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Learning Actually

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This is the first part of my ‘Learning Actually’ series. Although the core of the series is technology-aided learning, the main theme is organizational learning using a holistic approach. Whenever I am trying to design a solution for organizational learning, be it theoretically or practically in my professional life, I face roadblocks arising from the faulty core of the traditional learning culture, clichéd training methodologies and more intensely, the disability to distinguish between training and learning. After all, with a faulty learning strategy, your problems are not going to get solved by adding an ‘e’.

Hence ‘Learning Actually’.
Please share your comments, agreements and disagreements to make the series more complete.

Learning Actually…
is non linear

Like problem solving in the real world, learning is non-linear. The problem starts when we try to carry our habit of ‘first learn then work’ from our schools to work organizations. In the real world, there is no such thing as the linear method.

Why? Because the real world is complex, not just complicated. The learning needs of knowledge workers are also complex, networked and asymmetrical. Think about a hi-technology sales person. Will in-depth knowledge of the product’s features, functionalities and benefits alone make him successful? Apart from explicit knowledge (which can be gathered through linear learning) he needs to know the competitive advantages of his product. He requires the skill of listening to his clients and promptly designing solutions, which fit their needs. And throughout his sales cycle he needs to be in a learning curve. This can’t be achieved through a linear classroom-based model.
The metamorphosis of data into information, information into knowledge and knowledge into intelligence is complex and non-linear. The knowledge worker needs the knowledge inflow when he requires it. An excellent example of this can be found in an original paper published in Touchstone, written by E. Jeffrey Conklin & William Weil.

A study at the Microelectronics and Computer Technology Corporation (MCC) examined how people solve problems.
A number of designers participated in an experiment. Each was asked to design an elevator control system for an office building. All the participants were experienced, expert designers, but none had worked on elevator systems. Participants were asked to think out loud while they worked on the problem. The sessions were videotaped and then analyzed.

Traditional thinking, cognitive studies, and existing design methods all predicted that the best way to work on a problem like this was to follow an orderly and linear process, working from the problem to the solution. You begin by understanding the problem, which can include gathering and analyzing data. Once you have specified the problem and analyzed the data, you are ready to formulate-and then implement-a solution.

Traditional wisdom for solving complex problems-the “waterfall”

This is the pattern of thinking that we all assume we follow when faced with a problem. The conventional wisdom is that the more complex the problem, the more important it is to follow this orderly flow. If you work in a large organization, you have probably seen the waterfall model of problem solving enshrined in policy manuals, textbooks, internal standards for the design process, and the most advanced organizational tools and methods.

In the MCC study, however, the designers did not follow the waterfall model. They would start by trying to understand the problem, but would immediately jump to formulating potential solutions. Then they would go back to refining their understanding of the problem. Rather than being orderly and linear, the line plotting the course of their thinking looked more like a seismograph for a major earthquake, as illustrated in the diagram. We call this pattern both chaotic, for obvious reasons, and opportunity-driven, because in each moment the designers are seeking the best opportunity to progress toward a solution.

Actual pattern of problem solving – the “seismograph”

This non-linear process is not a defect, not a sign of stupidity or lack of training, but rather the mark of a natural learning process. It suggests that humans are oriented more toward learning (a process that leaves us changed) than toward problem solving (a process focused on changing our surroundings).

Of course, linear processes are quite appropriate for solving many problems, such as computing the square root of 1239 or choosing the shortest route to the new mall. But within organizations-such as corporations, institutions, and government-where lots of people work on complex issues, people are encountering a new class of much more difficult problems. We call these wicked problems because of the dynamic and evolving nature of the problem and the solution during the problem-solving process. It is these problems that the techniques described in this book are especially useful for solving.

Let me give a simplistic and personal example. I bought a Nikon D70 Digital SLR recently that came with a 400-page manual. The manufacturers would hope that I read the manual completely before operating the camera. Naturally, I did not. And I am positive most of you wouldn’t. I started using the camera straight out-of-the-box. Got stuck at some point, referred to the manual and moved forward. Again, I got stuck on something else, picked up the manual, and the cycle continues. I am still in the learning curve, but hey, it works. I am confident you would have done it the same way.

Classroom-based learning in organisations doesn’t always work because it follows a linear pattern. Sequester a bunch of people in a room for 3 days and teach them about the product you are going to launch next quarter. What happens next? Where is the continuity? What if I get stuck? Where is my cheat sheet? How can I obtain the tacit knowledge such as my advantage over the product of a competitor that I am going against in a bid next week? All these questions remain unanswered.

Written by anol

June 14th, 2005 at 11:05 am

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  1. [...] This is the second part of ‘Learning Actually’ Series. Read the first one – “Learning Actually is non linear” [...]

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