The purposes of this paper are to illustrate the use of several assessment strategies in an advanced course in statistics, and to present the results of student ratings for each assessment strategy in terms of difficulty, appropriateness, level of learning achieved, and preference. The assessment strategies used include structured data analysis assignments, open-ended data analysis assignments, reviews of applied research articles, and annotating computer output from multivariate software procedures. Findings indicate that students "prefer" instructor-directed or structured assignments overall, but feel they learn the most when the assessment is unstructured and requires greater self-direction. Suggestions for incorporating these assessment strategies into the multivariate classroom, as well as examples of each strategy, are included in this study.
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