Helping people develop new skills is a complex endeavor. There are many considerations: what they already know or don’t know; how people think; the skills and techniques of the trainers; even the motivation of the students. A bottom-line issue, though, is whether the students actually develop mastery of the skills. When we get to the end of the day (or the end of the training), employers want to know, can they do what I need them to do when it really counts?
Once again, I’m happy to share insights about these issues from How Learning Works, a very well-researched, but highly practical book for educators as well as business leaders.
Last week, in Part I of this article, I explored the first two of four insights for helping people develop mastery of skills. In that article, I focused on what I called “The Expertise Paradox” (reasons experts have difficulty teaching novices) and the importance of breaking down complex skills into component skills. This week, I look at re-integrating those skills and then the issue of properly applying those skills in real-world settings.
When learning new complex tasks, it can be very helpful to break the task into component skills. An important follow up step is to re-integrate those skills back into the complex task so that the sub-skills can be practiced together. This process of integration creates a “cognitive load” on the learner. This cognitive load can lead to stress and reduce the learning effectiveness.
Ambrose et al. (2010) defined cognitive load as “the total information-processing demands imposed by a given task or set of tasks.”1 Put simply, cognitive load is the brain power required to successfully complete a given task. Of course, different tasks have different cognitive loads (playing a piano concerto vs brushing your teeth) and different people have different cognitive capacities (the music prodigy vs people of typical intelligence as well as variances by age). For our purposes, we’re going to address the group of people who are working adults with typical intelligence.
However, within that broad group we still have experts and novices for any given task. Intuitively, we understand that the experts are more readily able to handle the cognitive load of a given task than the novices. It helps to consider why this is the case, though, because it provides insight into helping novices becomes experts as well.
The simple reason that experts can handle the same cognitive load more readily is that they have more practice at the complex task and the task has become cognitively automated. (The topic of practice will be covered in more detail in next week’s article.) Experts who do not consciously consider this fact are prone to set expectations that are too high for novices. (See “The Expertise Paradox” section of last week’s article).
There are some things that can be done to help novices “manage cognitive load as they learn to perform complex tasks.”2 First, when re-integrating components skills, it helps to focus on one skill at a time in the context of the full task. This temporarily reduces cognitive load and learning stress.
An example of this is learning to be a better writer using word processing software. While there are tools in word processing software that can help someone be a better writer, for the novice who is not a good writer and is simultaneously new to the software, the cognitive load of learning writing skills and new software together is quite daunting. Focusing on separate skill sets temporarily, and then integrating skills later, facilitates master.
Another help for reducing cognitive load is to support some elements of the complex task while the whole task is being practiced by the learner. An example of this is to provide examples to be modeled or to work through pre-solved problems together.
The apparent follow up step to integration of skills application of those skills to real-world settings.
Application is the logical conclusion to the process of learning and mastering skills, both simple and complex. This is the step of moving from what and how to when and where facilitated by understanding why.
This process is often called “knowledge transfer.”3 Ambrose et al. (2010) explained that there is quite a lot of research that has looked at why effective transfer is difficult to achieve. For this current discussion, we’re going to focus on two pertinent reasons.
First, we have the issue of context dependence. This occurs when a person’s skills learning is too tied to environmental and procedural cues that are absent in real-world settings. A simple example of this is when a trainer introduces each session with a comment such as, “Today, we’re going to focus on how to do X.” This is helpful in focusing students’ minds on the right skills, but by itself it does not help them understand when and where those skills should be used. In real-world settings, we don’t have other people telling us, “For this problem you need to use skill X.”
Another problem impeding knowledge transfer is closely related to the first: not understanding why to use particular skills. If the training process does not go beyond the what and how, students will have a difficult time selecting the correct skills to apply when in abstract contexts.
Ambrose et al. (2010) offered four helps for better knowledge transfer:
- During training, make strong connections between the activity (the what and how) and the reason (the why). Connect the concrete to the abstract.
- Apply concrete skills in multiple contexts. This will also facilitate the connection between concrete and abstract and reinforce the why, especially when the next technique is applied.
- Conduct structured comparisons between relevant situations. Analyze how they are similar and different and why specific skills apply or do not.
- Minor prompts from trainers (e.g. questions, reciting key words and phrases, mnemonic devices) can help students recall new and weak, but continuously strengthening pathways in the brain.
In the entire learning process, there are many critical elements: past experience and knowledge, how we think and organize information, motivation for learning, how we practice and get feedback, the context and environment for learning, becoming self-directed learners, and, of course, mastery of skills. They are all important and these are the topics being explored in this series.
However, the “acid test” for learning is really whether the skills have been mastered and whether people can apply them in the proper time and place. This isn’t the only important element, but it is a critical one. (An employer won’t care about the other topics if skill mastery can’t be developed.)
Therefore, when creating a strategy to train your people with new skills, skills that will enhance your competitive advantage in the future, carefully consider your approach to dealing with:
- The expertise paradox—Helping your experts be effective trainers for your novices
- Breaking it down—Deconstructing complex tasks into component skills
- Integration—Re-integrating the component skills into relevant complext tasks
- Application—Effective strategies to aid knowledge transfer
These are some of the tipping points between being a person being ready and willing to learn and being able to use what they’ve learned effectively, in real-world business settings.
Other Articles In This Series
Dr. Scott Yorkovich is a leadership coach and consultant. He works with individuals, small and medium organizations, and ministries. Contact him at ScottYorkovich[at]LeadStrategic.com with your questions.
Photo “Oltrarno Artisans” by Context Travel. Available at Flickr.com.
1: Susan A. Ambrose, Michael W. Bridges, Marsha C. Lovett, Michele DiPietro, and Marie K. Norman. How Learning Works: 7 Research-based Principles for Smart Thinking (San Francisco, CA: Jossey-Bass, 2010), 103.
2: Ambrose et al. (2010), p. 105.
2: Ambrose et al. (2010), p. 108.