Sunday, January 17, 2016

Sunday, December 27, 2015

Factual and emotional content

I saw this chart in Kyoto Station and reminded me of core structure of a lesson.

"Eat" is a factual content, while "paradise" is an emotional content. Both are needed for learners to understand content.

Saturday, December 26, 2015

Watch "Japanese great guitarist~shamisen" on YouTube

https://youtu.be/7QAMrzqeDGM

This reminded me of what Jane Bozarth showed us with the ukelele.

Estimation

This hour glass is an estimation of time, not exact. In learning, it is best to develop skills of estimation, exactness follows.

Thursday, October 15, 2015

Slow-Mo Learning is Faster

Whether it is trying to fix the faucet or a broken heart, important decisions make or break significant relationships each day. Problem solving skills are therefore of paramount importance whether one is a handyman, a father, a CEO, or the President of the the United States.



It is not any different for organizations experiencing problems. Personnel are required and expected to think on their toes and come up with solutions on the fly. Their troubleshooting mettle will be tested and imagination is stretched to its limits to come up with that ingenious idea to resolve the nagging problem currently experienced. The good news is, troubleshooting skills can be acquired and if you already have them, these can be improved.

In this tip we will talk about troubleshooting and how important it is in the organizational setting.

Diagnostics: Identifying the Problem 

Troubleshooting starts with diagnostics. Before a problem can be solved, it must first be identified. In the words of MIT professors Randall Davis and Walter Hamscher, "To determine why something has stopped working, it's useful to know how it was supposed to work in the first place." In the organizational setting, the question may be asked: is there a gap between current and desired performance? Identify your goals. What are the barriers towards accomplishing your goals?

So what is a Diagnostic? According to Harrison Dia in his book Diagnosis: Approaches and Methods, "In organizational diagnosis, consultants, researchers, or managers use conceptual models and applied research methods to assess an organization's current state and discover ways to solve problems, meet challenges, or enhance performance... hence, diagnosis can contribute to managerial decision making, just as it can provide a solid foundation for recommendations by organizational and management consultants."

One area of study is how well people estimate or predict between defined problems and anticipated solutions. This is affected by the accuracy of both the diagnosis of the problem and the solutions and the discrepancy between observations and predictions.


Power of Observation and Predictions in Learning

Learning has a lot to do with troubleshooting and problem solving. What drives this is the process of observation and predictions. According to  Davis and Hamscher, "Observation indicates what the device is actually doing, prediction what it's supposed to do. The interesting event is any difference between the two, a difference is termed a discrepancy."  When we see a problem we make observations on causes and related aspects of the problems; we also make predictions on how the problems can be fixed with some of our solutions. The discrepancy happens when our observations are far from our solutions.


SLOW-MO Learning - How to Do Better than Just Trial and Error Learning

Our daily lives and activities are made up of constant troubleshooting and problem solving. From tying our shoelaces to driving out of the garage door, there is a constant estimation process.

Similarly at work, we encounter daily troubleshooting and problem solving, from simple tasks of fixing a mail-merge formula in MS Office to investigating why the scrap level is so high in a particular batch.

What is interesting is that, to learn from this experience, it is worth understanding what I call the SLOW-MO Learning. To get things done, there is a cycle of problem - observation - prediction - discrepancy - back to the problem. The cycle continues until a solution is reached.



Although this happens in milliseconds, slowing down the mental process to extend thinking time may achieve more fruitful results.This is what I would term as SLOW-MO (slow motion learning approach).

In rapid motion, learners may overlook an effective diagnostic and troubleshooting process. There is no thinking through because workers merely follow the cause and effect method by trial and error. This often happens when we expect learners to memorize content rather than think and apply the content in real-life situations.

To improve the results of trial and error, there is the "Model of Reasoning" and for conversation here -- it is the SLOW-MO Learning . This involves slowing down in our mind, the flow of diagnosis and problem solving so we can discover the "discrepancy between our observation and predictions."  As the process decelerates, we take the time to add " reasoning" to our thinking. By pausing to ruminate, we "think through"  using "reasoning models" like the following: 

Fault models - set of things that can go wrong
Rule based - rules that guide how things work
Decision tree - scenarios or "What ifs"

Applying the reasoning models to troubleshooting and problem solving increases the chances of a successful solution.






This is an illustration for SLOW-MO Learning - you break down things so one clearly sees theflow. Then ask reasoning questions to better think through the troubleshooting situation.

There are many other "reasoning models" that can be employed. What is crucial is the ability to train and encourage our learners to take a SLOW-MO learning approach.  Guide them to train their minds to think through a troubleshooting or problem-solving situation and apply some "reasoning" to arrive at better solutions.

SLOW-MO Learning is the difference between trial and error and productive work.




In many work situations, many of the workers may not have access to knowledge and experience, tools and immediate solutions. They increase their chances of success when they add "reasoning" to how they approach problems and reach solutions.


References 

Exploring Artificial Intelligence: Survey Talks from the National Conferences on Artificial Intelligence. Edited by Howard E. Shrobe. Model Based Reasoning: Troubleshooting. Chapter 8. Randall Davis and Walter Hamscher, MIT: https://books.google.com.ph/books?  
 hl=en&lr=&id=JaCjBQAAQBAJ&oi=fnd&pg=PA297&dq=t...   

Cindy E. Hmelo-Silver. Problem-Based Learning: What and How Do Students Learn? Educational Psychology Review. Sept. 2004, Vol. 16, Issue 3, pp. 235-266.
http://link.springer.com/article/10.1023/B:EDPR.0000034022.16470.f3#page-1   

David Jonassen, Johannes Strobel and Chwee Beng Lee. Everyday Problem Solving in Engineering:Lessons for Engineering Educators 
http://hplengr.engr.wisc.edu/Problemsolving_Jonassen.pdf   

Harrison Dia. Diagnosis: Approaches and Methods. https://us.sagepub.com/sites/default/files/upm-binaries/5049_Harrison_Chapter_1.pdf


Ray Jimenez, PhD
Vignettes Learning
"Helping Learners Learn Their Way"