Whether we’re conducting training for a company as large as Google or as small as a start-up firm with fewer than five learners, we often encounter similar challenges. Two of the most common ones happen when class attendees have disparate skill sets, and learners are learning at different rates.
Our learners would have similar backgrounds, skill sets, and identical working memory capacities in a perfect world. In the real world, a class full of students with the exact same background and experience happens rarely, if at all.
Regardless of the student population, our goal is to transfer knowledge so that newly trained employees return to their jobs with excellent skills and greater productivity, arguably the end goal of all corporate-sponsored technical training.
The introduction described how neurons form new connections to each other in the brain’s neocortex (long-term memory) when learning takes place. We must aim for the neocortex to send our learners back to their jobs with more knowledge!
Unfortunately, some of our current training methods miss this mark with the result that learners are storing new information in the part of the brain known as the working memory. The problem with working memory is that information goes in but doesn’t stay. So when information resides only in working memory, learners return to their jobs, unable to recall and implement the knowledge gained in our class.
Connections between neurons can be made stronger with active focusing on a new topic—as learners do in class—but sometimes that’s not enough to form links in long-term memory. Thus, only the appearance of understanding is gained. This false sense of security regarding what has been learned can last long enough to give instructors a ten out of ten on course evaluations but not enough to increase on-the-job productivity. The problem with working memory is that information goes in but doesn’t stay.
From a pedagogical perspective, we have two jobs as trainers:
We must transfer knowledge as we teach using our favorite tried and true methods such as lectures, practice, writing code, and so on. Neural connections are being formed wherever these kinds of learning are taking place. Chemical signals pass from neuron to neuron as axons reach out to touch the dendrite of a nearby axon, creating a new synapse, and thus a learning connection is made.
We must ensure that these new connections are strengthened and stored in long-term memory so that learners return to work able to recall newly attained knowledge as needed. Adult learners have a significant advantage over children that trainers must exploit. Linking prior knowledge to new information helps learners make stronger connections, and adult learners can draw on a lot of previously acquired knowledge!
The challenge for trainers occurs early in our lesson when our words, ideas, and concepts are in a learner’s working memory. Suppose I begin my lecture with the difference between programming variables and constants. As long as my learners are focused on these ideas, they’re available to them from their working memory.
But like a juggler spinning objects in the air, the average adult’s working memory can hold only about four pieces of information at one time. This isn’t true for all people; some can hold much more (in fact, this difference explains why there are fast and slow learners).
The question is, what can we do as trainers to reduce this disparity?
Working memory capacity is believed to be fixed by adulthood. Capacity is relatively small for toddlers, but it grows to reach its peak (typically four pieces of information) at age 15. It’s also thought that some teaching methodologies can enhance working memory capacity. One effective method is to bring learners’ prior experience into play.
For example, programming languages are ripe with shared principles and concepts. Using previous knowledge of one programming language shouldn’t be challenging when learning a new and different language. If you’re unfamiliar with the learner’s current skill set and therefore find it difficult to make analogies, don’t hesitate to ask learners about the similarities or differences between what you are teaching and their current understanding. Their responses will help you make connections that are stronger.
When learning is fresh, the best way to strengthen neural links is through practiced retrieval of the information. “The use of retrieval practice as a learning strategy, by teachers and students, has been shown to increase students’ long-term retention and transfer of knowledge to new situations.”[1]
Fortunately, there are many ways to encourage your learners to practice retrieval. The most obvious one is asking questions frequently. In coaching trainers, I’ve found infrequent questioning to be the most common trainer mistake. I recommend lecturing no more than five minutes (ten minutes maximum) without asking a question. Finally, when students can retrieve and practice independently (as during lab exercises), the neural links have been strengthened, and the knowledge is linked to long-term memory.
For more tips on implementing practiced retrieval, see tip 41 on no-stakes testing, the anti-lecture, and quizzes.
How to Do It
These are some of the most effective techniques for teaching to long-term memory:
- Practiced retrieval
- Ask questions frequently.
- Be sure to call on all of your students regularly.
- Before you instruct students, ask them to provide the instructions instead.
- Use quizzes that encourage learners to reflect on what they’ve just learned.
- Provide frequent lab exercises that challenge the learner to perform tasks independently.
- Spaced repetition
- Ask short but frequent questions regarding previously taught material.
- Periodically, ask more extended reflection-type questions that cover material previously taught.
- Add one or two questions to quizzes that cover previously taught material.
- Many trainers hesitate to ask too many questions during class because they feel they are too time-consuming. While questions can be time-intensive, the payoff is learning that sticks.
It helps to know a bit more about questions so you can determine which are and aren’t time-consuming and which will be most effective.
Fact-Based Questions
These questions prompt factual information as a response and can be memorization-type questions. Combined with spaced repetition (such as those asked at the beginning of each new class as a form of review of the prior material), fact-based questions can be both helpful and quick. They’re common in software classes. Examples include: “How do you change the security setting?” and “Where is the configuration file located?”
Experienced-Based Questions
These help gauge a learner’s current understanding of a topic and also set the stage for connecting prior knowledge to new knowledge. Examples include: “How would you implement this feature without introducing a security vulnerability?” and “Why do you think this solution might degrade the performance of the application?”
Opinion-Based Questions
These may be the most time-consuming of all question types. Use these sparingly when time is limited. While value judgments can be appropriate, use them only when you think they’ll solve a problem for the group as a whole. Examples include: “What are the pros and cons of this technique?” and “Now that we’ve learned two different ways to solve this problem, which one is best and why?”
Challenges
How do you know your learners will retain what you’ve taught when they return to work?
Do you follow up with your learners?
Have you asked your learners what they think might help them retain new information? Have you offered suggestions such as a follow-up class or job aids?
References
[1] Pooja K. Agarwal, Jason R. Finley, Nathan S. Rose, and Henry L. Roediger III, “Benefits from retrieval practice are greater for students with lower working memory capacity, Memory,” DOI: 10.1080/09658211.2016.1220579, (2016)
