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Categorize and Code
Categorization and coding form critical elements in the interpretation of presented data from action research. This enables the identification of specific information from the data set, which can be used in the actual interpretation leading to the production of information. The first step towards the organization of data into a formal system involves categorization of the information into common segments entailing the same characteristic descriptions. According to Ary, Jacobs and Sorensen (2009), "The types of data collected can be categorized as experiencing, enquiring or examining" (p.556). This is especially important with regard to the formal recognition of the distinctiveness of data types. For instance, consider data from an n action research study involving the identification of most appropriate teaching methodologies. In this case data could be efficiently categorized by splitting the participants in the research according to age group, education levels, and subject specializations. Hence, the modes used for categorization depend fundamentally on the respective research interests and other theoretical provisions.
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The second step in the organization of action research data involves coding the identified categories in order to identify unique elements in the data. In essence, coding involves identifying individual pieces of data which belong to a distinct description. For example, the data collected from an interview could contain a mixture of general and specific information by virtue of the open-ended response mechanisms entailed in the respective processes. According to Henning, Stone & Kelly (2008), "Coding data reduces the information from the interview into a manageable form and helps you to better understand and communicate your findings" (p.103). There are various systems that can be used to code the data appropriately. This may involve the application of a color and symbol system. The actual coding begins by from going through the available transcripts, field reports, and assays resulting from the research. A coding scheme is theme is then developed based on the presented themes, incidence, common trends and patterns existing in the data (Henning, Stone & Kelly, 2008).
Analyze key Experiences
The act of subjecting key experiences in the action research is important in establishing key relationships relevant in the research. According to Henning, Stone and Kelly (2008), "Researchers tend to draw inspiration from their previous experiences, their everyday observations, their reading, their conversation with colleagues, and their findings from previous research" (p.19). By doing this, the researchers are in a position to consider some of the assumptions that are bound to affect the final results analysis of the research. During analysis of experiences drawn from the research it is important to infer from various viewpoints existing in the same subject of analysis. For example, in an action research study involving the analysis of effectiveness teaching modes involved in teaching History, it will be important to concisely use other research findings/experiences on the same subject in order to establish similarities, interactive elements, and conflicting views. Hinchey (2008) observes that, "...action researchers offer interpretations they consider most likely, using their own experiences and perspectives to inform their judgments" (p.94). Hence, in order to avoid bringing the concept of misjudgment in the reporting mechanism for the experiences this needs to be adequately supported by professional views. Sources that can be used to give major support to the key experiences as having significance to the action study include those that are peer reviewed and accredited.
Enrich analysis using Frameworks of Interpretation
There are different modes of interpretation that can be used in generating a competent framework of analysis. These will primarily depend on the data types and thematic concerns of the research in question. According to Henning, Stone and Kelly (2008), "Successfully interpreting data requires persistent thinking from different perspectives. It is common to offer alternative explanations for the same set of data" (p.156). This makes the research more meaningful by virtue of the fact that it leads to the emancipation of varied perspectives that are relevant in the research. The interpretation of data serves as a basis for the development of new teaching strategies (Henning, Stone & Kelly, 2008).
The first significant step in developing a framework for enriching analysis involves literature review. "The literature review helps you indentify what is already known, how it relates to your question, how your study might contribute to greater understanding of the topic, and the potential theoretical frameworks that might inform the study" (Ary, Jacobs, Razavieh & Sorensen, 2009). For example, consider an action research examining student traits leading to acts of indiscipline the school setting. In this case, it would be important to conduct a literature review of the behavioral models that are relevant in analyzing student behavior. Another important element in identifying a framework for interpretation involves the consideration of the qualitative and quantitative traits of the data. Hence, if the data was quantitative, the mode of interpretation that will be used to interpret data will take into account the numerical variables then infer inference will be made from existing theoretical interpretations of the same data variables.
Data analysis involves using a preferred method of analysis to bring out meaning in the action research. "Data analysis typically relies on qualitative coding processes and focuses on description and sense making" (Ary, Jacobs, Razavieh & Sorensen, 2009). Hence, researchers are constantly making attempts to correlate important elements in the data based on occurring similarities and differences. Another important element during data analysis involves the consideration of the magnitude of data variables from a quantitative perspective.
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Various data analysis methods can be used to bring out the desired interpretation. "Interpretation can be enhanced through the use of visuals, such as concept maps" (Ary, Jacobs, Razavieh & Sorensen, 2009). In the interpretation and analysis of quantifiable data it is important to display the data using tables and diagrammatic presentations. The use of a visual display enables the readers to understand the information, while it breaks up the monotony common with prose presentations (Koshy, 2005). The use of graphical presentations as a basis of data analysis also leads to the characterization of the data elements in an easy way to understand. Moreover, it is also important to consider the utilization personal interpretations, viewpoints, anecdotes and experiences. For instance, "during the analysis of data one action researcher, who carried out an intervention project to enhance the aspirations of pupils in an inner-city school, used student profiles and her own diary entries to create an authentic story of what happened" (Koshy, 2005). In this particular case, the research uses real time recording to analyze the student profiles and establishing key connection points. Data analysis also relies heavily on the categorization and coding elements used in the data.
Various management systems can be used in establishing ensuring that the research objectives are being met. One of the most suitable management systems is the performance management criterion. This system leads to the establishment of critical techniques that are used in guiding the respective research processes. The system has various advantages. First, it encourages practitioners to show commitment and focus on the assessment framework for their work (Whitehead and McNiff, 2006). This has a positive impact in ensuring that the desired action research deliverables are achieved correctly. McNiff and Whitehead observe that performance management enables research findings to become available to peer action researchers and the broad academic education research community (Whitehead and McNiff, 2006). This leads to the recognition of the contributions of the action research into the respective field of interest. However, the performance management also has significant disadvantages associated with the system. The most prominent disadvantage is the prolonging of the research process due to the focus given to the details.