Theory Analysis in Data Evaluation

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  • Theory Analysis in Data Evaluation
Şekil Resim Bir

The second stage, called theory analysis, is about understanding your data. You can use a variety analytical methods to make sense of the data you have taken in, including qualitative and quality methods.

Depending on the kind of analysis you are conducting depending on the type of analysis you are conducting, you may need to identify repeating themes and patterns within your data or look for connections between different items. Analysis involves sorting, coding, and comparing data with theories and concepts. It also involves understanding the information that you gather from your data.

In the case of conducting a qualitative assessment of participants in a certain program, for example, you can use a grounded theory to guide your analysis and help create a theoretical construct of your data. GT is an inductive research methodology that allows you to come up with new theories through the constant interaction between data collection and analysis. The GT method generally involves open coding in order to discover interesting patterns in the data and axial coding to discover connections between phenomena; and selective coding where you select a central category to tie the new ideas together.

The fundamental category is a collection of all emerging phenomena. It can be either a concept or a grouping. The idea chosen is then compared to a theory, and its fit is assessed by an iterative process of comparing events to the concept selected. Memos are used to reflect and record the concepts that are emerging during this stage.