Technical documentation has always been a medium of reaching to the end user with a purpose that largely revolves around training and education. But, it is only seldom that we think that learning isn’t mostly what our users look into our product documentation for. It is troubleshooting that they wish to do. All they are looking for is topic-based information; Learning, for them, is only a by-product.
For today’s presentation, we will cover these points. We may not have a lot of time to cover all the models and theories of cognitive learning, but we will have developed enough inclination toward “communicating for need” rather than “communicating for the sake of communication”.
We will cover the basic understanding of cognition and cognitive learning. We will see why learning to help people know is important. We will rather briefly look at the different cognitive learning theories. And, we will see if we can analyze something out of it, and keep that analysis in mind when writing product documentation, going forward.
One of the mistakes that technical communicators commit is that we fail to understand and deliver according to this need of the user, which in most cases – as I said – is troubleshooting. But, even if we assume that learning, the so-called by-product in the communication process, happens to be the only purpose for the user, our documentation is hardly focused enough to help them learn. Perhaps, we are trained to teach users, and not help them learning. Small words; big impact.
This is why understanding how people learn is important. Of course, cognitive learning and constructivism have been a part of studying human psychology for quite some time, but in the context of technical communication, we are still learning to see the real impact of their application. From what I’ve been able to learn about it, it is not about what you know, but how you use it that’s important. Let me, therefore, help you learn how I’ve learned to help. This week when we decided on talking about what we’ve learned at this year’s STC IAC, the idea was to talk about something that we learned… something that we didn’t know before. But, the conference, much like the one that I attended last year, provided me with those information tidbits that I knew of, just that I could never officially acknowledge that I knew the information tidbits, already. It is like, “I didn’t know that I knew what was told unless someone told that knew it”.
And, learning happens for most users much like that. Given our background and foreground of the work processes, we are writing for a user who will always have an interaction with the job profile before interacting with our products. That means, we don’t really have to educate them. We just have to capitalize on their knowledge to assist them in using our products. That’s much like holding the bicycle after your child has learned to balance and paddle simultaneously: It’s only guiding that you’ve got to do. The learning happens for most users much like that. Given our background and foreground of the work processes, we are writing for a user who will always have an interaction with the job profile before interacting with our products. That means, we don’t really have to educate them. We just have to capitalize on their knowledge to assist them in using our products. That’s much like holding the bicycle of your child when they’ve learned to balance and paddle simultaneously: It’s only guiding that you’ve to do.
Here, have a look at the results of the Index of Learning Style, which I will discuss as one of the cognitive learning theories: It is a online survey instrument that measures learning preferences based on four dimensions. It is a free tool and you can appear for a test that comprises of 44 choice-based questions, to choose between A and B choice. You can appear and re-appear for the test, but I honestly feel that your first attempt is usually right in such tests. This test measures how you like to learn, and was developed by Dr. Richard Felder and Dr. Barbara A. Soloman of the North Carolina State University of the US.
Look at the screenshots that Deepak, Arun, Sanjeev, and Smitha share with me. And, try to analyze the pattern of how they understand. Here we are talking about technical communicators – barring only Deepak. Even they did not know how they learned or what kept them interested as they learned. And, that’s the thing with us, too, in the real-life situations. We hardly get to know how our users learn to use our software. We can see that most of those who appeared for this test are active, sensing, and visual learners. The only exception is Smitha who qualifies a bit more as a reflective learner. We can also see that most of the appearing candidates tend to make cognitive leaps, continuously taking in information until they get it. Based on the score, only Arun and I like to learn by following a process from one logical step to another.
Here is the one-line information about each of the learning styles.
Then there’s this Experiential Learning Theory by David Kolb. I’ve analyzed that all users continue to follow the same learning pattern where they wish to get their hands on the product and learn in the process of Doing, Feeling, Watching, Thinking, and Maintaining.
David also sees and inter-relation between all these four elements. For example, those who prefer Reflecting and Testing are the ones who can perform better in situations that require generation of ideas; and those who prefer Reflecting and Conceptualizing are the ones who get attracted to theories that sound logic and can be approached on practical values.
As we look to conclude, we will stare at what we’ve covered and try to implement it in our daily lives and challenges, which revolve around the central problem of How to share correct information correctly. The analysis stage covers a systematic explanation of the way things are and the way they should be… this sounds too much like a tailor-made task for us. Most of the criticism for anything, anyway, belongs to technical communicators. The design stage is about outlining the performance objectives in order to fill the gap between the way things are and the way they should be. We should use the information gathered in the analysis and design phases to create a solution that bridges the gap. Implement and deliver the solution that you created. And, in the end, see from where the water seeps through if it does. (Or, wish that it doesn’t.)
From what we’ve discussed so far, we can conclude that learning and its cognition is subject to attention, imagining, judgment, memory, perception, reasoning, thinking process, and speech. And, that all these inter-related elements are subject to one’s own definitions, interpretations, and situations. We’ve also learned that committing a mistake isn’t an issue as big as not-correcting it or accumulating a set of such mistakes. Whether documentation is descriptive extension of the product or remains a replacement for the underlying training needs, it continues to be a medium of learning that can transform the user experience and provide useful and practical information. Based on the ADDIE model of Analysis, Design, Development, Implementation, and Evaluation, we can deduce that the involvement of these elements is equally dependent on the way we find, reduce, elaborate, arrange, and store (in short, transform) the information. The better we do it, the easier it is for our users to understand and apply it to relieve their pains. Repetition, which happens at the user level, and Elaboration, which happens at the documentation level, happen to be the two biggest differentiators in designing information. We’ve also learned that the transmission, translation, and articulation aren’t effect, unless we connect each of them to the business need. So, just for the sake of an example, saying that “something has changed” doesn’t sound as effective as saying that “The change will reduce your efforts and increase your efficiency.”
We conclude this presentation with some points to ponder: That despite how much quality effort and time we put into our documentation, the user’s background, experience, and knowledge continue to be the biggest factors in their comprehension of content. That the contextual relevance is of key importance. And, therefore, we should focus our efforts on adopting a task-oriented approach. And, that each task should correspond to an action and a conclusion, in most cases. That the use of verbs to communicate the correct application of these tasks will always bring the user to the content. That the requirement is that the software must perform in real-world scenarios to bring the current and expected performance quotients closer. To fulfill this requirement, the design must address and represent the variables and relationships to provide the user with a context that fits the dynamics of the daily workplace practices.
But, the two most-important conclusions are: That we underpin cognitive learning theories in technical communication and document design. That the users will, invariably, learn more when they aren’t consciously involved in the learning process.
Why Cognitive Learning is Important for Technical Communication
• What is Cognition? And, what is cognitive learning?
• Why is cognitive learning important?
• What are the cognitive learning theories?
• How do we learn?
• What are the takeaways?
COGNITION AND COGNITIVE LEARNING
Q: What is Cognition?
The act or process of knowing in the broadest sense; specifically, an intellectual process by
which knowledge is gained from perception or ideas. (Webster’s Dictionary)
Q: What is Cognitive Learning?
To know that the learning is happening!
Cognitive learning means storing inform from the short-term memory as a behavioural trait
into the long-term memory.
IMPORTANCE OF COGNITIVE LEARNING
Most users don’t know that they knew what they’re told
unless someone tells that they knew it.
Users only acknowledge the knowledge, later.
ANALYSING THE LEARNING PATTERN
Learner Key Characteristic
Active Learners Learn best by either applying the information or explaining it to others.
Reflective Learners Prefer to go by the book.
Sensing Learners Are good at learning facts and are detail oriented.
Intuitive Learners Identify the relationships between things, and are comfortable with abstract
Visual Learners Remember best what they see.
Verbal Learners Do better with explanations.
Sequential Learners Like to learn by following a process from one logical step to the next
Global Learners Tend to make cognitive leaps, continuously taking in information until they get
OTHER COGNITIVE LEARNING THEORIES
• David Kolb’s Experiential Learning Theory (ELT)
• Users learn and explore.
• The constant need of Do-Feel-Watch-Think
OTHER COGNITIVE LEARNING THEORIES
• The way things are, and the way they should be
• Outline performance objectives on gaps
• Create performance-driven solution
• Get things done: Delivery
• Measure how good did you do
• Cognition is subject to inter-related elements
• User’s learn through mistakes
• ADDIE model, too, is subjective
• Cater to the business needs
CONCLUSION: POINTS TO PONDER
• Background, experience, and knowledge: External factors