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SI Leader (fellow scholar):

Cornell Jones

SI Psych 7868 We now return from our adventure to analyze… Unit 8ab

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Hello and welcome to week 8. Now we are on to Data Analysis and two great articles to take a look at are in the File Share Pod: DataAnalysisMethod.pdf and 9602312_Qualitave Data AnalysisChap17.pdf

Exploration Map

Warm Up:

What’s Next Scenario

Evaluating Data Analysis

Article Review

Thematic Analysis Overview

Group Exploration: Data Analysis Spiral

Traveler’s Log / Tip of the Day

Our next journey

Cool Down and Recover

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Warm up

Imagine your friend and fellow scholar at Capella has approached you for some advice.

Yo fellow scholar! So I’ve just finished collecting data for a qualitative study investigating Psych7868 at Capella. I have data from interviews with four professors and ten students as well as ten hours of observations. But I’m not sure what to do next?

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What would you suggest?

Would there be more information you would want to know before you could help Bob?

What would Bob’s first step likely be ?

Ok well we are going to be looking at this process throughout the week so let’s start by looking at the readings

Readings Discussion

Patton 431–534

Creswell: Chapter 8

Read the document

‘Data Analysis’

Review data analysis sections of qualitative articles

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Now it is only Tuesdaty but has anyone got started with the readings

Patton highlights the analysis and interpretation of data in qualitative research

Creswell should focus on subsections:

"Three Analysis Strategies."

"The Data Analysis Spiral."

"Analysis Within Approaches to Inquiry."

Let’s take a look a few selections from our text to set the tone for this week

Words of Wisdom

“Qualitative analysis transforms data into findings. No formula exists for that transformation” (Patton, 2002, p. 432).

What is the purpose of data analysis?

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What do you think Patton might say?

Words of Wisdom

“Description forms the bedrock of all qualitative reporting…” (Patton, 2002, p. 438)

What is the fundamental aspect of qualitative reporting?

Qualitative Reporting

Description!

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Again what might Patton’s view be?

Words of Wisdom

“The processes of data collection, data analysis, and report writing are not distinct steps in the process—they are interrelated and often go on simultaneously in a research project” (Creswell, 2007, p. 150).

How does the process of data analysis happen?

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Now how about Creswell or your thoughts on this

But we will see as we go through the readings that pretty much all the approaches cover three or four processes although in different ways

Ok so now lets look at our first discussion post

Four Objectives of Data Analysis

How do you see the process of data analysis unfolding?

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Where would you guys start with Data Analysis ?

Remind that there are both general processes that are implied in all qualitative research and more specific processes that apply to each methodology and require research of primary sources such as

Giorgi and Moustakas for phenomenology.

Moustakas for heuristics.

Strauss and Corbin, and Charmaz for grounded theory.

Stake and Yin for case study.

Ok lets take a look at the first discussion post for this week *

Four Processes of Data Analysis

How can we think of the interrelated processes in data analysis?

Managing

Memoing

Describing

Classifying

Interpreting

Representing

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Many different ways but from last session * we see prepare, code, theme, represent

The process of managing and memoing is similar across all methods

And in Creswell p. 156 we can * manage, memo . . . And these processes are interrelated or multidirectional *

Also on p. 151 remember Creswell relates the data analysis process to a spiral * for next slide

Data Spiral Analysis

Representing

Visualizing

Matrix, Trees,

Propositions

Describing,

Classifying,

Interpreting

Context,

Categories,

Comparisons

Reading,

Memoing

Reflecting,

Writing Notes

Across Questions

Data

Managing

Files,

Units,

Organizing

Data Collection (text, images)

(Creswell, 2007)

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And the last slide I want to review for last session is the thematic analysis types * click for next slide

P 183 creswell

u08d1 Data Analysis

Describe the data analysis section from a qualitative dissertation or research article

Evaluate effectiveness of data analysis strategy, discussing strengths and limitations.

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How to Evaluate Data Analysis?

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So even though we have not probably had a chance to get through the readings any tips on how to evaluate Data analysis?

Are steps clearly outlined

Is conceptualization of themes/categories coherent

Triangulation?

Relevant to RQ?

Relevant to methodology?

Do findings have any significance?

Are analysis methods referenced?

Have steps been taken to protect data

Before clicking for answers use whiteboard?

Use Creswell 190-191 as a frame of reference and Patton 466-467 to help evaluate along with respective sections depending on the methodology

Think about triangulation

When finding an article check for RQ then Data Analysis and then Analysis and Results

Let’s take a look at an article quickly to get an idea*

Qualitative Data Analysis

"…thematic analysis involves the searching across a data set – be that a number of interviews or focus groups, or a range of texts – to find repeated patterns of meanings" (Braun & Clark, 2006, p. 86).

What form of data analysis spans all of qualitative research ?

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Thematic analysis is the overarching approach to find patterns in data resulting from qualitative inquiry.

Thematic analysis

How about the three types of thematic analysis acceptable for qualitative research at Capella University?

Inductive analysis

Theoretical analysis

Thematic analysis with constant comparison

(Percy & Kostere, 2008, p. 9)

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Extra ref: Abductive reasoning about the data starts with the data andsubsequently moves toward hypothesis formation (Deely, 1990; Fann, 1970;Rosenthal, 2004)

Inductive Analysis

(Percy & Kostere, 2008, p. 9)

Capella Track 3 Guide

Why would you want to use inductive analysis?

To avoid bias and data having an inter-participant effect on data from other participants. To allow themes to emerge.

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Inductive analysis is data driven and does not attempt to fit the data into any preexisting categories. The researcher sets aside all pre-understandings. The data collected from each participants (interviews, observations, open-ended questionnaire, etc.) are analyzed individually. Once the data from all participants have been analyzed, the repeating patterns and themes from all participants are synthesized together into a composite synthesis, which attempts to interpret the meanings and/or implications regarding the question under investigation (Percy & Kostere, 2008).

Step by Step (Percy & Kostere, 2008)

Review the data collected. Read and highlight sentences or phrases, or paragraphs that are meaningful.

Use research question to review the highlighted data.

Capella Track 3 Guide

Delete irrelevant information

Code data

Patterns should be clustered

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Review and familiarize yourself with the data collected. Read and highlight intuitively any sentences or phrases, or paragraphs that appear to be meaningful.

Review the highlighted data and use your research question to decide if the highlighted data are related to your question.

But keep deleted information

4. The code can be simple. You are tracking individual items of data.

Cluster the related or connected in some way and develop patterns. For each pattern, describe it in a phrase or statement, or code. (Your words)

Step by Step (Percy & Kostere, 2008)

Capella Track 3 Guide

Identify detailed pattern

Search for themes

Arrange themes

Write a short analysis describing themes

Repeat process for each participant

Combine all patterns and themes

Synthesized all data as it relates to the research question

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Place them in clusters created in step 5. Themes are patterns of patterns. After all data has been analyzed, arrange the themes in a kind of matrix with their corresponding supportive patterns. For each theme, write a detailed abstract analysis describing the scope and substance of each theme.

Complete the process for each participant.

Then combine the analysis of data for all participants including patterns and themes that consistent across the participants’ data.

The data are synthesized together to form composite synthesis of the data collected regarding the research question.

Theoretical Analysis

(Percy & Kostere, 2008, p. 9)

Capella Track 3 Guide

Why would you want to conduct theoretical analysis ?

Same as inductive except themes have already been determined by theory and research question.

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In this situation, the research may use his/her preunderstandings when conducting the data analysis. However, in this case the research also remains open to the possibilities of new themes emerging from the thematic analysis. The theoretical thematic analysis is driven by theory and the themes that are predetermined are usually located in the research question. Thus, the research question will have identified concepts from theories on the topic under inquiry. The data collected is analyzed individually and patterns that emerged from the data will be organized under the appropriate preexisting themes keeping in mind that new patterns and themes may also emerge from the data during the data analysis process.

Step by Step

Review the data collected. Highlight meaningful data. Remember there will be predetermined themes from the research question.

Use research question to review the highlighted data.

Delete irrelevant information

Code data

Capella Track 3 Guide

(Percy & Kostere, 2008, p. 11)

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Review, and familiarize yourself with the data collected. Read and highlight intuitively any sentences or phrases, or paragraphs that appear to be meaningful. Keeping in mind the predetermined categories (themes) that are related to the theory and research question posed as well as remaining open to any new patterns.

Review the highlighted data and use your research question to decide if the highlighted data are related to your question.

Patterns should be cluster

Preexisting theme are clustered with all other themes

Completely new emerging themes should be kept separate

Repeat steps 1 -7 for all participants

Search for overreaching themes

Capella Track 3 Guide

(Percy & Kostere, 2008, p. 11)

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Cluster the items of data that are related or connected in some way and develop patterns.

Patterns that are related to a preexisting theme are placed together with any other patterns that correspond with the theme along with direct quotes taken from the data to elucidate the pattern.

Arrange themes

Review separated themes

Write a short analysis describing themes

Synthesize data

Capella Track 3 Guide

(Percy & Kostere, 2008, p. 11)

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Arrange themes to correspond with the supporting patterns. The patterns are used to elucidate the themes.

Revisit the patterns that did not fit the preexisting categories an remain open to any new patterns and themes that are related to the research topic and have emerged from the data analysis.

For each theme, the researcher needs to write a detailed analysis describing the scope and substance of each theme.

Thematic Analysis with Constant Comparison

(Percy & Kostere, 2008, p. 9)

Capella Track 3 Guide

Why would you want to conduct constant comparisons?

To allow analysis to change and grow from one source of data to the next.

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Thematic analysis with constant comparison can be either inductive analysis or theoretical analysis. The difference is that the data collected are analyzed as they are collected. The analysis begins during the collection of data. The first participant’s data are analyzed and as each subsequent participant’s data are analyzed, they are compared to the previously analyzed data. The analysis constantly moves back and forth between current data and the data that have already been coded and clustered into patterns. Patterns and themes will change and grow as the analysis continues throughout the process.

Step by Step

Review the data collected. Highlight meaningful data. Remember there will be predetermined themes from the research question.

Use research question to review the highlighted data.

Delete irrelevant information

Code data

Capella Track 3 Guide

(Percy & Kostere, 2008, p. 11)

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Review the highlighted data and use your research question to decide if the highlighted data are related to your question.

Step 5

“The researcher will code and cluster the first participant’s data and as each subsequent participant’s data are analyzed, they are compared to the previously analyzed data. Throughout this process, each participant’s data are reviewed and analyzed, and the researcher is comparing and contrasting the data being analyzed with the data that have been previously analyzed in the study. Thus, a constant comparison emerges” (Percy & Kostere, 2008, p. 12).

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Identify detailed pattern

Search for overreaching themes

“Patterns and themes may tend to shift and change throughout the process of analysis” (Percy & Kostere, 2008, p. 12)

Capella Track 3 Guide

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Arrange data according to theme.

Write a short analysis describing themes

“Each pattern should be described and elucidated by supporting quotes from the data” (Percy & Kostere, 2008, p. 12)

Synthesize data

Capella Track 3 Guide

(Percy & Kostere, 2008, p. 12)

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Ok before we preview the assignment lets take a look at a research question in the collaboration room

u08a1 Data Analysis Strategies

Develop a step-by-step strategy for data analysis

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u08a1 Data Analysis Grading Rubric

Develop a strategy for data analysis consistent with RQ and methodology.

Describe strategy for data analysis in a step-by-step format.

Use consistent language to describe research design and data analysis plan.

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Ethnography Data Analysis

How does ethnographic analysis unfold?

Describe<->Analyze<->Interpret

Discover representative themes

Can focus on “life stories”; a key event; or most often, shared cultural patterns

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The process of managing data and memoing is similar across all methods per Creswell 156

Ethnographic thematic analysis and exemplary life histories

Ethnography shares a essential technique of data analysis, namely thematic analysis.

Ethnographic reports assemble “life stories” of culture, group or organization. The object is to collect data that uses their experiences to demonstrate significant themes and individual points of view. These life stores are historic and seizes the person’s emotions and perceptions concerning the culture, group or organization and research question.

Ethnographic reports, one common – though by no means required – presentation practice is to construct “life stories” of representative or exemplary participants in the culture, group or organization. The object is not to single out the individuals' for study, but to use their experiences to exemplify key themes and unique perspectives found in the data. These representative life stores are not standard biographies or life histories, but instead life hisotries capture the person’s own feelings, views and perspectives regarding the culture, group or organization and research question.

The data gathered in this ethnographic study of DCP, will be prepared in several ways as described by Creswell (1998). Transcripts of audio taped interviews were prepared by a licensed stenographer contracted to produce the documents within one week of the completed interview. These transcripts were labeled with code to denote the specific participant from which the information was gained. Field notes were collected and categorize in a fashion consistent with the field experience, in chronological order. All artifacts were labeled with codes to provide identification specific to the item as it relates to the owner, how the item was obtained, and information provided by participants concerning the item. (Mueller, 2009)

Field notes were collected and categorize in a fashion consistent with the field experience, in chronological order. …. (Mueller, 2009)

Transcripts of audio taped interviews were prepared by a licensed stenographer contracted to produce the documents within one week of the completed interview.

The data gathered in this ethnographic study of DCP, will be prepared in several ways as described by Creswell (1998).

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What does this first ethnographic slide discuss overall? What part of analysis? --preparing

This ethnography used data to identify the culture of the DCP who participate in this study. The meaning of the data to the work setting of these participants in terms of the communication, beliefs, language, relationships, and rituals is preserved within the data.

The data was prepared by initially reviewing the interview transcripts, field notes, and artifacts a minimum of three times. During each review, margin notes were taken of the transcripts of interviews and to the field notes collected. Memos were developed for each artifact collected.

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How about the first para? What is the author trying to do? – connect to the RQ

How about the second para? Step by step and memoing

Following the review of the data in total, as described in the preparation section, the data will be analyzed using NVIVO8 software program. The intent of the analysis will be to derive five to six themes found within the data that provide description of the work group culture. Visualization of the themes was node charts with data items that provide the best representation of the themes, e.g., verbatim quotes from interview transcripts, text from the training material, and description of artifacts. The themes guided interpretation of the cultural phenomenon as it relates to the specific participants and settings in which the data regarding the DCP was collected.

Visualization of the themes was provided using node charts with data items that provide the best representation of the themes, e.g., verbatim quotes from interview transcripts, text from the training material, and description of artifacts.

The intent of the analysis will be to derive five to six themes found within the data that provide description of the work group culture.

Following the review of the data in total, as described in the preparation section, the data will be analyzed using NVIVO12 software program.

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What is the overall notion of this paragraph? –coding and themes (after preparation)

First sentence …how about using software

Second sentence… will you discuss the purpose of your approach

Last sentence …will you discuss data presentation

Creswell (1998) advises the use of a “data analysis spiral” in conceptualizing data used in qualitative research (p. 143). The data was organized in files and units along with reflections, note taking, and memos about the data. The data were categorized and comparisons were formulated. Descriptions, classifications, and interpretations were established. Lastly, a visualization or representation was created from the qualitative data. Within each step, the researcher returned to the previous level of analysis as needed in eventual culmination of an account of the phenomena examined.

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What is the implication of the last paragraph? –interpretation

Go full screen and ask learners to identify the purpose of the last paragraph

Case Study Data Analysis

How does case study analysis unfold?

describe<->aggregate<->interpret<->patterns<->generalizations

Develop naturalist generalization

Focus on defined case (bounded system)

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Very similar process to ethnography

Case study is iterative (it-er-a-tive) in nature (Yin p.143)

Check to see if they can identify the complete names aggregate, interpret and generalizations

Describe the case, categorical aggregation, direct interpretation, thematic analysis, naturalistic generalizations

Important to know the language of each methodology although the processes are quite similar

Quote “The quantitative side of me looked for the emergence of meaning from the repetition of phenomena. The qualitative side of me looked for the emergence of meaning in the single instance” (Stake, 1995, p. 76).

Case Study Data Analysis

Capella Track 3 Guide

(Percy & Kostere, 2008, p. 19)

Analysis of the entire case is often called

Analysis of a certain aspect of the case is often called

Embedded analysis

Holistic analysis

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Direct Interpretation – the case study researcher looks at single instances in the described data and draws meaning form each without (yet) looking for multiple instances.

Categorical Aggregation – the researcher seeks a collection of meaning-rich instances from the data, aggregating these into categories of meaning.

This process pulls the described data apart and puts them back together in more meaningful ways

In this case study, two types of data collection were used before the analysis procedure began. The principal method of data collection in case study research was the in-depth interview, although observational field notes were also used. Stake suggested the interviewer should arrive at the arranged interview site with a small list of issue-oriented questions and suggested providing the participant with a copy of the list, proposing a concern about completing a schedule. Stake (1995) further declared, “Formulating the questions and anticipating probes that evoke good responses is a special art” (p. 65). (Hall, 2010)

Stake suggested the interviewer should arrive at the arranged interview site with a small list of issue-oriented questions…

In this case study, two types of data collection were used before the analysis procedure began. The principal method of data collection in case study research was the in-depth interview…

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What is this first slide about ? – data collection might be briefly summarized in the data analysis section for context

First sentence ….. Should we briefly discuss data collection

Second sentence ….what about the interview process?

Stake‘s (1995) collective case study design was used for this qualitative inquiry for the collection procedures and as the basic guide throughout the research process. This constructivist paradigm allowed the human subjective meaning to flow into the dynamics of the research, as the participant‘s experience was the answer the researcher was seeking (Baxter & Jack, 2008). Only through rich, descriptive stories, told by each participant, would the researcher then be able to sort and analyze the data as the themes and patterns emerged (Hanke, 2006; Preece, 2008; Stake, 1995).

This constructivist paradigm allowed the human subjective meaning to flow into the dynamics of the research, as the participant‘s experience was the answer the researcher was seeking (Baxter & Jack, 2008). Only through rich, descriptive stories, told by each participant, would the researcher then be able to sort and analyze the data as the themes and patterns emerged (Hanke, 2006; Preece, 2008; Stake, 1995).

Stake‘s (1995) collective case study design was used for this qualitative inquiry for the collection procedures and as the basic guide throughout the research process.

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W hat is the objective of this second part? Introduce the model and objective of data analysis

First sentence …….introduce model and primary source

Second sentence ……….objective or rationale

In simple format, the following procedure transpired:

During a face-to-face interview with each participant, data collected from the interviews were taken from the digital recordings and transcribed to typewritten form by a professional typist.

The field notes were informal handwritten notes, summarized by the researcher. These were also transcribed by the professional typist.

Member checking was used to ensure the researcher had interpreted the data correctly. She visited with each participant and shared the data with them individually. At that time, each participant had the opportunity to clarify the interpretation with the researcher and could also contribute additional perspectives on the study, if they so desired (Baxter & Jack, 2008).

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What is this slide about? Step by step process

Lets take a look at the last bullet here….what do you think about member checking?

Stake‘s model did not really have a set procedure for analyzing collective case studies, except to explain that the researcher may analyze within each setting or across settings, in an effort to understand the similarities and variations between the cases (Baxter & Jack, 2008). For this reason, a thematic analysis was used for the remaining procedure of analyzing the data.

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What is the main idea of this slide? – how to address when your model does not include something.

Thematic analysis has been considered to be flexible and, therefore, worked very well with Stake‘s model of qualitative inquiry. As Braun and Clarke (2006) assured, “Thematic analysis provided a flexible and useful research tool, which can potentially provide a rich and detailed, yet complex, account of data” (p. 78). Identifiable themes and patterns were reported within the data during the analysis phase (Aronson, 1994; Braun & Clarke, 2006). A theme captured something important about the data and symbolized a level of a patterned response within the data set. In other words, the themes emerged from the data. It was up to the researcher to decide what the patterns and themes meant because there was no rigid rule as to what made up a theme (Braun & Clarke, 2006). Hall (2010)

Identifiable themes and patterns were reported within the data during the analysis phase (Aronson, 1994; Braun & Clarke, 2006). A theme captured something important about the data and symbolized a level of a patterned response within the data set. In other words, the themes emerged from the data. It was up to the researcher to decide what the patterns and themes meant because…

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So this is the end of Hall’s data analysis and is there anything that you would add?

What grade would you give him or her?

Grounded Theory Coding

Capella Track 3 Guide

Saturation of categories w/constant comparison

Propositions or hypotheses explaining codes are developed

Open

Coding

Selective Coding

Regrouping of data into central phenomenon categories

Axial

Coding

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Open coding—breaking down

Axial—Reassembling

Selective—Connecting and competing theory

Individual and focus group data were analyzed concurrently, looking for all possible interpretations employing coding procedures. Coding consists of naming and categorizing data. Coding is defined as the analytic process through which “data are fractured, conceptualized, and integrated to form theory” (Strauss & Corbin, 1998, p. 3).

Open Coding

The first process was open coding, which is breaking down the data into separate units of meaning. The process of developing categories is called the constant comparative procedure (Creswell, 2002). This method is a fundamental feature of grounded theory. Comparison explores differences and a similarity across incidents within the data collected, and provides guidelines for collecting additional data. Comparing each incident in the data with other incidents appearing to belong to the same category while exploring their similarities and differences, this process can reduce and group data into meaningful categories (Strauss & Corbin, 1998).

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Categories are named from the analysis of data and described in relationship to the features of the phenomenon under study. The properties of a category are dimensionalized, by placing or locating the properties along a continuum within a range of possible values (Strauss & Corbin). Recordings were open coded using ATLAS.ti. The individual interviews and focus group recordings were conceptualized line by line by the researcher. Several concepts were constructed out of the data, breaking the data into manageable pieces. The pieces of data were explored for ideas contained in interpreting the data. Conceptual names that stood for and represented the properties contained in the data, which defined and described the concepts, were identified by the researcher. Dimensions (variations within properties) that give specificity and range to concepts were compared and merged into new…

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Notice that each step of coding is very clearly outlined

Words like dimensionalized are specific to grounded theory

Open coding takes us to the point where we have named categories of data that are specified on a continuum

Axial coding, the appreciation of concepts in terms of their dynamic interrelationships, was the next stage of coding. The focus of axial coding is to construct a model that details the specific conditions that give rise to a phenomenon’s occurrence. It involves putting the data together in new ways using a coding paradigm, a system of coding that identifies causal relationships between categories, making explicit connections between categories and subcategories. This process involves explaining and understanding relationships between categories in order to understand the phenomenon to which they relate, and reassembles the data …

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One of the things I like about grounded theory is that the steps are very clearly outlined

The third and final step was selective coding. This is the process of selecting and identifying the core category (ies) around which all other categories are based and systematically relating them to other categories by validating the relationships, filling in, refining, and developing the categories. Theoretical codes integrate the theory by weaving the fractured concepts into hypotheses that work together, developing a theory of the motivations of doctoral learners. Selective coding identified the core categories of achievement, determination, and persistence. These categories were systematically related to other categories, validating, refining, and developing those categories. Selective coding consists of integrating and refining the theory that is organized around the central category (ies). … Williams (2009)

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Another example of this coding is available Creswell p. 285

Phenomenology Data Analysis

How does phenomenological data analysis unfold?

epoch<->horizonalization<->meaning units<->textual description<->structural description <->Combined description

Focus on the essence of a common experience

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Phenomenology is trying to locate shared mechanisms in consciousness

What is the first thing we need to usually do with phenomenology and heuristics?—epoch and then phenomenological reduction (Patton, p. 485)

Horizonalization: after bracketing all data aspects are treated with equal value

finds significant statements and achieve a sense of the whole. Read the entire description in order to get a general sense of the whole statement.

Discrimination of Meaning Units with in a Psychological Perspective and Focused on the Phenomenon being researched. Re-read text and delineates ach time that a transition in meaning occurs.

Explores the “what” (textual) and the “how” (structural) Creswell p. 159) and begins to transform the subjects everyday expression into psychological language with emphasis on the phenomenon being investigated. Once meaning units have been delineated and linked, the researcher goes through all of the meaning unit, which are still expressed in the language of the participant, reflects on them, and comes up with the essence of the experience for the participant. Each relevant unit’s essence is transformed into the language of psychological science.

Synthesis of transformed meanings units into a consistent statement of the participant’s of the experience.

Final synthesis includes all of the essence or structure statements regarding each participant’s experience into one consistent statement, which describes and captures the essence of the experience being studied.

The researcher used phenomenological research methods as described by Moustakas (1994). Phenomenological methods were followed for the data collection and analysis. There are four stages to data analysis in transcendental phenomenology: epoche', transcendental phenomenological reduction, imaginative variation, and the synthesis of composite textural and composite structural descriptions into a universal textural structural description of the phenomenon (Moustakas, 1994).

The universal description of the essence of the lived experiences of African American college students diagnosed with ADHD emerged from the data that was collected during the interviews. . .

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Please note that there are three modles of phenomenolgoical analysis in file share doc: Empirical Phenomenology, Transcendental Phenomenology, Stevick-Colaizzi-Keen Method of Analysis of Phenomenological Data

So what do you guys think of the first para? –states the modle

Second para? Refers back to the RQ

After the information from the interviews was transcribed, they were analyzed using methods described by Moustakas (1994). The first procedure is epoche'. The researcher sets aside all biases toward the phenomenon during the epoche’ process. This allowed the researcher to view the phenomenon from a fresh perspective. The next stage of transcendental phenomenological data analysis, phenomenological reduction, consisted of developing textural descriptions of the phenomenon. This was accomplished by the researcher examining the transcribed text line by line. Meaning units were discovered during this process. The meaning units were then clustered into common themes. ..

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Validity checks were conducted after each of the participant’s textural-structural descriptions of their experiences was developed. The individual’s textural –structural descriptions were submitted to the participants for review. Five out of the total eight participants were contacted for the validity check. Each of the participants reviewed their own individual textural-structural descriptions. Participants were asked to review the textual structural descriptions for accuracy and completeness. Participants were permitted to modify, add or delete, and /or change the parts of the description to ensure that the researcher had fully captured the essence of his or her experiences. There were no modifications requested by the participants.

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After the validity checks, the individual textural themes were then synthesized into a composite textural description of the experience of African American college students diagnosed with ADHD. The composite textural description entailed the common characteristics and themes that emerged from all of the participants in the research. The individual structural themes were synthesized to develop a composite structural description of the participants as whole. The composite structural description provides information about the universal structures of the participants as a group. Finally, the composite textural and composite structural descriptions were synthesized to develop a composite textural-structural description of the phenomenon... Poe (2011)

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Heuristic Data Analysis

How does heuristic data analysis unfold?

engagement->immersion->incubation->illumination->explication->synthesis

Focus on the essence of a shared experience

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“Data collection, in a heuristic inquiry, often is integrated with data analysis, because personal reflection is an integral part of every stage or phase of the processes. While there will be activities which clearly are “data collection” vs. “data analysis,” at times the distinction is not so clear” (Percy & Kostere, 2008, p. 35).

Evaluating Data Analysis

Are steps clearly outlined

Is conceptualization of themes/categories coherent

Triangulation?

Relevant to RQ?

Relevant to methodology?

Do findings have any significance?

Are analysis methods referenced?

Have steps been taken to protect data

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Use Creswell 156-157 as a frame of reference and Patton 466-467 to help evaluate along with respective sections depending on the methodology

Think about triangulation

Choosing a strategy

There are countless strategies for data analysis so how will you decide?

Purpose

Methodology

Resources

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Must consider your RQ, purpose, and methodology as well as resources

What did you observe in your week 1 expedition?

Travelers Log

Remember that there are both general analytic strategies and specific strategies!

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Patton’s themes

Match discussion questions to different SMR sections

Our Next Adventure!

How will you present your data?

How much data will you present?

What will be your role as a researcher and how will you define that role in the final project

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Considerations

Read Creswell 148-158 (then find section for your methodology)

Review Patton’s ‘Options for Organizing… p. 439

Plz review Patton p. 440-441 to get a real sense of the work

Review ‘Data Analysis’ link

What types of themes do you expect to find?

Will codes be emergent/inductive or a priori /pre-existing/prefigured?

Think about software

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p. 156 to start

Experiences, stories, emotions, events, occurrences, interactions

See Creswell p. 152 for more on emergent or a priori

‘Data Analysis’ link provides content adapted from Qualitative Research Approaches in Psychology

For software read Creswell p. 164-173 (It would be helpful to reference at least what seems appropriate at this point) in reality spending several days investigating appropriate software may save you months later

Warm-up: Data Analysis

1. On average 10 two-hour interviews will produce about how many single-spaced pages?

1. 10-20

2. 200-300

3. 1-5

4. 1000-2000

Patton, 2002, p. 440

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So how do you guys feel about that?

What implications does that have on your research design?

Warm-up: Data Analysis

2. What type of coding may limit data reflecting views of participants?

1. Open coding

2. In vivo codes

3. Axial coding

4. A priori coding

Creswell, 2007, p. 152

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What is the fourth way? Fill a gap in the knowledge

Warm-up: Data Analysis

3. What methodology often begins with a description of personal experiences?

Ethnography

2. Case study

3. Phenomenology

4. Grounded theory

Creswell, 2007, p. 156

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If you are not sure on some of these take a look at the introduction for Unit 7 in courseroom

Warm-up: Data Analysis

4. What methodology would have a researcher use a conditional matrix for interpretation of data?

Case study

2. Ethnography

3. Grounded Theory

4. Heuristics

Creswell, 2007, p. 156

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Warm-up: Data Analysis

5. Grounded theory would be more likely to use what type of thematic analysis?

1. Inductive

2. Theoretical

3. Constant Comparison

4. Historical

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For example : What is the process of becoming addicted to Facebook?

P. 160 Creswell

Warm-up: Data Analysis

6. What methodology does not often begin with a description of the phenomenon?

Case study

2. Ethnography

3. Grounded Theory

4. Heuristics

Creswell, 2007, p. 164

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Warm-up: Data Analysis

7. ‘Meaning units’ is an analytic term relating to what methodology ?

Case study

2. Ethnography

3. Grounded Theory

4. Heuristics

5.Phenomenology

Creswell, 2007, p. 159

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Warm-up: Data Analysis

8. A key term in grouping data for heuristic methodology is ?

Aggregation

2. Axial Coding

3. Explication

4. Meaning Units

5.Open coding

Creswell, 2007, p. 159

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Cool Down

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Grounded Theory Data Analysis How does grounded theory analysis unfold? open coding<->axial Coding<->selective coding

Explain process of something

Focus on explanation and theory

Grounded Theory Data Analysis

How does grounded theory

analysis unfold?

open coding<->axial Coding<->selective

coding

Explain process of something

Focus on explanation and theory