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Qualitative Data Analysis
Following interviews and document collection, final quantitative analysis was conducted. The researcher read and coded interview data and documents, using documents to provide deeper understanding, answer clarifying questions generated from
coding, and to confirm, inform, and shape interview data coding. Following qualitative analysis of interviews and documents, quantitative data were reintroduced to refine emerging codes and themes. At that point, both quantitative and qualitative data were combined for interpretation and analysis.
Interview data analysis. Using the interview protocol, all digital recordings of interviews were transcribed by the researcher. Since the interviews were semi-structured, follow-up questions and responses were transcribed for those records. Because a digital recorder was used, the researcher used digital pitch control to adjust the speed of the recording. This allowed the researcher to more accurately transcribe the recording. The researcher also used pause, rewind, and repeat features during transcription to maximize accuracy.
Because participants were promised confidentiality, pseudonyms were used throughout the transcript for people and places that could reveal the identity of any of the participants or other people or places they named in their responses. Ellipses were used to denote pauses in responses and asterisks were used to denote words or phrases that were not clear or could not ascertained. Bolded text was used for words or phrases spoken with emphasis. Following the initial transcription, all digital recordings were played two additional times while reading the final transcript to ensure accuracy. Once the researcher confirmed accuracy of the transcript, any field notes taken during the interview were added to the transcript. These notes helped assess the quality of the data obtained through interviews, which Merriam (1988) suggests is important for interview data analysis. For any field notes indicating personal demeanor, nonverbal cues, or physical expressions, such as hand quotation marks, the researcher attributed those to specific phrases, words,
or questions. These notes, along with the interview transcripts, helped assess the quality of the data obtained through interviews.
Creswell and Plano Clark (2007) suggest that qualitative analysis begins with coding the data. Coding involves “grouping evidence and labeling ideas so that they reflect increasingly broader perspectives” (p. 132). So, data were grouped into codes, and then codes were grouped into broader themes. Themes can also be grouped into even larger dimensions or perspectives as they are related or compared to one another. For this reason, interview data analysis mimicked an iterative process involving reading and coding, followed by a categorical aggregation of themes emerging from the codes. In this way, the researcher has “...observed a sufficient number of occurrences of an event, process, or activity to constitute grounds for a valid generalization” (Stebbins, 2001).
Though an issue or concept identified from the data may align with presidential decision making, the meaning of the issue did not yield qualitative weight unless additional instances of the same issue or concept emerged from the data.
Interview transcripts were compiled into a single file, and as suggested by Creswell and Plano Clark (2007), codes were recorded in the left margin and broader themes were recorded in the right margin. The researcher read and coded interview data. Following initial coding, the researcher compiled all codes and grouped similar codes together. Following the first round of interview coding, the researcher began reading documents in order to provide explanation, clarification, and context for interview data.
Using the grouped codes developed from the first round of interview coding, the researcher read and coded interview data a second time to further refine codes and identify emerging themes. Following the second round of interview coding, the
researcher continued to group codes, noting the frequency of specific codes and again, continued reading documents. Also, because the purpose of interviews was to further explore how the KCTCS president and college presidents share academic, administrative, and personnel decision making, as well as explore how external state influences on this decision making and what the role of the KCTCS Board of Regents and boards of directors is in decision making, the researcher grouped codes by decision area and by research question following the second round of coding.
The researcher used the refined and grouped codes by decision area and research question from the second round of interview coding to further explore particular issues and concepts that could be identified as emerging themes. By framing the codes by decision area and research question, the researcher could more clearly identify themes that emerged from the data cumulatively, but also themes that emerged according to sets of interview questions and their corresponding research questions. Following the second round of interview coding, the researcher continued reading documents in order to provide explanation, clarification, and context for interview data, as well as to refine codes and themes.
Using the refined and grouped codes by decision area and research question, the researcher conducted a third round of coding. The purpose of this round of interview coding was to further hone emerging themes, ascribing particular language to effectively describe them and examining relationships between themes. The researcher read and reviewed documents throughout interview data analysis. This simultaneous approach to interview and document analysis involved an iterative process of reading and coding interview data, followed by reading and coding documents, and then returning to reading
and coding interview data again. Naturally, the codes identified through interview analysis were applied to document analysis, though the data were not yet mixed for interpretation.
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