Listening vs. Doing: The Problem with Subject-Centered Training

People learn better by doing than by listening, and they learn better when they are held accountable to immediately use what they have learned.

To illustrate this point in the classroom I discuss pilot training (I am an instrument rated private pilot).  I have a book that I take to the classroom which is the Practical Test Standard for a Commercial Pilot.

I first ask if anyone in the room has any flight experience.  The answer is usually no.  I then ask if anyone has ever had the desire to fly a plane.  Someone will always raise their hand.  I pull out the book and say “This book has everything that you need to know to become a commercial pilot.  Study it tonight, and tomorrow we will put you in the pilot seat of an airplane and send you for your practical flying test with an examiner from the Federal Aviation Administration”.

Everyone laughs because they recognize how foolish this sounds.  However, it is precisely what we do when we have subject-centered classroom training but no real-world application.  Listening to someone lecture about flying an airplane or reading about flying an airplane is a lot different than flying one.  The same is true for learning about Six Sigma.

Every lesson in our Six Sigma courses is designed with a learning objective written using Bloom’s Taxonomy, an instructional strategy to meet the objective, and a practical exercise to determine if the objective has been met.  Here is an example from our Black Belt classroom program:

Learning Objective:  At the end of this lesson, you will be able to use Minitab to perform simple linear regression and will be able to correctly interpret the results.

Instructional Strategy:  The instructor delivers a lecture about what linear regression is and when it should be used.  The instructor then explains how to use Minitab to perform simple linear regression and works an example problem.

Assessment:  Students are provided a Minitab Worksheet file that contains paired data (X and Y values) for an exercise.  They individually conduct a linear regression analysis of the data and answer the following questions:

• What is the null hypothesis?
• What is the alternate hypothesis.
• Should the null hypothesis be rejected? Why or why not?
• What value of Y can be expected for an X value of 93.1?
• How confident are you in your prediction?

The answers allow the instructor to determine if the student has met the learning objective.  If not, more instruction and practice is indicated.