Theory Analysis in Data Evaluation

The second step of the evaluation process, theory analysis, is all about understanding the results of your data collection. You can employ a variety of analytical techniques to make sense of the data you’ve collected, such as quantitative and quality methods.

Depending on the nature and the extent of your assessment, you may wish to look for patterns or themes that you see in your data. You might also want to find connections between different elements. Analysis involves sorting, coding and the comparison of data with theories and concepts. It also includes understanding the information you uncover through your data.

When conducting a qualitative analysis of participants in a certain program, for example, you can use a grounded theory to guide your analysis and help develop a theoretical construction of your data. GT is a research technique that allows you to uncover theories by constantly interacting between data collection and analyses. The GT process involves open code, which is used to identify interesting patterns within the data. Axial coding is a method of identifying the relationships between phenomena and selective coding to bring the emerging ideas together.

The primary category is an amalgamation of all emerging phenomena. It could be an individual concept or a set of related concepts. The chosen idea is then compared with a theory and the adequacy is evaluated by repeatedly comparing events to the conceptual. During this phase, memos are kept to record and reflect on the emerging concepts.

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