In college courses that use group work to aid learning and evaluation, class groups are often selected randomly or by allowing students to organize groups themselves. This article describes how to control some aspect of the group structure, such as increasing schedule compatibility within groups, by forming the groups using multidimensional scaling. Applying this method in an undergraduate statistics course has resulted in groups that have been more homogeneous with respect to student schedules than groups selected randomly. For example, correlations between student schedules increased from a mean of 0.29 before grouping to a within-group mean of 0.50. Further, the exercise motivates class discussion of a number of statistical concepts, including surveys, association measures, multidimensional scaling, and statistical graphics.
The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education