Corporations in the U.S. spend $156 billion annually to train employees. So when I read the headline “So Much Training, So Little to Show for It” in a recent online Wall Street Journal (WSJ) article, I wanted to know why Eduardo Salas, a professor of organizational psychology at the University of Central Florida and a program director at its Institute of Simulation and Training, had reached that conclusion. He uses data gathered in 2011 on employee learning from the American Society for Training and Development (ASTD), as well as research that claims 90 percent of new skills are lost within a year to point out that businesses spend a lot of money on training that doesn’t stick. One myth, according to Salas, is that “technology will solve all training problems … that a mobile app or computer game is the solution to learning.”
Salas believes that organizations need to rely more on the science of learning and training instead of acting on what he refers to as “myths” that lead people to make poor decisions about training. That’s a strong message! Is he right?
Before we launch into further discussion about myths and training, let’s look at how myths develop. A myth is the result of stories—real or imagined—that are repeated over and over for years—centuries and millennia—until hundreds of versions of a story exist. Myths are not created by one individual, but by many storytellers. Each time a story is retold, it changes. Myths usually do contain a grain of truth, however, and that may be what keeps them alive.
Let’s assume there’s a grain of truth in this myth about technology solving training problems. What is it?
A Quest for Clarity
What is technology? Well, technology means different things to different people. It comes from the Greek word techne which means “art, skill, and cunning at hand.” In this article, technology means “the purposeful application of knowledge in the design, production, and use of goods and services and in the organization of human activities.” Businessdictionary.com divides technology into five categories: tangible (e.g., blueprints, models); intangible (e.g., problem solving and training); automated and intelligent technology (e.g. telepresence robots and some computers); semi-automated, partially intelligent technology (e.g., computer tablets and smartphones); and labor-intensive technology (e.g., software programs and most water sprinklers for the yard).
If we assume that technology is the purposeful application of knowledge to produce goods and services that people use, then we’re right to think that technology will solve all training problems. If on the other hand we assume that technology is a computer and software, a robot, a tablet or smartphone, or the TV remote then we can be fairly certain that technology will not solve all training problems. How we use technology appears to be a key factor in whether or not it can solve training problems.
In the future, the training industry might employ intelligent, decision-making, problem-solving robots to train people, but for the present and foreseeable future, all indications point to reliance on partially intelligent and labor-intensive technology to create and deliver training. So how did this particular myth (or we could call it a “half-truth”) get started?
A history of the partnership that has developed between technology and learning is far too long to include here. Briefly, however, it was B. F. Skinner, a behaviorist psychologist, who introduced the concept of using technology to enable people to do self-teaching. He developed a specialized book—a teaching machine—that presented material in a structured, organized manner. And in 1957 Skinner published a paper about the teaching machine that launched a lot of interest in programmed instruction.
There’s an excellent discussion on teaching machines in Thomas Gilbert’s book Human Competence: Engineering Worthy Performance (originally published in 1978). Gilbert’s storytelling style and humor provide good reading and fascinating insights into the genesis of eLearning. But eLearning as we know it today wouldn’t appear until 38 years later.
By 1995, computer use was more widespread and the Internet was becoming main stream. During that year, a small group of learning professionals with a passion for technology and learning were listening to Brandon Hall. Hall heads up one of today’s leading eLearning research companies. Back then, he was showing the group the latest technologies and computer applications from his CD-ROM library. Everyone was excited about the level of instructional design and various applications, and they started talking to others about what they’d seen.
In 1996, the American Society for Training and Development (ASTD) held one workshop on Internet-based training. The next year, Training Magazine published the first article on “Internet-Based Training”; and Elliott Masey founded the TechLearn Conference. And in the span of two years, a new industry was born. At seminars, sales demonstrations, and in magazines, everybody was talking about eLearning!
At that time, predictions about the impact of eLearning included:
- eLearning will replace all classroom training
- eLearning courseware is easy and cheap to design and develop
- eLearning technologies are easy to use and integrate
- eLearning technology infrastructure is easy to implement
- Employees from almost all cultures like eLearning
- eLearning is mostly about how to use technology
- Significant cost savings can be made by adoption of eLearning
- The eLearning market will at least quadruple annually
People learned quickly that automated technology—primarily computers, software, and the Internet—had inherent limitations that prevented wide distribution of eLearning. Then, as today, technology did not match people’s expectations.
The problems that developed in the 1990s, when people tried to merge technology and learning to produce eLearning, persist today. Those bold predictions about the impact of eLearning would have on training don’t match the state of eLearning today. Here’s what we know for sure as eLearning development nears the 30-year mark:
- Only a few organizations have moved most of their classroom-based curriculum to the Internet
- High-quality, well-designed eLearning requires a significant investment of both time and money in assessment, scoping, design, development, and deployment
- eLearning technology integration has proven to be more difficult than imagined
- Connectivity and speed issues have been ongoing challenges due to a lack of high bandwidth
- eLearning is not that much about technology but more about learning, using technology
So Salas is right when he says that we need to rely on the science of learning and training rather than the technology to deliver training. In the 67 years since Skinner introduced the teaching machine, advances in technology have been phenomenal. Technology is making it possible to do things that we couldn’t even imagine 10 years ago. Things like online MOOCs that bring together tens of thousands of people to learn with each other in one space of time but from many places around the world. But we’ve also made mistakes due to assumptions and misunderstandings about learning and about technology.
Today, we have better understanding about how people learn as well as how technology can support learning. Dr. Salas suggests that vendors make sure training is flashy and engaging with lots of bells and whistles that employees find “fun and interesting for a few hours.” He argues, however, that visually interesting presentations are not enough; that for learning to successfully transfer back to the job, participants need opportunities and time to practice in the work environment. They also need very clear and precise learning objectives, and clear feedback on performance. When these things are not present, it’s unlikely that the training experience will transfer back to the job, or that it will stick.
It’s true that many people LOVE shiny new gadgets that have lots of “bells and whistles.” We’re eager consumers of the next new thing to come along. But that’s only one side of our infatuation with technology. The other side is that we live in a complex world and we have to manage wild problems with limited time and resources. So when someone says they have a solution to any problem and then brings out the sample to cement the impression, we get interested.
Mobile apps and computer games are examples of this type of problem-solving technology. We need to be open-minded consumers, though, and try to understand the need before we commit to a course of action. Mobile apps are designed to remember and do things repeatedly and easily. They complement our human intelligence and free our minds to do complex problem solving and decision-making tasks. But they’re not the solution to everything learning related.
Those stories and predictions—like the stories and predictions about eLearning that spread—are often not accurate. While digital devices are portable, and we’ve both seen and heard lots of stories about the amazing things mobile apps can do, making it easy to believe mobile technology reduce the need to take people away from their jobs for training, the research indicates mobile technology is not the answer for every learning need. There’s convincing evidence that the learning environment is a key factor in learning and retention. The science of learning tells us that we have the ability to hold information in our short-term memories for a short amount of time. So Salas is also right about what is needed to make training stick. To get better ROI for training, we need to practice what the research has proven and provide learners with time and opportunities to integrate new skills and knowledge with their prior experiences.
 Gilbert, Thomas F. (2007) Human Competence: Engineering Worthy Performance, Tribute Edition. San Francisco: Pfeiffer, pp. 297.
 Thomas F. Gilbert’s book Human Competence: Engineering Worthy Performance was first published in 1978 New editions are available. [Return to text.]
 Quinn, Clark N. (2011). Designing mLearning. San Francisco: Pfeiffer. [Return to text.]