for a claim that the Kirkpatrick model holds no value. Instead, I am suggesting that the learning world of 2015 requires much more. Just as the sophistication of the instructional design toolkit has improved since the 1990s, so too must the approaches, methods, and tools we use to evaluate learning and learning outcomes.

Conclusion

On almost any day, learning professionals can visit a website, look at a professional journal, read a pundit’s blog, or leaf through some new industry book and discover a new and exciting pronouncement. It’s been that way for as long as I have been in this profession, and I don’t expect it to change any time soon. All we can do is take everything with a grain of salt, and try our best to figure out what these pronouncements really mean, how they might help us, and what we have to watch out for. And, above all else, don’t be afraid to push back when the little voice in your head is saying that something is too good to be true, or that you’ve heard it before.

References

Bersin by Deloitte. 2014. The Corporate Learning Factbook 2014: Benchmarks, Trends, and Analysis of the U.S. Training Market. Oakland, CA: Bersin by Deloitte.

Di Stefano, G., F. Gino, G. Pisano, and B. Staats. 2014. “Learning by Thinking: How Reflection Aids Performance.” Working Paper, Harvard University.

Driscoll, M.P. 2004. Psychology of Learning for Instruction. 3rd ed. Boston: Allyn and Bacon.

Kirkpatrick, D.L. 1994. Evaluating Training Programs: The Four Levels. San Francisco: Berrett-Koehler.

Lipsman, A. 2014. “Major Mobile Milestones in May: Apps Now Drive Half of All Time Spent on Digital.” Insights (blog), comScore, June 25. www.comscore.com/Insights/Blog/Major-Mobile-Milestones-in-May-Apps-Now-Drive-Half-of-All-Time-Spent-on-Digital.