We explore three analytic methods that can be used to quantify and qualify changes in attitude and similar outcomes that may be encountered in the educational context. These methods can be used or adapted whenever the outcome of interest is change in a generally unmeasurable attribute, such as attitude. The analyses we describe focus on: (1) change in total "attitude score"; (2) item-level changes in attitudes towards different topics; and (3) "attitude shift" that is defined based on a qualified change algorithm. In our example data, the total-score approach gives a general index to the level of positive attitude; the item-level approach gives the median level of positive attitude and indicates items with the most positive/negative attitude (i.e., items to target in future iterations). The qualified change approach provides an objective measure of whether a shift in attitude has occurred. Each analysis is described with its advantages and disadvantages using the data from a survey of 70 preclinical first and second year medical students before and after an elective 11-week interactive seminar (22 contact hours) which introduced elements of complementary and alternative medicine (CAM) into programmed medical school training. When assessing changes that are more qualitative than quantitative, any of these methods can be employed to derive either descriptive or inferential statistics. The methods are straightforward and are appropriate when measurements are imperfect, ratings are subjective and differences are not necessarily absolute. (Contains 4 tables and 1 figure.)