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Marla designs help documents for the software applications her company produces. She sits across from Sean who develops monthly training webinars. Marla would like to “move up” to building instruction like Sean does, but Sean tells Marla that he thinks that the work that Marla does is actually more useful for the company’s users.

We could argue the merits of documentation versus training, but there’s always the question of what each user needs at each moment of time. Context is everything.

The science of learning is a science that works to understand how we learn and how we can improve learning and instruction. But to be fair, humans have been learning on their own since, well, forever.

For instance, if Corinne wants to know how to do something, she often asks the person next to her and then gets on with her job. Yan mentors Morey and they meet most Tuesday afternoons. Marlena uses self-study materials and is going to take the certification exam in less than three weeks.

So why do numerous disciplines (neuroscience, psychology, education, computer science, and others) expend enormous energy and resources to figure out how we learn and how to best build instruction? Can’t we just leave people alone?

We Learn All the Time

An interesting study by D.W. Livingstone shows that the majority of workplace learning happens not in formal settings but in informal ones. Numerous studies, including those by Livingstone, Jay Cross, Jane Hart and others, show informal learning as a proportion of all workplace learning at greater than 70 percent.

If you haven’t already looked into informal learning, you should, because training professionals need to understand it more. Saul Carliner’s book, Informal Learning Basics, on the subject is a good primer, as are writings by Jay Cross and Jane Hart.

You might think that the definitions of learning and instruction are self-explanatory, but actually they aren’t so simple. And they help us see exactly what we are trying to do.

Learning, Defined

There are many definitions of learning. A favorite comes from De Houwer:  “Learning is changes in behavior that result from experience.”

Some definitions don’t require changes in behavior, only changes in knowledge. For me, this doesn’t cut it. If you can’t do what you are learning, the learning isn’t quite cooked yet. For example, if you can’t use what you are learning, you are on your way but not there yet.

Applied learning requires knowledge and experience with the range of possibilities, of course. As my colleague Catherine Lombardozzi reminded me, people need deep knowledge, not only to follow a script. So if a customer service agent is following a script for handling returns, but she cannot handle the variety of returns, she only knows how to follow a script. She hasn’t really learned the whole returns process.

One definition of learning discusses how learning requires the ability to correct errors. Now this is truly deep learning. One of the biggest problems people have is correcting things that go wrong. Misconceptions and mistakes are a big problem in learning. So when defining learning, we may want to determine how far into expertise we are talking about. Are they proficient (competent or skilled) or are they expert?

Why Build Instruction?

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People can and do learn on their own. But we also know that when there are very specific things we want people to be able to do, there are efficient ways to help them. If learning occurs when we interact with our environment, then instruction is the creation of special environments specifically to promote learning.

Dr. Richard Mayer, professor of psychology at the University of California, in his book Applying the Science of Learning reminds us we are trying to change behavior as a result of instruction and there are methods to do so that are more effective than others (that’s what the science of learning and instruction are about).

This view has very far reaching implications. It means that if we are building “instruction,” we have to impact what people do. That’s a high bar. Although it is may not be practical to expect that everything we do reach that high bar, we ought to reach that bar often.

So that leads to two question that we should ask ourselves:

  • How do we infer (assume changes in) learning after instruction?
  • How do we determine if the change has made it from instruction to the job?

We will answer these critical questions soon.


This is article 1 of Science of Learning 101, and I very much want your comments. Is this helpful to you? Does it answer your questions? Your comments can change the course of this series.


References

Cross, J. (2007). Informal learning: Rediscovering the Natural Pathways that inspire innovation and
Performance. San Francisco: Pfeiffer.

De Houwer, J., Barnes-Holmes, D. & Moors, A (2013). What is learning? On the nature and merits of a functional definition of learning. Psychonomic bulletin & review.

Livingstone, D.W. (2001). Adults’ informal learning: Definitions, findings, gaps and future research. NALL Working Paper 21-20010. Centre for the Study of Education and Work, Ontario Institute for the Study of Education, University of Toronto. Retrieved from  

Mayer, R. E. (2011). Applying the science of learning. Upper Saddle River, NJ: Pearson.