Below is a review of what was discovered by refining the cross-tabulations into descriptive statistics. After the data has been prepared, and the quantitative and qualitative data analyzed, the descriptive statistics can be used to help one talk about the data.
The objective of an assessment determines what can discovered. For example, if the objective was to ask the audience if they liked the play, then one won’t find out much about why they liked the play. It is therefore critical to ask the right questions and set the most informative objectives for the assessments. Objectives get better when they are very descriptive, for example, of exactly what one wants students to learn, or what one wants to find out about audience opinion.
If, for example, the objective was to find out all the different reasons for why the audience liked the play, then our categories of those answers will reflect that objective by suggesting that all of the different reasons could be sorted into similar categories. The answers to the assessment, perhaps in this example, an audience feedback sheet, could be full of a wide-range of answers. Some of those answers may be sorted into categories that are not helpful, such as the content of the play, and some of those answers could be sorted into categories that may have something to do with the acting, the set, the seats—things that could be readily changed. Categories help sort audience feedback into similar kinds of information and ultimately into manageable chunks of data.
Once the data is sorted into categories of similarity, the first set of results have been created and these can be called findings. Grouping data together, either quantitative or qualitative data, is an act of judgment and it produces the beginning of the findings. For example, if there are several audience comments that fall into two categories, praise for the show and dislike over the seats, then each one is a finding. These two categories of comments can be combined into a finding statement that might look like this,“Many audience members liked the show but disliked the seats.” Combining data into categories of similarity and reporting them in descriptive statements is producing findings.