I am teaching a course in quantitative methods to first year graduate students and introduced team-based learning to this course for the first time last spring.  For the most part it went well with one exception, Application Exercises.

Here is my dilemma.  The subject matter certainly provides ample material for application exercises.  Working with real-world data, students conduct real-world analyses.  The problem has to do with the team-based aspect of the activity.  The applications readily lend themselves to individual effort.  However, figuring out how to best meet the single answer, simultaneous reporting criteria is difficult.

What I observed was usually the one student on the team who had best statistical knowledge would sit at their workstation and do all the work.  The rest of the team watched over their shoulder.  Obviously this much social loafing is counter-productive.  As a team, they were more focused on "getting the right answer" than on learning the statistical concepts behind the analyses.  I encouraged everyone to work the problem and to help one another out.  Still, the students would quickly gravitate to the one workstation where the student already "got it."

My question is how to use team-based applications in this situation to greater effect.  I am striving for that mystical "cognitive

__________________________________________
Isaac T. Van Patten, Ph.D.
Professor of Criminal Justice
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It doesn't matter how beautiful your theory is;
It doesn't matter how smart you are;
If it doesn't agree with the [data], its wrong.
-Richard Feynman