Theory Analysis in Data Evaluation
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Theory Analysis in Data Evaluation

Theory Analysis in Data Evaluation

The second phase of the evaluation cycle the theory analysis phase is about interpreting the results of your data collection. There are several analytic strategies that can be employed to understand your data, including quantitative and qualitative methods.

Based on the nature and depth of your evaluation You may want to discover patterns or themes that repeat in your data. You may also want to look for connections among different elements. The process of analysis involves sorting, coding, and the comparison of your data with other theories and concepts, and it includes making sense of what you’re discovering in your data.

In the case of conducting a qualitative assessment of participants in a particular program, for instance, you can use a grounded theory to guide your analysis and help develop a theoretical construction from your data. GT is a method of research that lets you discover theories through constant interaction between data collection and analysis. The GT process generally involves open coding to identify interesting phenomena in the data; axial coding to identify relationships between phenomena and selective coding where you choose a central category to hold the emerging ideas together.

The core category is an amalgamation of all emerging phenomena. It could be either a concept or a grouping. The selected idea is then evaluated against a theory and the degree of fit is determined by iterative comparisons of incidents to the selected idea. During this process, notes are recorded to document and review the new ideas.

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