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Running head: DATA ANALYSIS AND APPLICATION TEMPLATE
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DATA ANALYSIS AND APPLICATION TEMPLATE 7
[8a1] Unit 8 assignment 1
Course: PSY7864
Instructor: Gennaro Ottomanelli
Date: 3/04/2019
Data Analysis and Application (DAA) Template
Section 1: Data File Description
Data set collected by a teacher across three class sections with each section consisting of about 35 students (N = 105). The student data is comprised of student demographics and performance which is based on a selection of quizzes, final and a total score within the class. Twenty-one variables were assigned overall, with student gender (1= female; 2= male) using the nominal, or categorical, scale of measurement consisting of 41 males and 64 females while GPA (previous grade point) is employ a ratio measurement. The variable gender is a dichotomous (categorical) variable with two categories (male and female) whereas GPA is continuous and has a quantitative value. The measurement scale for gender is nominal scale whereas GPA is ratio scale (Warner, 2013).
Section 2: Testing Assumptions
The assumption that are required to be made before running a statistical t test analysis is that the response variable Y must be quantitative and approximately normally distributed, i.e. it must be normally distributed when the sample size is less than 25 observations. Another assumption is the homogeneity of variance, which states that the variance of the response variable Y is approximately equal across the observations (groups), i.e., the observation that are being compared must show equal variance. There must be independence both between and within groups for the t test to be appropriate. In this case, Gender and GPA must be independent from each other. The last assumption is the robustness of the violation of the assumptions especially when the sample size is too small. In our case, the sample size is the equal and large enough, hence, this assumption is met (Warner, 2013).
From the histogram above, it clearly indicates that the GPA score is approximately normal although it is slightly left-skewed hence the normality assumption is met. Much of the data lie within the superimposed normal curve.
Descriptives
Statistic
Std. Error
gpa
Mean
2.8622
.06955
95% Confidence Interval for Mean
Lower Bound
2.7243
Upper Bound
3.0001
5% Trimmed Mean
2.8873
Median
2.8400
Variance
.508
Std. Deviation
.71266
Minimum
1.08
Maximum
4.00
Range
2.92
Interquartile Range
1.19
Skewness
-.220
.236
Kurtosis
-.688
.467
The skewness of the data indicates that the data is slightly left-skewed. Since 0.236*3 = 0.708 > |-.236|, then the data is approximately normally distributed. Kurtosis describes the flatness of the data. With kurtosis -1.0 < -0.688 <1.0, the data is thus approximately normal as also supported by .467*3 = 1.401 > |-.688|.
Tests of Normality
Kolmogorov-Smirnova
Shapiro-Wilk
Statistic
df
Sig.
Statistic
df
Sig.
gpa
.100
105
.012
.961
105
.004
a. Lilliefors Significance Correction
The Shapiro-Wilk test is .961 with a p value .004 < 0.05. It indicates that the GPA data is not normally distributed since the p (.004) value is less α (.05). Although .961 is quite close to 1, the p value is far much lower that α, hence the normality test is violated.
The Levene test result is .758 when equal variance is assumed. Since .758 > .05, the we can conclude that the variability between the gender and grade is not statistically significant. Therefore, equal variance is assumed (George, D., & Mallery, P., 2016).
From the analysis above, it is evident that the GPA data is normally distributed because the normality assumption are met by the graphical representation using histogram and the skewness and kurtosis. The assumption of homogeneity of variance is also met supporting the normality of the data.
Section 3: Research Question, Hypotheses, and Alpha Level
Research question: Is there a significant difference between GPA score for Male and Female?
Null Hypothesis (H0): There is no significant difference between the GPA score of Male and Female
Alternative Hypothesis (H1): There is a significant difference between the GPA score for Male and Female
Alpha level is 0.05
Section 4: Interpretation
Group Statistics
gender
N
Mean
Std. Deviation
Std. Error Mean
gpa
1
64
2.9719
.67822
.08478
2
41
2.6910
.73942
.11548
The result above was done to test the homogeneity of variance between both genders relative to the GPA score together with the descriptive statistics for both groups. The difference between the means of groups (M1 – M2) = (2.9719 – 2.6910) = 0.2809 GPA. Therefore, the difference between the least score and highest GPA score between the two groups differed by 0.2809 which is not a large difference in score. The standard deviation for each group is .67822 and .73942 for Female (Group 1) and Male (Group 2) respectively (Bonett, 2015).
The Levene F value is small (F = .095) and is not statistically difference (p = .758). The Levene F test is not statistically different since (p > .05) Therefore, there is not enough evidence to reject the null hypothesis and thus homogeneity of variances t is reported. Similarly, the equal variances t test result was statistically significant, t (103) = 1.999, p = .048, two-tailed. Hence, at α = 0.05 and using two-tailed as the criterion, the .2809 difference in GPA score between the Male and Female was not statistically significant.
The effect size (η2) is determined as below;
η2 = t2 ÷ (t2 + df)
= 1.9992 ÷ (1.9992 + 103)
= 0.0373 ≈ 0.04. This implies that 4% of the variance of the GPA score is predicted from the gender of the students. This is not a large predictor to the variability of the GPA between the two groups (Warner, 2013).
The upper 95% confidence interval for the difference between the groups is .55965 while the lower CI is .00215.
Section 5: Conclusion
The analysis above clearly shows that there is no enough evidence to reject the null hypothesis hence we can conclude that there is no difference between the GPA score between Male and Female with 5% alpha level. We are 95% confident that the mean difference between the gender lies within the CI. The Levene F test asserts that the variability between the group in not significant at alpha = 0.05. In relation to the test-statistic approach, the variability between the male and female is insignificant since p > 0.05.
References
Bonett, D. G. (2015). Interval estimation of standardized mean differences in paired-samples designs. Journal of Educational and Behavioral Statistics, 40(4), 366–376.
George, D., & Mallery, P. (2016). IBM SPSS Statistics 23 step by step: A simple guide and refrence (Vol. 14th). New York and London: Routledge.
Warner, R. M. (2013). Applied statistics: From bivariate through multivariate techniques. Thousand Oaks, California: SAGE Publications, Inc.
Section 1 . Topic Endorsement |
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1.1 Research Topic (2 paragraphs) FIRST PARAGRAPH: Describe the specific topic to be studied. SECOND PARAGRAPH: describe the significance of this topic to your program/field (e.g., Psychology, Counseling, Business, Technology, Public Service Leadership, Education, etc.) AND your specialization within your program. The Research Topic should be correctly formed: · The Research Topic should be appropriate for the specialization. · The Research Topic should use appropriate language for key concepts/phenomena. · Relationships between/among the concepts should be clearly specified (e.g., correlation). · The target population should be named · The concepts should be appropriately focused. · Use current (within 5-7 years), scholarly, PRIMARY resources to support statements. · Use APA style in citing all resources. |
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1.2 Research Problem (1 Paragraph) Write a brief statement regarding the need for the study that fully describes the problem or need being addressed. The “need for the study” is what we often refer to as the Research Problem. In simplified terms, the research problem should take this form: “The research literature on _________ indicates that we know ________, we know __________, but we do not know ______________.” The Research Problem should be correctly stated: · Existing literature and key findings should be summarized · Gaps or problems in the existing literature should be clearly formulated · The Research Problem should be explicitly stated, not implied. . • Use current (within 5-7 years), scholarly, PRIMARY resources to support statements. • Use APA style in citing all resources. |
The research literature on the relationship between spirituality, self-esteem and happiness among African America men indicates that we know that there is a positive effect of the spiritual program on the happiness and well-being of average school going 13 – 15 years (Pandya, 2017), and we know that that higher levels of spiritual and religious involvement are found to enhance the well-being, improve one’s perceptions of life quality, increase one’s satisfaction with life and thereby, promoting one’s happiness (Gaur, 2019), but we do not know the strength of the relationship (correlation) which exist between spirituality, self – esteem and happiness among the study population. |
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2.1 Research Problem Background (3 paragraphs) Provide a brief SUMMARY of your review of the research literature on the topic. This should include citations from at least 10 articles, but should indicate that you have performed a full review of the literature (minimum of 75 articles) on the topic. This should be demonstrated by providing a statement about the body of existing literature on the topic, then, summarizing recent research findings on the topic, highlighting the findings that are most relevant to your proposed study, demonstrating how your proposed research could add to the existing literature on the topic. Be sure to provide appropriate in text citations and include references in the reference section. • Use current (within 5-7 years), scholarly, PRIMARY resources to support statements. • Use APA style in citing all resources. • This will not be your full dissertation literature review but an initial foundation. You will continue to add to your literature review throughout your dissertation process. |
A review of existing literature on the subject the role of spirituality in self-esteem and happiness revealed that there is gap in research with the population of African American men. In addition, most studies fail to connect spirituality to psychology in handling psychological problems. The broaden-and-build theory of positive emotions explains the phenomenon as well as the underlying foundations of positive emotions in the human body and mind. Pandya, S. P. (2017) in his study on a cross – Country Longitudinal RCT study on Spirituality, Happiness, and Psychological Well – being between ages 13 – 15 years old found out that there is a positive effect of the spiritual program on the happiness and well-being of average school going 13 – 15 years. In his study, he used a random sample of 5339 adolescents from at least 60 schools in 50 different countries. The spiritual program comprises of various components such as self-awareness, relational consciousness, meditation, and mindfulness works for adolescents’ cross-culturally (Pandya, 2017). The direction and strength of the association is not reported, hence the gap in the study. Sankul Gaur (March 2019) carried out a systematic review of 33 studies on spirituality, religiosity and happiness. The research question of the study was to explore the relation between spirituality, religiousness and happiness to establish them as the emerging predictors of happiness. The results of the study showed that higher levels of spiritual and religious involvement are found to enhance the well-being, improve one’s perceptions of life quality, increase one’s satisfaction with life and thereby, promoting one’s happiness. The reports that spiritual and religious practices were closely associated with reduction in stress, anxiety and suicidal tendency. Del Rio, C. M., & White, L. J. (2012) in his study on separating spirituality from religiosity reported that spirituality must be separated from religiosity if effective epistemic endeavors are to be achieved on either construct. Ivtzan (2016) in the study of how negative emotions such as fear and anger leaving behind positive emotions such as happiness. Positive emotions face neglect because they are less differentiated compared to negative emotions and a problem-focused approach of psychology fails to support a study of negative emotions. In addition, negative emotion’s models exist on prototypes while positive emotions fail to fit such models. Also, Samta P. Pandya (2017) in his study on Spirituality for Wellbeing of Bereaved Children in Residential Care founded out that spiritual intervention programs positively contributed to bereaved children’s outcome measures viz. psychological well-being, self-concept, health, happiness, quality of life, resilience and academic performance. Similarly, Samta P. Pandya (2015) in his study on Adolescents, well-being and spirituality among 396 adolescents from four cities – Vancouver, London, Johannesburg and Mumbai reported that Spirituality is generally perceived as having positive mental health and well-being influences and spirituality influences achievement, hope, well-being and happiness of adolescents. Therefore, past studies have showed that spirituality has a positive impact on the happiness and well-being of the teenagers below ages 25. Joshanloo, M., & Daemi, F. (2015) on their study of how self-esteem mediates the relationship between spirituality and subjective well-being in Iran founded out that spirituality was a significant predictor of self-esteem in this Iranian-Islamic sample. The sample size for the study, N = 322. The respondents were undergraduate students from the local college. Hayman, J. W. et al, (2007) on their study on the spirituality among college freshmen where they were examining the relationships between self-esteem, body image, and stress reported that there was a positive relationship was found between spirituality and self-esteem. A sample of 204 college freshmen who identified themselves as being highly spiritual were used in the study. on the other hand, Stern, S., & Wright, A. J. (2018) in their study on discrete effects of religiosity and spirituality on gay identity and self-esteem founded out that there is a positive association between spirituality and identity affirmation, identity superiority, and self-esteem. Religiosity was negatively associated with identity affirmation and self-esteem and positively associated with internalized homonegativity and heteronormativity. The researchers used a sample of 376 self-identified sexual minority adults were given measures of religiosity, spirituality, LGB identity, and self-esteem. Lastly, Awan, S., & Sitwat, A. (2014) in their study on workplace spirituality, self-esteem, and psychological wellbeing among mental health professionals reported that and self-esteem with psychological well-being among mental health professionals. Self-esteem and workplace spirituality were predictors of psychological wellbeing. The sample size for that study was 120 mental health professionals. |
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Example
Conflict of Interest
When referring to a conflict of interest, the research takes into account the potential for dual relationships, vulnerable populations, or bias data collection (Capella, n.d.). The researcher must examine whether their research may involve any conflicts of interest by evaluating these details. In doing this, a plan can be put into place to ensure preparation before research and tackling issues if they do occur during. Within a Qualitative study, this means we must ensure that all questions delivered remain open-ended and not leading. Especially in cases where the population may be answering questions about their personal experiences. Coding data following collecting answers will help process these data into the appropriate areas, reducing bias as well.
Vulnerable and Protected Populations
Vulnerable or protected populations such as children, seniors, prisoners, cognitively impaired persons, or employees are susceptible to risks of coercion, influence, or intimidation with a study. As such, these specific populations are not allowed to participate in the study, and would violate principles of respect and beneficence (HHS, 2016). The Belmont Report was delivered to help design guidelines in which researchers could abide by such guidelines of human dignity, respect, and protection. As such, my study would require that I work with BCBA’s in which I am not personally working with. Additionally, I will not work directly with children that may be involved in the caseload of the BCBA’s being studied.
Self as Subject
As a researcher, one could also be a study participant. This, however, poses challenges and ethical issues due to its nature. A study involving one’s own experiences holds potentially biased data. This vulnerability to bias must be established if such data is to be used, and must be scrutinized in a structured analytical process to ensure accuracy of data (Patton, 2015). Ethical dilemmas such as reliving potentially traumatic experiences, subjective data, and respecting participant rights must be considered to ensure an effective, non-biased, ethical study.
Ethical Considerations for Proposed Study
The main ethical issues I may need to consider in this proposed study is a conflict of interest. Being that I am a working BCBA myself, the recruitment of similar BCBA’s may pose a potential for coming across BCBA’s I already interact with and talk to. To ensure a larger range of participants and ensure I don’t run into issues where my participants are individuals I already interact with, I will recruit at least 15-20 individuals and then deliver a preliminary questionnaire to ensure they meet the participant demographic criteria I am looking for such as, currently a working BCBA, and had a child within 1 year of study. Any identifying information would be omitted from study and personal details kept private to ensure dignity and respect for participants. Again, while I do not foresee any ethical issues, it is possible I may come across a participant that I have conversed with personally in the field. A risk assessment should be conducted to determine that no psychological, social, or physical harm may come to any participant. Finally a determination on whether any prior relationship may be known to eliminate any personally connected BCBA’s from the study to remove the potential bias of information. Conflicts of interest, self as a subject, or study of vulnerable populations must be reviewed before conducting a qualitative study to ensure its conducted in an ethical manner per the HHS, the IRB, and Capella University. (HHS, 2016; Capella, n.d.; Capella, 2016).
Natasha Bouchillon
References:
Capella University. (n.d.) Institutional Review Board (IRB). Retrieved from https://campus.capella.edu/doctoral-programs/research-scholarship/institutional-review-board
Capella University. (2016). Assessing risk in research. Retrieved from http://assets.capella.edu/campus/doctoral-programs/UnderstandingResearchRisks
Department of Health & Human Services. (2016). The belmont report. Retrieved from https://www.hhs.gov/ohrp/regulations-and-policy/belmont-report/index.html
Patton, M. Q. (2015). Qualitative research & evaluation methods (4th ed.). Thousand Oaks, CA: Sage.
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 and 9602312_Qualitave Data AnalysisChap17
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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
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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
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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?
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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?
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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
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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 *
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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
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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
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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*
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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.
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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)
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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).
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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)
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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
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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.
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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
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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.
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
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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
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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
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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).
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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
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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?
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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
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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).
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?
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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.
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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…
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).
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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?
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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
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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
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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
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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
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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.
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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
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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).
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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
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Choosing a strategy
There are countless strategies for data analysis so how will you decide?
RQ
Purpose
Methodology
Resources
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Must consider your RQ, purpose, and methodology as well as resources
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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
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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
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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?
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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
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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
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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
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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
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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
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ShortDoc_Internal
Last updated: 11/29/2006 3:05 PM
The material in this document comes from the HASOP manual Qualitative Research Approaches i
n
Psychology.
Data Analysis
Data analysis in ethnography: Thematic analysis and exemplary life
histories
Ethnography shares with the other four approaches a core method of data analysis, namely thematic
analysis. The other approaches may use different terms or specify slightly different procedures, but the
core analytic method is quite similar. We describe it briefly here in its ethnographic form, and we’ll
describe it briefly in its other forms when outlining the other approaches. Learners are advised to
master the general method regardless of the approach they select.
Once the data are collected by observations, interviews (audio taped and transcribed), field notes, or
any other sources, patterns of experience (recurring words, phrases, descriptions, etc.) are identifie
d
and listed. These patterns are derived from direct quotes and paraphrases of recurring ideas emerging
from the data. These patterns form the first level of thematic analysis.
Next, the researcher identifies data that correspond to the identified patterns. If, in a study of the cultu
re
of a corporation, a pattern is noted such as “males defer to hierarchically superior males, but not to
hierarchically superior females,” examples that confirm this – that show it is both recurring and an
accurate description of events – are located in the data (transcripts, notes, etc.) and annotated with the
listed pattern (as quotes along with citation of their source).
Now, the researcher combines and catalogues related patterns into themes. Themes are defined as
descriptive meaning units derived from the patterns. For example, if along with the earlier example this
pattern emerged: “males repeatedly initiate flirting behavior with females regardless of the females’ rank
and the females return the flirtation, even when they dislike it,” two themes or meaning units might be
constructed as follows: “Males impose rank-dominance on subordinate males” and “males impose
sexual-dominance on all females.”
Finally, at the highest level of abstraction, themes that emerge from the patterns (which emerged from
the original data) are synthesized together to form a comprehensive representation of the element o
f
the culture that is being investigated. The above meaning units or themes might constellate with oth
er
descriptive themes of the male and female interactions in the organization into a rich and textur
ed
description of the rules, customs, attitudes, and practices around gender in that organization.
This distillation of the practice of thematic analysis is adapted from Taylor and Bodgan (1984) and
Aronson (1994).
In writing 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. Perhaps a more accurate term would be “culture stories” or “organization stories.” The
objective is not to single out the individuals for study, but to use their experiences to exemplify key
themes found in the data. These representative life stories are not standard biographies or life histories
as might be found in biographical research.
These life or organizational stories are created in a process not unlike thematic analysis. Here,
however, the stories of the participants’ experience in the culture, group, society, or organization are
culled for the initial patterns of recurring experiences, behaviors, etc. These in turn are organized into
themes or meaning units which in a robust way exemplify important aspects of the larger culture,
society, group, or organization. Finally, as in thematic analysis, the meaning units are woven into a
richly evocative description of the meaning of the persons experience in this culture which stands for
Data Analysis
2
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many others’ similar experiences. In effect, the life story (or the organization story, if you will) of the
exemplar “stands for” the essence of the ethnographic description of what it means to be a member of
this culture, group, or organization.
R
eferences
Aronson, J. (1994). A Pragmatic View of Thematic Analysis. The Qualitative Report, 2, Number 1.
Retrieved January 20,2003, from http://www.nova.edu/ssss/QR/index.html
Taylor, S, J. & Bogdan, R. (1984). Introduction to qualitative research methods: The search for
meaning. 2nd edition. New York: John Wiley.
Data analysis in case studies
Two types of data analysis for a case study are sometimes referred to (for example, Patton, 2005):
holistic analysis, in which the information about the entire case is analyzed; and embedded analysis, in
which information about a specific but limited aspect of the case is analyzed. For example, in a case
study of learners’ experiences with online education, if all aspects of the experience are studied – the
nature of the online platform, the IT support structure, the type of educational company providing the
online learning, the quality and training of the teachers, the nature of the curriculum, the demographics
of the learners, the costs and benefits perceived by the learners, the work load of the faculty, and so
on
and so forth – the analysis is said to be holistic.
However, if out of that mass of data only one aspect is analyzed and reported – for example, the
learners perceptions of the learning platform and of the instructors’ competence – this would be an
embedded analysis. A case study dissertation would most likely be a holistic analysis of a case or set of
cases.
There is no consensus format for case study data analysis, but a common series of steps can be found
in many sources. The following description is adapted from Creswell (1998) and Stake (1995).
• The opening step of data analysis – sometimes referred to as description – involves creating a
detailed description of the case as a whole and of its setting(s) and contexts. The objective is
both clarity and detail, creating a rich and textured picture of the case and its settings.
• The case study researcher looks at single instances in the described data and draws meaning
from each without (yet) looking for multiple instances. This process pulls the described data
apart and puts them back together in more meaningful ways. This may be called direct
interpretation.
• Next, the researcher seeks a collection of meaning-rich instances from the data, aggregating
these into categories of meaning, giving rise to the term categorical aggregation.
• By analyzing the categories (and the underlying instances and data of the various categories),
the researcher will identify themes – common statements of recurring description and patterns
of meaning – and connections between or among the themes. These themes will be developed
using verbatim passages and direct quotes from the data to elucidate each theme. At this point,
data from the case itself are used, without being compared yet with data and themes from other
cases; this is within-case analysis.
• The same steps are followed for each case in the series, so that each is analyzed within itself.
(For instance, if the study investigates ten cases of multiple sclerosis in young married people,
each person’s data are analyzed separately first, as a single case, before taking the next step)
• Then, the researcher will develop a thematic analysis across cases (across case analysis) as
well as interpretations of the integrated meaning of all the cases in the study.
• In the final, interpretive, phase, the researcher develops naturalistic generalizations from the
data as a whole and reports on the lessons learned from the case study.
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References
Creswell, J. (1998). Qualitative inquiry and research design: Choosing among five traditions. Thousand
Oaks, CA: Sage Publications, Inc.
Stake, R. (1995). The art of case study research. Thousand Oaks, CA: Sage.
Grounded theory data analysis methods and procedures: Coding
Because grounded theory goes beyond the descriptive and interpretive goals of many other qualitative
models and is aimed at building theories, data analysis tends to be more complex and aims to achieve
an explanatory power that is not necessary in other approaches. The heart of the grounded theory
approach occurs in its use of coding, its main form of data analysis. There are three different types of
coding used in a more-or-less sequential manner (this discussion is adapted from Strauss and Corbin,
1990, 1998, Patton, 2003; and Creswell, 1998).
The first type of coding is open coding which is much like the description goal of science. Usually open
coding is done first. During open coding, the researcher labels and categorizes the phenomena being
studied. This involves the process of describing the data through means such as examination,
comparison, conceptualization, and categorization. Labels are created to describe in one or a few
words the categories one finds in the data. Examples are collected for all these categories. For
example, in a grounded theory study of the effects of child sexual abuse, open coding might discover in
the reports of the participants some categories such as these: Feeling powerless, hating myself, hating
the abuser, or feeling permanently damaged.
The categories are studied more carefully to identify subcategories, which are called properties and
dimensionality in the categories. For instance, the researcher in our example might discover that “hating
myself” had a wide range of emotional power – in some participants it is very strong, whereas in others
it is not strong at all. The categories, properties, and dimensions discovered in the data are fully
described in the participants’ words.
Then begins the second type of coding: axial coding which involves finding links among the categories,
properties, and dimensions that were derived from open coding. (A link is an axis, hence the term
axial.) How is axial coding actually done?
Axial coding first identifies the central categories about the phenomenon. These central or core
categories tend to be the most important aspect(s) of element of the phenomenon, the one that clearly
has the greatest strength and appears in all or most of the participants’ reports or other data. For
instance, a central category of the phenomenon of the psychological effects of childhood sexual abuse
might be found to be “feelings of powerlessness.”
Next, the researcher explores the data carefully to discover causal conditions, which are categories of
conditions influencing the central category or categories. For instance, in the child sexual abuse study,
one causal condition might be found to be “repeated humiliations,” a condition that is found across
many reports to support or influence the development of feelings of powerlessness (the central
category).
The researcher continues axial coding by identifying interactions among the categories (which are
called strategies, although that term might be confusing). Strategies in the example study could be, for
example, “repeated humiliations strengthen feelings of powerless, but weaken hatred of the abuser
while strengthening self-hatred.” You might think of “strategies” in grounded theory as the equivalent of
correlations in statistical theory-building.
Axial coding continues with the identification and exploration of other supporting or weakening
conditions which exert lesser influences on the central variables. These are categories in the data
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which label the contexts and intervening conditions. Examples from the grounded theory study of the
effects of child sexual abuse might include “protection by another adult,” which when found to be
present ameliorates (positively influences) the central category, but which is insufficient in itself to
prevent the damage entirely. Finally, consequences are carefully identified and described. These would
include all the outcomes of the presence of the central category in all its interactions (strategies) w
ith
contexts, intervening conditions, properties, dimensions, etc. Consequences describe what happens
when the central category is found under specific conditions. For example, when “feelings of powerless”
are found to be very strong, accompanied (interacting with) “isolation” and “repeated humiliation,”
depression may be found to be a consequence.
Notice that these consequences are NOT presupposed, but are carefully teased out of the real reports
and descriptions of their experiences by the many participants in the study. Preconceptions about the
theory must be left at the door. See “Phenomenology,” below, and its discussion of epoche and the
phenomenological reduction. Without using the terminology of phenomenology, the requirement is the
same.
The third type of coding is selective coding continues the axial coding activity of relating the subsidiary
categories to the central category(s). Selective coding is the process of selecting your main
phenomenon (core category) around which all other phenomena (subsidiary categories) are grouped,
arranging the groupings, studying the results and rearranging where necessary. It is necessary to
remain faithful to the data, so in selective coding, one frequently goes “back to the things themselves”
to ensure that one is capturing what one’s informants told one.
From this last type of coding, the grounded theory researcher moves toward developing a model of
process and a transactional system, which essentially tells the story of the outcome of the research.
Creating a literal “story line” is one manner of doing selective coding. The story line tells the results of
the axial coding in a coherent narrative. Many grounded theory researchers do not create a conditional
matrix, a diagram or picture of the various categories, interactions, and relationships among the central
category(s) and the subsidiary categories. But the conditional matrix is a very helpful tool in creating the
narrative story line which embodies the grounded theory.
The selective coding process typically focuses on two dimensions of the phenomenon: its process and
its transactional system. Again, the conditional matrix is quite useful in elucidating these two elements
of the theory.
• Process is the manner in which actions and interactions occur in a sequence or series. It
incorporates the time element. (“As time went on and I got older, the repeated humiliations
my father inflicted on me began to tear me apart. I started to hate myself, though not
at
first.”) It also incorporates the various categories which mutually influenced each other.
(“My brother tried to help, and I was grateful, but I was more worried he’d get hurt, so I
asked him to stay out of it. He hasn’t been much a part of my life since.”)
• The transactional system is a grounded theory’s analytic method that allows an
examination of the interactions of different events. (“Self-hatred led to increased willingness
to be hurt. It strengthened the belief among most participants that the victim is bad and
deserves punishment, and also strengthened the yearning for even the abusive “love”
offered by the perpetrator. This in turn alienated most participants from other sources of
more benign love, because the victims did not feel worthy of it.”)
The use of the conditional matrix and the process and transactional-system analysis leads finally to the
general description of the grounded theory. It might be a brief sentence distilling all the above work, or a
more complex statement. But it will also be accompanied by a set of propositions or hypotheses which
menon under study. explain the pheno
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At this stage, it is usual for grounded theory researchers to return not only to the original data to ensure
that the theory fits those data, but may meet with the participants again to compare the theory wit
perceptions and to ask them whether the theory fits their experiences. Their responses will be taken as
new data to be incorp
h their
orated into the theory, which is thought to be in a continual adaptation and
volution. Grounded theory is never complete. (Adapted from Strauss, & Corbin, 1990, 1998; Creswell,
2002)
d
ge.
trauss, A., Corbin, J. (1998). Basics of qualitative research: Techniques and theory for developing
grounded theory (2nd ed.). Newbury Park, CA: Sage.
e a
method of analysis of phenomenological data are acceptable in the General Psychology specialization.
ed provided they meet (are equivalent to) the criteria described in these pages.
r deeper
comparison. These segments (or “meaning units” as described above) will be organized
ematically in two major ways: within the context of a single interview, and across a series of
ed
g
erviews” would not have been possible unless the
dividual phrases could have been cut out and kept in a separate “meaning unit” document of some
ings that emerge from the data in their own terms. If we include these two preliminary steps with
e
1998; Patton,
References
Creswell, J. (1998). Qualitative inquiry and research design: Choosing among five traditions. Thousan
Oaks, CA: Sage Publications, Inc.
Patton, M. (2002). Qualitative research and evaluation methods (3rd ed.). Newbury Park, CA: Sa
Strauss, A., Corbin, J. (1990). Basics of qualitative research: Grounded theory procedures and
techniques. Newbury Park, CA: Sage.
S
Phenomenological Data Analysis
Most standard texts (e.g., Creswell, 1998; Patton, 2002; or Taylor and Bogdan, 1984) propos
general five-step model for phenomenological analysis. These steps are elaborated in three more
detailed models described in Appendix A (see “empirical phenomenology” [Amedeo Giorgi],
“transcendental phenomenology” [Clark Mousakas] and the Stevick-Colaizzi-Keen Method of Analysis
of Phenomenological Data). The Giorgi model, the Moustakas model, and the Stevick-Colaizzi-Keen
Other models can be us
Preliminary steps
The generic method of analysis consists of five essential steps, but is preceded by careful preparation
of the data and of the researcher. First, the data must be transformed into written form – usually
transcripts of interviews – which can be studied as a whole and, later, in bits or units. Word processing
programs are ideal for this, allowing both retention of the original interview in “raw” form and “cutting
and pasting” individual segments (phrases, sentences, paragraphs) into separate documents fo
analysis and
th
interviews.
For example, in a series of phenomenological interviews on the experience of grief in children, the
researcher found that participant A repeated the phrase, “she left me behind” many times in talking
about what it was like to lose his mommy. Within the context of that child’s experience, being “left
behind” became a very significant part of the experience, a “meaning unit.” Meanwhile, child B repeat
the phrase “she’s gone, I can’t find her” a number of times. This too was a meaning unit for child B.
Looking across both transcripts and comparing the two meaning units and reflecting deeply on them
and their contexts in the interviews, the researcher teased out a deeper level of meaning by comparin
the two different units: “I feel lost.” This “across int
in
kind, which word processing makes quite handy.
Before starting to analyze data, though, the researcher does a second preparatory step, which as been
described briefly above as the “phenomenological reduction.” She attempts to reduce the impact of his
or her biases, preconceptions, and beliefs about the phenomenon and opening oneself to the data and
mean
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the five steps proposed by most texts, we have a generic seven-step model for data analysis, beginning
Step 1 and 2: Prepare the data and adopt the phenomenological attitude (“reduction” or “epoche” [see
below].)
tep 3: Achieve a Sense of the Whole. The researcher reads the entire description in order to get a
oes
de
ith psychological criteria in mind. The researcher next eliminates redundancies and clarifies and
concrete
ants, reflects on them, and comes up with the essence of the experience for the
articipant. The researcher next transforms each relevant unit’s essence into the language of
ere, the researcher synthesizes all of the transformed meaning units (now expressed in
e language of psychological science) into a consistent statement regarding the participant’s
r synthesizes all of the essence or structure statements
regarding each participant’s experience into one consistent statement, which describes and captures
d
above. Either of the
odels is acceptable for phenomenological research in the General Psychology specialization. The
at
tive
rationale should be approved by the mentor (and the dissertation committee, of course)
nd reviewed (with a rating of “Satisfactory” or better) by the Methodology Committee of the
85,
gy”)
Ernest Keen of Bucknell University (1975) and Paul F. Colaizzi and Emily M. Stevick of Duquesne
with:
Steps in phenomenological data analysis: Generic model
S
general sense of the whole statement.
Step 4: Discrimination of Meaning Units Within a Psychological Perspective and Focused on the
Phenomenon Being Researched. Once the sense of the whole has been grasped, the researcher g
back to the beginning and reads through the text once more and delineates each time that a transition
in meaning occurs. The specific aim is to discriminate “meaning units” from within a psychological
perspective and with a focus on the phenomenon being researched. The meaning unit should be ma
w
elaborates on the meaning of the units by relating them to each other and to the sense of the whole.
Step 5: Transformation of Subjects Everyday Expressions into Psychological Language with Emphasis
on the Phenomenon Being Investigated. Once meaning units have been delineated and linked
together, the researcher goes through all of the meaning units, which are still expressed in the
language of the particip
p
psychological science.
Step 6: Synthesis of Transformed Meaning Units into a Consistent Statement of the Structure of the
Experience. H
th
experience.
Step 6: Final Synthesis: Finally, the researche
the essence of the experience being studied.
Acceptable Models of Phenomenological Analysis
The generic model described above is elaborated in two acceptable and detailed models of
psychological phenomenological analysis developed by Amedeo Giorgi at Duquesne University an
Clark Moustakas at the Center for Humanistic Studies and The Union Institute. Each of these models is
detailed and provides a stepwise guide to the seven generic steps presented
m
Moustakas model is further elaborated in the Stevick-Colaizzi-Keen model.
A learner may adopt a different model for the data analysis, provided that the alternative model is
least as clearly articulated and provides at least as much guidance for procedures as the accepted
models. The learner should prepare a careful description of and rationale for using an alterna
model, and that
a
Specialization.
The Giorgi model (usually called “empirical phenomenology” or “phenomenological psychology”) (19
1997) (Giorgi & Giorgi, 2003) and the Moustakas model (often called “transcendental phenomenolo
and the “Stevick-Colaizzi-Keen Model” synthesized by Moustakas (1994) and based on the work of
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University are described more fully in Appendix A. They differ from each other and from the generic
model above only in the ways in which they outline the procedures. Each provides much more detail
bout how to proceed in each step or stage.
eferences
Creswe research design: Choosing among five traditions. Thousand
Giorgi, A ). Phenomenology and psychological research. Pittsburgh, PA: Duquesne University
Giorgi, A s a qualitative
Giorgi, A amic,
ng
y and design (pp. 243-273). Washington, DC: American
Keen, E ogy phenomenologically. Unpublished Manuscript. Lewisberg, PA:
rd age.
Taylor, itative research methods: The search for
meaning. 2nd edition. New York: John Wiley.
uld
e the researcher (who performs them) is a
articipant, they already are a form of data collection.
n.
form of the phenomenological
duction or epoche (see Appendix A for a description of epoche).
other forms of self-expression may become the
rimary mode of both data collection and data analysis.
ith
a
R
ll, J. (1998). Qualitative inquiry and
Oaks, CA: Sage Publications, Inc.
. (1985
Press.
. (1997). The theory, practice and evaluation of phenomenological methods a
research procedure. Journal of Phenomenological Psychology, 28, 235-281.
.P. & Giorgi, B.M. (2003). The descriptive phenomenological psychological method. In C
P.M., Rhodes, J.E. & Yardley, L. (Eds.), Qualitative research in psychology: Expandi
perspectives in methodolog
Psychological Association.
. (1975). Doing psychol
Bucknell University.
Moustakas, C. (1994). Phenomenological research methods. Thousand Oaks, CA: Sage.
Patton, M. (2002). Qualitative research and evaluation methods (3 ed.). Newbury Park, CA: S
S, J. & Bogdan, R. (1984). Introduction to qual
Data Analysis Methods in Heuristic Inquiry
In general, six steps characterize the heuristic approach to data analysis. They are as follows: initial
engagement, immersion, incubation, illumination, explication and synthesis (Douglass and Moustakas,
l985; Moustakas, , 1967, 1981, 1990, 2001). Steps 1 and 2 (initial engagement and immersion) wo
appear to be preliminary to data collection, but becaus
p
Step 1: Initial engagement involves and awareness of the topic. In heuristics it is essential that the
topic not only be of importance to the researcher but also that he/she experiences a sense of passion in
connection with it. From the experience of being with the topic in an open way emerges the questio
The culmination of the initial engagement period is the creation of a clear research question which
forms the heart of the inquiry. Initial engagement requires the researcher to reduce the influence of
preconceptions and beliefs about the phenomenon, so it includes a
re
Step 2: During the immersion step, the researcher makes his/her question the center of the
experiential world, allowing the self to become one with the question. This is done in a loose, non-
structured way, permitting openness to the range of related experiences, which helps to facilitate an
understanding of the phenomenon. During this step, the researcher is non-judgmental and non-critical,
open to the flow of experience (again, a version of the phenomenological reduction). The researcher is
open to intuitions (hunches based on clues) and tacit knowledge (knowing that he/she knows but not
knowing how he/she knows). At this stage, journaling or
p
During immersion, heuristic researchers also gather information from their co-researchers, in the form
of interviews, diaries, journals, writings, art, film, etc.., and immerse themselves in those data along w
their own data. Typically, each researcher finds a personal method for immersing oneself in the data
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that are emerging from the interviews and other documents. As can be seen, data “collection” and d
“analysis” are not easily separated into d
ata
iscrete steps or stages, but are an integrated and ongoing
process each informing the other.
d on
re
el. No
y the engaged
searcher will be “present” to the process and reflecting often on how it is going.
er
n
n learner, because the time-and-money pressures of the four-course, one-year model can be
factor.
erves
s
d
on
indwelling and reflection
e essential structures of the experience of the phenomenon under study.
f
heuristic inquiry is similar to the “final synthesis” in the generic model of
phenomenological analysis.
uestion or problem AND (2) to develop portraits of the persons who have explicated the experience.
eferences
Douglas inquiry: The internal search to know. Journal of
Mousta arch. In J.F.T. Bugental (Ed.) Challenges of Humanistic
Psychology. McGraw-Hill.
Step 3: After a period of time, having been immersed in the research question, the researcher puts
aside all deliberate focus on the experience and the data and allows the information to be processe
an unconscious level, a process known as incubation. When this becomes appropriate cannot be
arbitrarily specified, but depends on the data themselves. A common marker is when new themes are
no longer emerging in the data ( a condition sometimes called saturation). During incubation, data a
no longer being collected intentionally (although new insights may emerge or new information may
arise). Instead, the researcher allows the data to “go unconscious” and to be processed at that lev
intentional (conscious) work is done to further the interpretation, although obviousl
re
Step 4: The information continues to consolidate and grow (“incubate”) until a sense of discovery
occurs. This moment of realization and enlightenment is known as illumination, and often has the fell
of an “Aha!” experience. At this point, new knowledge is obtained, representing a whole that is great
than the sum of its parts. The great danger here is that the researcher will succumb to pressures of
time, money, or expediency and “force” an illumination which is not authentic. Because the incubatio
period (step 3) is by nature an unconscious process, it is unpredictable. One cannot know ahead of
time when insight or illumination will emerge. This provides an alement of risk to the Capella University
dissertatio
a
Step 5: The next step is explication. During the explication phase, the researcher returns to the data
(transcripts, documents, etc.), and with the new insights gained during the illumination phase, obs
the patterns and themes arising which portray essential meanings. This is a version of “thematic
analysis” as discussed in the section on ethnography. Indwelling is used to dwell within the experiences
and draw meaning from them. Polanyi (l966) refers to indwelling as follows: “It brings home to us that
it is not by looking at things, but by dwelling in them, that we understand their joint meaning” (p. l8). Thi
phase resembles the earlier immersion phase, with the difference that now one dwells in the data an
their emerging meanings and structures in order to interpret them, whereas in the earlier immersi
phase, one was immersed in the articulation of the phenomenon itself and in gathering similar
articulations from one’s co-researchers. The goal of step 5 is to articulate by
th
Step 6: The final step in a heuristic inquiry is synthesis. It is through synthesis that the whole
experience is captured. Synthesis is more than a summary, it is the creation of a new understanding o
the essence of the experience. “Synthesis goes beyond distillation of themes and patterns. It is not a
summary or recapitulation. In synthesis, the searcher is challenged to generate a new reality, a new
monolithic significance that embodies the essence of the heuristic truth” (Douglass and Moustakas,
l985, p. l7). The synthesis in
The task is (l) to arrive at a depiction of the experience, a synthesizing statement that illuminates the
q
R
s, B. & Moustakas, C. (l985). Heuristic
humanistic psychology, 25(3), 39-55.
kas, C. (1967) Heuristic rese
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Moustakas, C. (1981) Heuristic methods of obtaining knowledge. In C. Moustakas, Rhythms, Rituals,
and Relationships. Center for Humanistic Studies.
Moustakas, C. (1990) Heuristic Research: Design, methodology and applications. Newbury Park, CA:
Sage.
Moustakas, C. (2001) Heuristic research: Design and Methodology. In K.J. Schneider, J.F.T. Bugental
& J.F. Pierson, (Eds.) The Handbook of Humanistic Psychology: Leading edges in theory,
research, and practice. Sage.
Polanyi, M. (l966). The tacit dimension. Garden City, New York: Anchor Books Doubleday and
Company, Inc.
Detailed Step-by-Step Procedures for Data Analysis
Three Models of Phenomenological Analysis
A. Empirical Phenomenology is a model of phenomenological psychological research that was
developed at Duquesne University (Giorgi, 1985, 1997; Giorgi & Giorgi, 2003).
In order to develop an understanding of the phenomenological psychological research method,
it is essential to first understand the concept of intentionality and its role in the
phenomenological method. The following passage from Amedeo Giorgi (1997) explains the
role of intentionality in phenomenology.
Finally, no discussion of phenomenology would be complete without mentioning intentionality.
Edmund Husserl took the term over from Franz Bretano but uses it in a fundamentally different
way. For Husserl, intentionality is the essential feature of consciousness, and it refers to the
fact that consciousness is always directed to an object that is not itself consciousness, although
it could be, as in reflective acts. More precisely, consciousness always takes an object, and the
object always transcends the act in which it appears. This idea is important for the human
sciences as well, since it helps overcome the Cartesian understanding of the subject-object
relationship. There are not two independent entities, objects and subjects, existing in
themselves which later get to relate to each other, but the very meaning of subject implies a
relationship to an object, and to be an object intrinsically implies being related to subjectivity.
Thus, the subject object relationship must be understood structurally and holistically (p. 237).
In the philosophical phenomenological method there are three interlocking steps: (1) the
phenomenological reduction, (2) description and (3) search for essences. The
phenomenological reduction is a methodological device devised by Husserl that is used to
make research findings, which use the phenomenological model more precise. During the
phenomenological reduction, one brackets past knowledge about the phenomenon
encountered in order to be fully present to it as it is in the concrete situation in which one is
encountering it. One puts aside or renders “non-influential” all past knowledge that may be
associated with the presently given object.
The researcher cannot expect all participants in the psychological phenomenological study to
be phenomenological and, thus, capable of assuming the attitude of the phenomenological
reduction. Moreover, for human science research, the details, biases, errors, and prejudices
that we carry with us in everyday life are exactly what have to be understood in psychological
phenomenological research. What is critical is that the description be as precise and detailed
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as possible with a minimum number of generalities and abstractions. However, the
phenomenological attitude does demand that the researcher be able to do his/her work from
within the attitude of the reduction or else no phenomenological claims for the analysis could be
made.
There are two descriptive levels of the empirical phenomenological model:
Level 1, the original data is comprised of naïve descriptions obtained through open-ended
questions and dialogue.
Level II, the researcher describes the structures of the experiences based on reflective analysis
and interpretation of the research participant’s account or story.
The method of analysis consists of five essential steps which are as follows:
1) Sense of the Whole – One reads the entire description in order to get a general sense
of the whole statement.
2) Discrimination of Meaning Units Within a Psychological Perspective and Focused on
the Phenomenon Being Researched – Once the sense of the whole has been grasped,
the researcher goes back to the beginning and reads through the text once more and
delineates each time that a transition in meaning occurs with the specific aim of
discriminating “meaning units” from within a psychological perspective and with a focus
on the phenomenon being researched. The meaning unit should be made with
psychological criteria in mind. The researcher next eliminates redundancies and
clarifies and elaborates on the meaning of the units by relating them to each other and
to the sense of the whole.
3) Transformation of Subjects Everyday Expressions into Psychological Language with
Emphasis on the Phenomenon Being Investigated – Once meaning units have been
delineated, the researcher goes through all of the meaning units, which are still
expressed in the concrete language of the participants, reflects on them and comes up
with the essence of the experience for the participant. The researcher next transforms
each relevant unit into the language of psychological science.
4) Synthesis of Transformed Meaning Units into a Consistent Statement of the Structure
of the Experience – Finally, the researcher synthesizes all of the transformed meaning
units into a consistent statement regarding the participant’s experience.
5) Final Synthesis – Finally the researcher synthesizes all of the statements regarding
each participant’s experience into one consistent statement, which describes and
captures the essence of the experience being studied.
(Adapted from Giorgi, 1985, 1997; Giorgi & Giorgi, 2003)
B. Transcendental Phenomenology -There are three core processes that facilitate derivation of
knowledge in the transcendental phenomenological approach as proposed by Clark Moustakas
(1994). The three core processes are: Epoche, Transcendental- Phenomenological
Reduction and Imaginative Variation.
1) Epoche: Setting aside prejudgments and opening the research interview with an
unbiased, receptive presence. It is returning to things themselves, free of
prejudgments and preconceptions.
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2) Transcendental Phenomenological Reduction: The task is that of describing in textual
language just what one sees, not only in terms of the external object but also the
internal act of consciousness, the experience as such, the rhythm and relationship
between phenomenon and self. Textual qualities are as follows: rough and smooth;
small and large; quiet and noisy; colorful and bland; hot and cold; stationary and
moving; high and low; squeezed in and expansive, fearful and courageous; angry and
calm – descriptions that present varying intensities; ranges of shapes, sizes and
special qualities; time references and colors within an experiential context.
a. Bracketing the Topic or Question – The focus of the research is placed in
brackets, everything else is set aside so that the entire research process is
rooted solely on the topic and question.
b. Horizonalizaton – Every statement is treated as having equal value.
c. Statements irrelevant to the topic or question as well as those that are
repetitive or overlapping are deleted, leaving only the Horizons (the textual
meaning and invariant constituents of the phenomenon)
d. Delimiting Horizons or Meanings: Horizons that stand out as invariant
qualities of the experience.
e. Invariant Qualities and Themes – Non-repetitive, non-overlapping
constituents are clustered into themes.
f. Individual Textual Descriptions – Develop integration, descriptively, of the
invariant textural constituents and themes of each research participant.
g. Composite Textual Description – Develop integration of all of the individual
textual descriptions into a group or universal textual description.
3) Imaginative Variation: The task of Imaginative Variation is to seek possible meanings
through the utilization of imagination, varying frames of reference, employing polarities
and reversals, and approaching the phenomenon from divergent perspectives, different
positions roles or functions. The aim is to arrive at structural descriptions of an
experience, the underlying and precipitating factors that account for what is being
experienced; in other words the “how” that speaks to conditions that illuminate the
“what” of experience. How did the experience of the phenomenon come to be what it
is? The steps to Imaginative Variation are as follows:
a. Systematic varying of the possible structural meanings that underlie the
textural meanings. Vary perspectives of the phenomenon from different
vantage points, such as opposite meanings and various roles. Using free
fantasy variations, consider freely the possible structural qualities or
dynamics that evoke structural qualities.
b. Construct a list of the structural qualities of the experience.
c. Recognizing the underlying themes or contexts that account for emergence
of the phenomenon.
d. Develop structural themes by clustering the structural qualities into themes.
e. Considering the universal structures that precipitate feelings and thoughts
with reference to the phenomenon, such as: time, space, bodily concerns,
materiality, causality, relation to self, or relation to others;
f. Individual Structural Descriptions: For each participant, integrate the
structural qualities and themes into an individual structural description of
the experience.
g. Composite Structural Description: Integration of all of the individual
structural descriptions into a group or universal structural description of the
experience.
4) Synthesis of Meanings and Essences: The final step in the phenomenological
research process is the intuitive integration of the composite textual and structural
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descriptions into a unified statement of the essences of the experience of the
phenomenon as a whole. The essences of any experience are never totally
exhausted. The fundamental textual-structural synthesis represents the essences at a
particular time and place from the vantage point of an individual researcher following
an exhaustive imaginative and reflective study of the phenomenon.
(Adapted from Moustakas, 1994)
C. Stevick-Colaizzi-Keen Method of Analysis of Phenomenological Data (See Flow Chart in
Appendix B)
Epoche is the first step in the phenomenological method and is a process in which the
researcher sets aside all preconceived ideas about what is being experienced and described by
the participants. Phenomenological Reduction is the process by which the participant describes
in textual language just what one sees, not only in terms of the external object but also the
internal act of consciousness, the experience under inquiry as such, the rhythm and
relationship between phenomenon and self. Textual qualities are as follows: rough and
smooth; small and large; quiet and noisy; colorful and bland; hot and cold; stationary and
moving; high and low; squeezed in and expansive, fearful and courageous; angry and calm –
descriptions that present varying intensities; ranges of shapes, sizes and special qualities; time
references and colors within an experiential context. During this step in the phenomenological
process, the textural qualities of the lived experience of the participant are separated. Those
comments that deal with the question are clustered into themes (Moustakas, 1994).
Following the Phenomenological Reduction, the researcher uses imaginative variation. The
task of imaginative variation is to seek possible meanings through the utilization of imagination,
varying frames of reference, employing polarities and reversals, and approaching the
phenomenon from divergent perspectives, different positions roles or functions. The aim is to
arrive at structural descriptions of an experience, the underlying and precipitating factors that
account for what is being experienced; in other words, the “how” that speaks to conditions that
illuminate the “what” of experience. How did the experience of the phenomenon come to be
what it is? Through the use of imaginative variation the researcher examines the data collected
from participants from different views, changing the frames of reference, using polarities and
reversals, and looking at the phenomenon from different perspectives, positions, roles, or
functions. Employ universal structures as themes: time, space, materiality, relationship to self,
relationship to others, bodily concerns, causal and intentional structures.
The final step of the process is called intuitive integration. Intuitive integration is the process by
which the researcher develops textural-structural synthesis that represents the essence of the
experience of the phenomenon under inquiry (Moustakas, 1994).
The steps to the modified Stevick-Colaizzi-Keen Method of Analysis of
Phenomenological Data are as follows:
1) Set aside all preconceived ideas about what is being experienced and described
by the participant (Epoche).
2) Consider each statement with the emphasis on the importance for description of
the experience.
3) Record all of the relevant statements dealing with the experience.
4) Make a list of every non-repetitive, non overlapping statement. These constitute
the invariant horizons or meaning units of the experience.
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5) Cluster the invariant meaning units into themes.
6) Organize the invariant meaning units and themes into a description of the
textures of the experience (textural description). Include direct quotes and
verbatim passages from the participants.
7) Reflect on the textual descriptions. Through the use of imaginative variation,
develop a description of the structures of these experiences (structural
description).
8) Construct a textural-structural description of the meanings and essences of the
experiences for the individual participant.
9) Once this process is completed for the data collected from each participant in the
study, synthesize all of these descriptions into a composite textural-structural
description of the experience representing the essence of the experience of the
participants in the study as a whole. Thus, developing a composite textural-
structural synthesis, which represents the lived experience of the subject under
investigation for participants involved in the study.
(Adapted from Moustakas, 1994)
References
Brennan, J. (1998). History and systems of psychology. Prentice-Hall: New Jersey.
Giorgi, A. (1985). Phenomenology and psychological research. Pittsburgh, PA: Duquesne University
Press.
Giorgi, A. (1997). The theory, practice and evaluation of phenomenological methods as a qualitative
research procedure. Journal of Phenomenological Psychology, 28, 235-281.
Giorgi, A.P. & Giorgi, B.M. (2003). The descriptive phenomenological psychological method. In Camic,
P.M., Rhodes, J.E. & Yardley, L. (Eds.), Qualitative research in psychology: Expanding
perspectives in methodology and design (pp. 243-273).
Washington, DC: American Psychological Association.
Moustakas, C. (1994). Phenomenological research. Thousand Oaks, CA: Sage.
Van Manen, M. (1990). Researching lived experience: Human science for an action sensitive
pedagogy. Albany, NY: State University of New York Press.
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Appendix B Flow chart of Keen’s version of transcendental phenomenological data
analysis
Step 1:
Epoche
Step 2: Phenomenological
reduction
Step 3: Imaginative Variation
Step 4: Intuitive synthesis
Epoche is the first step in the phenomenological method and is a process in which the researcher sets
aside all preconceived ideas about what is being experienced and described by the participants.
Phenomenological researchers develop their own techniques, often involving meditative or awareness
techniques (such as mindfulness meditation, journaling, and the like) to become aware of the arising of
biases or biasing thoughts).
Phenomenological Reduction is the process by which the participant describes in textual language just
what one sees, not only in terms of the external objects but also the internal act of consciousness, the
experience under inquiry as such, the rhythm and relationship between phenomenon and self. During
this step in the phenomenological process, the textural qualities of the lived experience of the
participant are separated and a textural description is developed.
The task of imaginative variation is to seek possible meanings through the utilization of imagination,
varying frames of reference, employing polarities and reversals, and approaching the phenomenon
from divergent perspectives, different positions roles or functions. The aim is to arrive at structural
descriptions of an experience, the underlying and precipitating factors that account for what is being
experienced; in other words, the “how” that speaks to conditions that illuminate the “what” of
experience.
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The final step of the process is called intuitive integration. Intuitive integration is the process by which
the researcher develops textural-structural synthesis that represents the essence of the experience of
the phenomenon under inquiry
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Appendix C Flow chart of Generic thematic analysis of Qualitative Data
Step 1: Patterns of experience are identified: recurring
words and phrases are identified and summarized.
These are called meaning units.
Step 2: Confirming data (specific words, phrases, etc.) are
linked to the meaning units from step 1.
Step 3: Related patterns or meaning units (steps 1 & 2) are combined into
themes.
Step 4: Themes are synthesized to form a comprehensive
description of the phenomenon.
Patterns of experience or meaning units
Once the data are collected by observations, interviews (audio taped and transcribed), field notes, or
any other sources, patterns of experience (recurring words, phrases, descriptions, etc.) are identified
and listed. These patterns are derived from direct quotes and paraphrases of recurring ideas emerging
from the data. These patterns form the first level of thematic analysis.
Linking the data themselves to the meaning units (confirming the meaning units)
Next, the researcher identifies data that correspond to the identified patterns. If, in a study of the culture
of a corporation, a pattern is noted such as “males defer to hierarchically superior males, but not to
hierarchically superior females,” examples that confirm this – that show it is both recurring and an
accurate description of events – are located in the data (transcripts, notes, etc.) and annotated with the
listed pattern (as quotes along with citation of their source). This step is critical, because it provides
confirming evidence that the meaning units have emerged directly from the data themselves and not
from the researcher’s biases or preconceptions. This step also provides the material for substantiating
the “results” section of the dissertation (typically Chapter Four).
Creating Themes
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Now, the researcher combines and catalogues related patterns into themes. This is a more abstract
step, during which the researcher must beware the intrusion of bias, preconceptions, beliefs, etc.
Themes are comprised of combinations and distillations of the descriptive meaning units derived from
the patterns in the data. For example, if along with the earlier example this pattern emerged: “males
repeatedly initiate flirting behavior with females regardless of the females’ rank and the females return
the flirtation, even when they dislike it,” two themes or meaning units might be constructed as follows:
“Males impose rank-dominance on subordinate males” and “males impose sexual-dominance on all
females.”
Synthesis of themes
Finally, at the highest level of abstraction, themes that emerge from the patterns or meaning units
(which emerged from the original data) are synthesized together to form a comprehensive
representation of the element of the culture that is being investigated. The above meaning units or
themes might constellate with other descriptive themes of the male and female interactions in the
organization into a rich and textured description of the rules, customs, attitudes, and practices around
gender in that organization.
This distillation of the practice of thematic analysis is adapted from Taylor and Bodgan (1984) and
Aronson (1994)
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Appendix D Moustakas’ Description of Data Analysis in Heuristic Research
1) Place all the material drawn from one participant before you (recordings, transcriptions,
journals, notes, poems, art work, etc.). This material may either be data gathered by self-search
or by interviews with co-researchers.
2) Immerse yourself fully in the material until you are aware of and understand everything that is
before you.
3) Put the material aside for a while. Let it settle in you. Live with it but without particular attention
or focus. Return to the immersion process. Make notes where these would enable you to
remember or classify the material. Continue the rhythm of working with the data and resting
until an illumination or essential configuration emerges. From your core or global sense, list the
essential components or themes that characterize the fundamental nature and meaning of the
experience. Reflectively study the themes, dwell inside them, and develop a full depiction of
the experience. The depiction must include the essential components of the experience.
4) Illustrate the depiction of the experience with verbatim samples, poems, stories, or other
materials to highlight and accentuate the person’s lived experience.
5) Return to the “raw material” of your co-researcher (participant). Does your depiction of the
experience fit the data from which you have developed it? Does it contain all that is essential?
Complete the above steps for each participant. Then:
a) Place the Reflective Depiction for each participant before you.
b) Immerse yourself completely in the Reflective Depictions until you are fully aware of and
understand what they contain.
c) Put the material aside and engage in a rhythm of rest and work until the essential invariant and
non-repetitive themes of the material stand out.
d) Make a list of the essential components of the experience (these should portray the qualities,
nature, and meanings that characterize the experience).
e) From the above, develop a full reflective depiction of the experience, one that characterizes the
participants as a group, reflecting core meanings not only for the individuals but the group of
persons as a whole. Include in the depiction, verbatim samples, poems, stories, etc., to
highlight and accentuate the lived nature of the experience. This depiction will serve as the
creative synthesis, which will combine, in an esthetically pleasing way, the themes and patterns
into a representation of the whole. This synthesis will communicate the essence of the lived
experience under inquiry. The synthesis is more than a summary – it is like a chemical
reaction, a creation of anew.
f) Return to the individuals, select two or three and develop portraits of these persons that are
consistent with the composite depiction of the group as a whole, in such a way that the
phenomenon and the person emerge as real.
(Adapted from Moustakas, 1990)
References
Moustakas, C. (1990). Heuristic research. Newbury Park, CA: Sage.
Data Analysis Methods in Heuristic Inquiry
Douglass, B. & Moustakas, C. (l985). Heuristic inquiry: The internal search to know. Journal of humanistic psychology, 25(3), 39-55.
Moustakas, C. (1967) Heuristic research. In J.F.T. Bugental (Ed.) Challenges of Humanistic Psychology. McGraw-Hill.
Moustakas, C. (1981) Heuristic methods of obtaining knowledge. In C. Moustakas, Rhythms, Rituals, and Relationships. Center for Humanistic Studies.
Moustakas, C. (1990) Heuristic Research: Design, methodology and applications. Newbury Park, CA: Sage.
Moustakas, C. (2001) Heuristic research: Design and Methodology. In K.J. Schneider, J.F.T. Bugental & J.F. Pierson, (Eds.) The Handbook of Humanistic Psychology: Leading edges in theory, research, and practice. Sage.
Polanyi, M. (l966). The tacit dimension. Garden City, New York: Anchor Books Doubleday and Company, Inc.
Detailed Step-by-Step Procedures for Data Analysis
Three Models of Phenomenological Analysis
Brennan, J. (1998). History and systems of psychology. Prentice-Hall: New Jersey.
Giorgi, A. (1985). Phenomenology and psychological research. Pittsburgh, PA: Duquesne University Press.
Giorgi, A. (1997). The theory, practice and evaluation of phenomenological methods as a qualitative research procedure. Journal of Phenomenological Psychology, 28, 235-281.
Giorgi, A.P. & Giorgi, B.M. (2003). The descriptive phenomenological psychological method. In Camic, P.M., Rhodes, J.E. & Yardley, L. (Eds.), Qualitative research in psychology: Expanding perspectives in methodology and design (pp. 243-273).
Washington, DC: American Psychological Association.
Moustakas, C. (1994). Phenomenological research. Thousand Oaks, CA: Sage.
Van Manen, M. (1990). Researching lived experience: Human science for an action sensitive pedagogy. Albany, NY: State University of New York Press.
Moustakas, C. (1990). Heuristic research. Newbury Park, CA: Sage.
1
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The material in this document comes from the HASOP manual Qualitative Research Approaches i
n
Psychology.
Data Analysis
Data analysis in ethnography: Thematic analysis and exemplary life
histories
Ethnography shares with the other four approaches a core method of data analysis, namely thematic
analysis. The other approaches may use different terms or specify slightly different procedures, but the
core analytic method is quite similar. We describe it briefly here in its ethnographic form, and we’ll
describe it briefly in its other forms when outlining the other approaches. Learners are advised to
master the general method regardless of the approach they select.
Once the data are collected by observations, interviews (audio taped and transcribed), field notes, or
any other sources, patterns of experience (recurring words, phrases, descriptions, etc.) are identifie
d
and listed. These patterns are derived from direct quotes and paraphrases of recurring ideas emerging
from the data. These patterns form the first level of thematic analysis.
Next, the researcher identifies data that correspond to the identified patterns. If, in a study of the cultu
re
of a corporation, a pattern is noted such as “males defer to hierarchically superior males, but not to
hierarchically superior females,” examples that confirm this – that show it is both recurring and an
accurate description of events – are located in the data (transcripts, notes, etc.) and annotated with the
listed pattern (as quotes along with citation of their source).
Now, the researcher combines and catalogues related patterns into themes. Themes are defined as
descriptive meaning units derived from the patterns. For example, if along with the earlier example this
pattern emerged: “males repeatedly initiate flirting behavior with females regardless of the females’ rank
and the females return the flirtation, even when they dislike it,” two themes or meaning units might be
constructed as follows: “Males impose rank-dominance on subordinate males” and “males impose
sexual-dominance on all females.”
Finally, at the highest level of abstraction, themes that emerge from the patterns (which emerged from
the original data) are synthesized together to form a comprehensive representation of the element o
f
the culture that is being investigated. The above meaning units or themes might constellate with oth
er
descriptive themes of the male and female interactions in the organization into a rich and textur
ed
description of the rules, customs, attitudes, and practices around gender in that organization.
This distillation of the practice of thematic analysis is adapted from Taylor and Bodgan (1984) and
Aronson (1994).
In writing 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. Perhaps a more accurate term would be “culture stories” or “organization stories.” The
objective is not to single out the individuals for study, but to use their experiences to exemplify key
themes found in the data. These representative life stories are not standard biographies or life histories
as might be found in biographical research.
These life or organizational stories are created in a process not unlike thematic analysis. Here,
however, the stories of the participants’ experience in the culture, group, society, or organization are
culled for the initial patterns of recurring experiences, behaviors, etc. These in turn are organized into
themes or meaning units which in a robust way exemplify important aspects of the larger culture,
society, group, or organization. Finally, as in thematic analysis, the meaning units are woven into a
richly evocative description of the meaning of the persons experience in this culture which stands for
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many others’ similar experiences. In effect, the life story (or the organization story, if you will) of the
exemplar “stands for” the essence of the ethnographic description of what it means to be a member of
this culture, group, or organization.
R
eferences
Aronson, J. (1994). A Pragmatic View of Thematic Analysis. The Qualitative Report, 2, Number 1.
Retrieved January 20,2003, from http://www.nova.edu/ssss/QR/index.html
Taylor, S, J. & Bogdan, R. (1984). Introduction to qualitative research methods: The search for
meaning. 2nd edition. New York: John Wiley.
Data analysis in case studies
Two types of data analysis for a case study are sometimes referred to (for example, Patton, 2005):
holistic analysis, in which the information about the entire case is analyzed; and embedded analysis, in
which information about a specific but limited aspect of the case is analyzed. For example, in a case
study of learners’ experiences with online education, if all aspects of the experience are studied – the
nature of the online platform, the IT support structure, the type of educational company providing the
online learning, the quality and training of the teachers, the nature of the curriculum, the demographics
of the learners, the costs and benefits perceived by the learners, the work load of the faculty, and so
on
and so forth – the analysis is said to be holistic.
However, if out of that mass of data only one aspect is analyzed and reported – for example, the
learners perceptions of the learning platform and of the instructors’ competence – this would be an
embedded analysis. A case study dissertation would most likely be a holistic analysis of a case or set of
cases.
There is no consensus format for case study data analysis, but a common series of steps can be found
in many sources. The following description is adapted from Creswell (1998) and Stake (1995).
• The opening step of data analysis – sometimes referred to as description – involves creating a
detailed description of the case as a whole and of its setting(s) and contexts. The objective is
both clarity and detail, creating a rich and textured picture of the case and its settings.
• The case study researcher looks at single instances in the described data and draws meaning
from each without (yet) looking for multiple instances. This process pulls the described data
apart and puts them back together in more meaningful ways. This may be called direct
interpretation.
• Next, the researcher seeks a collection of meaning-rich instances from the data, aggregating
these into categories of meaning, giving rise to the term categorical aggregation.
• By analyzing the categories (and the underlying instances and data of the various categories),
the researcher will identify themes – common statements of recurring description and patterns
of meaning – and connections between or among the themes. These themes will be developed
using verbatim passages and direct quotes from the data to elucidate each theme. At this point,
data from the case itself are used, without being compared yet with data and themes from other
cases; this is within-case analysis.
• The same steps are followed for each case in the series, so that each is analyzed within itself.
(For instance, if the study investigates ten cases of multiple sclerosis in young married people,
each person’s data are analyzed separately first, as a single case, before taking the next step)
• Then, the researcher will develop a thematic analysis across cases (across case analysis) as
well as interpretations of the integrated meaning of all the cases in the study.
• In the final, interpretive, phase, the researcher develops naturalistic generalizations from the
data as a whole and reports on the lessons learned from the case study.
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References
Creswell, J. (1998). Qualitative inquiry and research design: Choosing among five traditions. Thousand
Oaks, CA: Sage Publications, Inc.
Stake, R. (1995). The art of case study research. Thousand Oaks, CA: Sage.
Grounded theory data analysis methods and procedures: Coding
Because grounded theory goes beyond the descriptive and interpretive goals of many other qualitative
models and is aimed at building theories, data analysis tends to be more complex and aims to achieve
an explanatory power that is not necessary in other approaches. The heart of the grounded theory
approach occurs in its use of coding, its main form of data analysis. There are three different types of
coding used in a more-or-less sequential manner (this discussion is adapted from Strauss and Corbin,
1990, 1998, Patton, 2003; and Creswell, 1998).
The first type of coding is open coding which is much like the description goal of science. Usually open
coding is done first. During open coding, the researcher labels and categorizes the phenomena being
studied. This involves the process of describing the data through means such as examination,
comparison, conceptualization, and categorization. Labels are created to describe in one or a few
words the categories one finds in the data. Examples are collected for all these categories. For
example, in a grounded theory study of the effects of child sexual abuse, open coding might discover in
the reports of the participants some categories such as these: Feeling powerless, hating myself, hating
the abuser, or feeling permanently damaged.
The categories are studied more carefully to identify subcategories, which are called properties and
dimensionality in the categories. For instance, the researcher in our example might discover that “hating
myself” had a wide range of emotional power – in some participants it is very strong, whereas in others
it is not strong at all. The categories, properties, and dimensions discovered in the data are fully
described in the participants’ words.
Then begins the second type of coding: axial coding which involves finding links among the categories,
properties, and dimensions that were derived from open coding. (A link is an axis, hence the term
axial.) How is axial coding actually done?
Axial coding first identifies the central categories about the phenomenon. These central or core
categories tend to be the most important aspect(s) of element of the phenomenon, the one that clearly
has the greatest strength and appears in all or most of the participants’ reports or other data. For
instance, a central category of the phenomenon of the psychological effects of childhood sexual abuse
might be found to be “feelings of powerlessness.”
Next, the researcher explores the data carefully to discover causal conditions, which are categories of
conditions influencing the central category or categories. For instance, in the child sexual abuse study,
one causal condition might be found to be “repeated humiliations,” a condition that is found across
many reports to support or influence the development of feelings of powerlessness (the central
category).
The researcher continues axial coding by identifying interactions among the categories (which are
called strategies, although that term might be confusing). Strategies in the example study could be, for
example, “repeated humiliations strengthen feelings of powerless, but weaken hatred of the abuser
while strengthening self-hatred.” You might think of “strategies” in grounded theory as the equivalent of
correlations in statistical theory-building.
Axial coding continues with the identification and exploration of other supporting or weakening
conditions which exert lesser influences on the central variables. These are categories in the data
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which label the contexts and intervening conditions. Examples from the grounded theory study of the
effects of child sexual abuse might include “protection by another adult,” which when found to be
present ameliorates (positively influences) the central category, but which is insufficient in itself to
prevent the damage entirely. Finally, consequences are carefully identified and described. These would
include all the outcomes of the presence of the central category in all its interactions (strategies) w
ith
contexts, intervening conditions, properties, dimensions, etc. Consequences describe what happens
when the central category is found under specific conditions. For example, when “feelings of powerless”
are found to be very strong, accompanied (interacting with) “isolation” and “repeated humiliation,”
depression may be found to be a consequence.
Notice that these consequences are NOT presupposed, but are carefully teased out of the real reports
and descriptions of their experiences by the many participants in the study. Preconceptions about the
theory must be left at the door. See “Phenomenology,” below, and its discussion of epoche and the
phenomenological reduction. Without using the terminology of phenomenology, the requirement is the
same.
The third type of coding is selective coding continues the axial coding activity of relating the subsidiary
categories to the central category(s). Selective coding is the process of selecting your main
phenomenon (core category) around which all other phenomena (subsidiary categories) are grouped,
arranging the groupings, studying the results and rearranging where necessary. It is necessary to
remain faithful to the data, so in selective coding, one frequently goes “back to the things themselves”
to ensure that one is capturing what one’s informants told one.
From this last type of coding, the grounded theory researcher moves toward developing a model of
process and a transactional system, which essentially tells the story of the outcome of the research.
Creating a literal “story line” is one manner of doing selective coding. The story line tells the results of
the axial coding in a coherent narrative. Many grounded theory researchers do not create a conditional
matrix, a diagram or picture of the various categories, interactions, and relationships among the central
category(s) and the subsidiary categories. But the conditional matrix is a very helpful tool in creating the
narrative story line which embodies the grounded theory.
The selective coding process typically focuses on two dimensions of the phenomenon: its process and
its transactional system. Again, the conditional matrix is quite useful in elucidating these two elements
of the theory.
• Process is the manner in which actions and interactions occur in a sequence or series. It
incorporates the time element. (“As time went on and I got older, the repeated humiliations
my father inflicted on me began to tear me apart. I started to hate myself, though not
at
first.”) It also incorporates the various categories which mutually influenced each other.
(“My brother tried to help, and I was grateful, but I was more worried he’d get hurt, so I
asked him to stay out of it. He hasn’t been much a part of my life since.”)
• The transactional system is a grounded theory’s analytic method that allows an
examination of the interactions of different events. (“Self-hatred led to increased willingness
to be hurt. It strengthened the belief among most participants that the victim is bad and
deserves punishment, and also strengthened the yearning for even the abusive “love”
offered by the perpetrator. This in turn alienated most participants from other sources of
more benign love, because the victims did not feel worthy of it.”)
The use of the conditional matrix and the process and transactional-system analysis leads finally to the
general description of the grounded theory. It might be a brief sentence distilling all the above work, or a
more complex statement. But it will also be accompanied by a set of propositions or hypotheses which
menon under study. explain the pheno
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At this stage, it is usual for grounded theory researchers to return not only to the original data to ensure
that the theory fits those data, but may meet with the participants again to compare the theory wit
perceptions and to ask them whether the theory fits their experiences. Their responses will be taken as
new data to be incorp
h their
orated into the theory, which is thought to be in a continual adaptation and
volution. Grounded theory is never complete. (Adapted from Strauss, & Corbin, 1990, 1998; Creswell,
2002)
d
ge.
trauss, A., Corbin, J. (1998). Basics of qualitative research: Techniques and theory for developing
grounded theory (2nd ed.). Newbury Park, CA: Sage.
e a
method of analysis of phenomenological data are acceptable in the General Psychology specialization.
ed provided they meet (are equivalent to) the criteria described in these pages.
r deeper
comparison. These segments (or “meaning units” as described above) will be organized
ematically in two major ways: within the context of a single interview, and across a series of
ed
g
erviews” would not have been possible unless the
dividual phrases could have been cut out and kept in a separate “meaning unit” document of some
ings that emerge from the data in their own terms. If we include these two preliminary steps with
e
1998; Patton,
References
Creswell, J. (1998). Qualitative inquiry and research design: Choosing among five traditions. Thousan
Oaks, CA: Sage Publications, Inc.
Patton, M. (2002). Qualitative research and evaluation methods (3rd ed.). Newbury Park, CA: Sa
Strauss, A., Corbin, J. (1990). Basics of qualitative research: Grounded theory procedures and
techniques. Newbury Park, CA: Sage.
S
Phenomenological Data Analysis
Most standard texts (e.g., Creswell, 1998; Patton, 2002; or Taylor and Bogdan, 1984) propos
general five-step model for phenomenological analysis. These steps are elaborated in three more
detailed models described in Appendix A (see “empirical phenomenology” [Amedeo Giorgi],
“transcendental phenomenology” [Clark Mousakas] and the Stevick-Colaizzi-Keen Method of Analysis
of Phenomenological Data). The Giorgi model, the Moustakas model, and the Stevick-Colaizzi-Keen
Other models can be us
Preliminary steps
The generic method of analysis consists of five essential steps, but is preceded by careful preparation
of the data and of the researcher. First, the data must be transformed into written form – usually
transcripts of interviews – which can be studied as a whole and, later, in bits or units. Word processing
programs are ideal for this, allowing both retention of the original interview in “raw” form and “cutting
and pasting” individual segments (phrases, sentences, paragraphs) into separate documents fo
analysis and
th
interviews.
For example, in a series of phenomenological interviews on the experience of grief in children, the
researcher found that participant A repeated the phrase, “she left me behind” many times in talking
about what it was like to lose his mommy. Within the context of that child’s experience, being “left
behind” became a very significant part of the experience, a “meaning unit.” Meanwhile, child B repeat
the phrase “she’s gone, I can’t find her” a number of times. This too was a meaning unit for child B.
Looking across both transcripts and comparing the two meaning units and reflecting deeply on them
and their contexts in the interviews, the researcher teased out a deeper level of meaning by comparin
the two different units: “I feel lost.” This “across int
in
kind, which word processing makes quite handy.
Before starting to analyze data, though, the researcher does a second preparatory step, which as been
described briefly above as the “phenomenological reduction.” She attempts to reduce the impact of his
or her biases, preconceptions, and beliefs about the phenomenon and opening oneself to the data and
mean
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the five steps proposed by most texts, we have a generic seven-step model for data analysis, beginning
Step 1 and 2: Prepare the data and adopt the phenomenological attitude (“reduction” or “epoche” [see
below].)
tep 3: Achieve a Sense of the Whole. The researcher reads the entire description in order to get a
oes
de
ith psychological criteria in mind. The researcher next eliminates redundancies and clarifies and
concrete
ants, reflects on them, and comes up with the essence of the experience for the
articipant. The researcher next transforms each relevant unit’s essence into the language of
ere, the researcher synthesizes all of the transformed meaning units (now expressed in
e language of psychological science) into a consistent statement regarding the participant’s
r synthesizes all of the essence or structure statements
regarding each participant’s experience into one consistent statement, which describes and captures
d
above. Either of the
odels is acceptable for phenomenological research in the General Psychology specialization. The
at
tive
rationale should be approved by the mentor (and the dissertation committee, of course)
nd reviewed (with a rating of “Satisfactory” or better) by the Methodology Committee of the
85,
gy”)
Ernest Keen of Bucknell University (1975) and Paul F. Colaizzi and Emily M. Stevick of Duquesne
with:
Steps in phenomenological data analysis: Generic model
S
general sense of the whole statement.
Step 4: Discrimination of Meaning Units Within a Psychological Perspective and Focused on the
Phenomenon Being Researched. Once the sense of the whole has been grasped, the researcher g
back to the beginning and reads through the text once more and delineates each time that a transition
in meaning occurs. The specific aim is to discriminate “meaning units” from within a psychological
perspective and with a focus on the phenomenon being researched. The meaning unit should be ma
w
elaborates on the meaning of the units by relating them to each other and to the sense of the whole.
Step 5: Transformation of Subjects Everyday Expressions into Psychological Language with Emphasis
on the Phenomenon Being Investigated. Once meaning units have been delineated and linked
together, the researcher goes through all of the meaning units, which are still expressed in the
language of the particip
p
psychological science.
Step 6: Synthesis of Transformed Meaning Units into a Consistent Statement of the Structure of the
Experience. H
th
experience.
Step 6: Final Synthesis: Finally, the researche
the essence of the experience being studied.
Acceptable Models of Phenomenological Analysis
The generic model described above is elaborated in two acceptable and detailed models of
psychological phenomenological analysis developed by Amedeo Giorgi at Duquesne University an
Clark Moustakas at the Center for Humanistic Studies and The Union Institute. Each of these models is
detailed and provides a stepwise guide to the seven generic steps presented
m
Moustakas model is further elaborated in the Stevick-Colaizzi-Keen model.
A learner may adopt a different model for the data analysis, provided that the alternative model is
least as clearly articulated and provides at least as much guidance for procedures as the accepted
models. The learner should prepare a careful description of and rationale for using an alterna
model, and that
a
Specialization.
The Giorgi model (usually called “empirical phenomenology” or “phenomenological psychology”) (19
1997) (Giorgi & Giorgi, 2003) and the Moustakas model (often called “transcendental phenomenolo
and the “Stevick-Colaizzi-Keen Model” synthesized by Moustakas (1994) and based on the work of
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University are described more fully in Appendix A. They differ from each other and from the generic
model above only in the ways in which they outline the procedures. Each provides much more detail
bout how to proceed in each step or stage.
eferences
Creswe research design: Choosing among five traditions. Thousand
Giorgi, A ). Phenomenology and psychological research. Pittsburgh, PA: Duquesne University
Giorgi, A s a qualitative
Giorgi, A amic,
ng
y and design (pp. 243-273). Washington, DC: American
Keen, E ogy phenomenologically. Unpublished Manuscript. Lewisberg, PA:
rd age.
Taylor, itative research methods: The search for
meaning. 2nd edition. New York: John Wiley.
uld
e the researcher (who performs them) is a
articipant, they already are a form of data collection.
n.
form of the phenomenological
duction or epoche (see Appendix A for a description of epoche).
other forms of self-expression may become the
rimary mode of both data collection and data analysis.
ith
a
R
ll, J. (1998). Qualitative inquiry and
Oaks, CA: Sage Publications, Inc.
. (1985
Press.
. (1997). The theory, practice and evaluation of phenomenological methods a
research procedure. Journal of Phenomenological Psychology, 28, 235-281.
.P. & Giorgi, B.M. (2003). The descriptive phenomenological psychological method. In C
P.M., Rhodes, J.E. & Yardley, L. (Eds.), Qualitative research in psychology: Expandi
perspectives in methodolog
Psychological Association.
. (1975). Doing psychol
Bucknell University.
Moustakas, C. (1994). Phenomenological research methods. Thousand Oaks, CA: Sage.
Patton, M. (2002). Qualitative research and evaluation methods (3 ed.). Newbury Park, CA: S
S, J. & Bogdan, R. (1984). Introduction to qual
Data Analysis Methods in Heuristic Inquiry
In general, six steps characterize the heuristic approach to data analysis. They are as follows: initial
engagement, immersion, incubation, illumination, explication and synthesis (Douglass and Moustakas,
l985; Moustakas, , 1967, 1981, 1990, 2001). Steps 1 and 2 (initial engagement and immersion) wo
appear to be preliminary to data collection, but becaus
p
Step 1: Initial engagement involves and awareness of the topic. In heuristics it is essential that the
topic not only be of importance to the researcher but also that he/she experiences a sense of passion in
connection with it. From the experience of being with the topic in an open way emerges the questio
The culmination of the initial engagement period is the creation of a clear research question which
forms the heart of the inquiry. Initial engagement requires the researcher to reduce the influence of
preconceptions and beliefs about the phenomenon, so it includes a
re
Step 2: During the immersion step, the researcher makes his/her question the center of the
experiential world, allowing the self to become one with the question. This is done in a loose, non-
structured way, permitting openness to the range of related experiences, which helps to facilitate an
understanding of the phenomenon. During this step, the researcher is non-judgmental and non-critical,
open to the flow of experience (again, a version of the phenomenological reduction). The researcher is
open to intuitions (hunches based on clues) and tacit knowledge (knowing that he/she knows but not
knowing how he/she knows). At this stage, journaling or
p
During immersion, heuristic researchers also gather information from their co-researchers, in the form
of interviews, diaries, journals, writings, art, film, etc.., and immerse themselves in those data along w
their own data. Typically, each researcher finds a personal method for immersing oneself in the data
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that are emerging from the interviews and other documents. As can be seen, data “collection” and d
“analysis” are not easily separated into d
ata
iscrete steps or stages, but are an integrated and ongoing
process each informing the other.
d on
re
el. No
y the engaged
searcher will be “present” to the process and reflecting often on how it is going.
er
n
n learner, because the time-and-money pressures of the four-course, one-year model can be
factor.
erves
s
d
on
indwelling and reflection
e essential structures of the experience of the phenomenon under study.
f
heuristic inquiry is similar to the “final synthesis” in the generic model of
phenomenological analysis.
uestion or problem AND (2) to develop portraits of the persons who have explicated the experience.
eferences
Douglas inquiry: The internal search to know. Journal of
Mousta arch. In J.F.T. Bugental (Ed.) Challenges of Humanistic
Psychology. McGraw-Hill.
Step 3: After a period of time, having been immersed in the research question, the researcher puts
aside all deliberate focus on the experience and the data and allows the information to be processe
an unconscious level, a process known as incubation. When this becomes appropriate cannot be
arbitrarily specified, but depends on the data themselves. A common marker is when new themes are
no longer emerging in the data ( a condition sometimes called saturation). During incubation, data a
no longer being collected intentionally (although new insights may emerge or new information may
arise). Instead, the researcher allows the data to “go unconscious” and to be processed at that lev
intentional (conscious) work is done to further the interpretation, although obviousl
re
Step 4: The information continues to consolidate and grow (“incubate”) until a sense of discovery
occurs. This moment of realization and enlightenment is known as illumination, and often has the fell
of an “Aha!” experience. At this point, new knowledge is obtained, representing a whole that is great
than the sum of its parts. The great danger here is that the researcher will succumb to pressures of
time, money, or expediency and “force” an illumination which is not authentic. Because the incubatio
period (step 3) is by nature an unconscious process, it is unpredictable. One cannot know ahead of
time when insight or illumination will emerge. This provides an alement of risk to the Capella University
dissertatio
a
Step 5: The next step is explication. During the explication phase, the researcher returns to the data
(transcripts, documents, etc.), and with the new insights gained during the illumination phase, obs
the patterns and themes arising which portray essential meanings. This is a version of “thematic
analysis” as discussed in the section on ethnography. Indwelling is used to dwell within the experiences
and draw meaning from them. Polanyi (l966) refers to indwelling as follows: “It brings home to us that
it is not by looking at things, but by dwelling in them, that we understand their joint meaning” (p. l8). Thi
phase resembles the earlier immersion phase, with the difference that now one dwells in the data an
their emerging meanings and structures in order to interpret them, whereas in the earlier immersi
phase, one was immersed in the articulation of the phenomenon itself and in gathering similar
articulations from one’s co-researchers. The goal of step 5 is to articulate by
th
Step 6: The final step in a heuristic inquiry is synthesis. It is through synthesis that the whole
experience is captured. Synthesis is more than a summary, it is the creation of a new understanding o
the essence of the experience. “Synthesis goes beyond distillation of themes and patterns. It is not a
summary or recapitulation. In synthesis, the searcher is challenged to generate a new reality, a new
monolithic significance that embodies the essence of the heuristic truth” (Douglass and Moustakas,
l985, p. l7). The synthesis in
The task is (l) to arrive at a depiction of the experience, a synthesizing statement that illuminates the
q
R
s, B. & Moustakas, C. (l985). Heuristic
humanistic psychology, 25(3), 39-55.
kas, C. (1967) Heuristic rese
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Moustakas, C. (1981) Heuristic methods of obtaining knowledge. In C. Moustakas, Rhythms, Rituals,
and Relationships. Center for Humanistic Studies.
Moustakas, C. (1990) Heuristic Research: Design, methodology and applications. Newbury Park, CA:
Sage.
Moustakas, C. (2001) Heuristic research: Design and Methodology. In K.J. Schneider, J.F.T. Bugental
& J.F. Pierson, (Eds.) The Handbook of Humanistic Psychology: Leading edges in theory,
research, and practice. Sage.
Polanyi, M. (l966). The tacit dimension. Garden City, New York: Anchor Books Doubleday and
Company, Inc.
Detailed Step-by-Step Procedures for Data Analysis
Three Models of Phenomenological Analysis
A. Empirical Phenomenology is a model of phenomenological psychological research that was
developed at Duquesne University (Giorgi, 1985, 1997; Giorgi & Giorgi, 2003).
In order to develop an understanding of the phenomenological psychological research method,
it is essential to first understand the concept of intentionality and its role in the
phenomenological method. The following passage from Amedeo Giorgi (1997) explains the
role of intentionality in phenomenology.
Finally, no discussion of phenomenology would be complete without mentioning intentionality.
Edmund Husserl took the term over from Franz Bretano but uses it in a fundamentally different
way. For Husserl, intentionality is the essential feature of consciousness, and it refers to the
fact that consciousness is always directed to an object that is not itself consciousness, although
it could be, as in reflective acts. More precisely, consciousness always takes an object, and the
object always transcends the act in which it appears. This idea is important for the human
sciences as well, since it helps overcome the Cartesian understanding of the subject-object
relationship. There are not two independent entities, objects and subjects, existing in
themselves which later get to relate to each other, but the very meaning of subject implies a
relationship to an object, and to be an object intrinsically implies being related to subjectivity.
Thus, the subject object relationship must be understood structurally and holistically (p. 237).
In the philosophical phenomenological method there are three interlocking steps: (1) the
phenomenological reduction, (2) description and (3) search for essences. The
phenomenological reduction is a methodological device devised by Husserl that is used to
make research findings, which use the phenomenological model more precise. During the
phenomenological reduction, one brackets past knowledge about the phenomenon
encountered in order to be fully present to it as it is in the concrete situation in which one is
encountering it. One puts aside or renders “non-influential” all past knowledge that may be
associated with the presently given object.
The researcher cannot expect all participants in the psychological phenomenological study to
be phenomenological and, thus, capable of assuming the attitude of the phenomenological
reduction. Moreover, for human science research, the details, biases, errors, and prejudices
that we carry with us in everyday life are exactly what have to be understood in psychological
phenomenological research. What is critical is that the description be as precise and detailed
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as possible with a minimum number of generalities and abstractions. However, the
phenomenological attitude does demand that the researcher be able to do his/her work from
within the attitude of the reduction or else no phenomenological claims for the analysis could be
made.
There are two descriptive levels of the empirical phenomenological model:
Level 1, the original data is comprised of naïve descriptions obtained through open-ended
questions and dialogue.
Level II, the researcher describes the structures of the experiences based on reflective analysis
and interpretation of the research participant’s account or story.
The method of analysis consists of five essential steps which are as follows:
1) Sense of the Whole – One reads the entire description in order to get a general sense
of the whole statement.
2) Discrimination of Meaning Units Within a Psychological Perspective and Focused on
the Phenomenon Being Researched – Once the sense of the whole has been grasped,
the researcher goes back to the beginning and reads through the text once more and
delineates each time that a transition in meaning occurs with the specific aim of
discriminating “meaning units” from within a psychological perspective and with a focus
on the phenomenon being researched. The meaning unit should be made with
psychological criteria in mind. The researcher next eliminates redundancies and
clarifies and elaborates on the meaning of the units by relating them to each other and
to the sense of the whole.
3) Transformation of Subjects Everyday Expressions into Psychological Language with
Emphasis on the Phenomenon Being Investigated – Once meaning units have been
delineated, the researcher goes through all of the meaning units, which are still
expressed in the concrete language of the participants, reflects on them and comes up
with the essence of the experience for the participant. The researcher next transforms
each relevant unit into the language of psychological science.
4) Synthesis of Transformed Meaning Units into a Consistent Statement of the Structure
of the Experience – Finally, the researcher synthesizes all of the transformed meaning
units into a consistent statement regarding the participant’s experience.
5) Final Synthesis – Finally the researcher synthesizes all of the statements regarding
each participant’s experience into one consistent statement, which describes and
captures the essence of the experience being studied.
(Adapted from Giorgi, 1985, 1997; Giorgi & Giorgi, 2003)
B. Transcendental Phenomenology -There are three core processes that facilitate derivation of
knowledge in the transcendental phenomenological approach as proposed by Clark Moustakas
(1994). The three core processes are: Epoche, Transcendental- Phenomenological
Reduction and Imaginative Variation.
1) Epoche: Setting aside prejudgments and opening the research interview with an
unbiased, receptive presence. It is returning to things themselves, free of
prejudgments and preconceptions.
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2) Transcendental Phenomenological Reduction: The task is that of describing in textual
language just what one sees, not only in terms of the external object but also the
internal act of consciousness, the experience as such, the rhythm and relationship
between phenomenon and self. Textual qualities are as follows: rough and smooth;
small and large; quiet and noisy; colorful and bland; hot and cold; stationary and
moving; high and low; squeezed in and expansive, fearful and courageous; angry and
calm – descriptions that present varying intensities; ranges of shapes, sizes and
special qualities; time references and colors within an experiential context.
a. Bracketing the Topic or Question – The focus of the research is placed in
brackets, everything else is set aside so that the entire research process is
rooted solely on the topic and question.
b. Horizonalizaton – Every statement is treated as having equal value.
c. Statements irrelevant to the topic or question as well as those that are
repetitive or overlapping are deleted, leaving only the Horizons (the textual
meaning and invariant constituents of the phenomenon)
d. Delimiting Horizons or Meanings: Horizons that stand out as invariant
qualities of the experience.
e. Invariant Qualities and Themes – Non-repetitive, non-overlapping
constituents are clustered into themes.
f. Individual Textual Descriptions – Develop integration, descriptively, of the
invariant textural constituents and themes of each research participant.
g. Composite Textual Description – Develop integration of all of the individual
textual descriptions into a group or universal textual description.
3) Imaginative Variation: The task of Imaginative Variation is to seek possible meanings
through the utilization of imagination, varying frames of reference, employing polarities
and reversals, and approaching the phenomenon from divergent perspectives, different
positions roles or functions. The aim is to arrive at structural descriptions of an
experience, the underlying and precipitating factors that account for what is being
experienced; in other words the “how” that speaks to conditions that illuminate the
“what” of experience. How did the experience of the phenomenon come to be what it
is? The steps to Imaginative Variation are as follows:
a. Systematic varying of the possible structural meanings that underlie the
textural meanings. Vary perspectives of the phenomenon from different
vantage points, such as opposite meanings and various roles. Using free
fantasy variations, consider freely the possible structural qualities or
dynamics that evoke structural qualities.
b. Construct a list of the structural qualities of the experience.
c. Recognizing the underlying themes or contexts that account for emergence
of the phenomenon.
d. Develop structural themes by clustering the structural qualities into themes.
e. Considering the universal structures that precipitate feelings and thoughts
with reference to the phenomenon, such as: time, space, bodily concerns,
materiality, causality, relation to self, or relation to others;
f. Individual Structural Descriptions: For each participant, integrate the
structural qualities and themes into an individual structural description of
the experience.
g. Composite Structural Description: Integration of all of the individual
structural descriptions into a group or universal structural description of the
experience.
4) Synthesis of Meanings and Essences: The final step in the phenomenological
research process is the intuitive integration of the composite textual and structural
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descriptions into a unified statement of the essences of the experience of the
phenomenon as a whole. The essences of any experience are never totally
exhausted. The fundamental textual-structural synthesis represents the essences at a
particular time and place from the vantage point of an individual researcher following
an exhaustive imaginative and reflective study of the phenomenon.
(Adapted from Moustakas, 1994)
C. Stevick-Colaizzi-Keen Method of Analysis of Phenomenological Data (See Flow Chart in
Appendix B)
Epoche is the first step in the phenomenological method and is a process in which the
researcher sets aside all preconceived ideas about what is being experienced and described by
the participants. Phenomenological Reduction is the process by which the participant describes
in textual language just what one sees, not only in terms of the external object but also the
internal act of consciousness, the experience under inquiry as such, the rhythm and
relationship between phenomenon and self. Textual qualities are as follows: rough and
smooth; small and large; quiet and noisy; colorful and bland; hot and cold; stationary and
moving; high and low; squeezed in and expansive, fearful and courageous; angry and calm –
descriptions that present varying intensities; ranges of shapes, sizes and special qualities; time
references and colors within an experiential context. During this step in the phenomenological
process, the textural qualities of the lived experience of the participant are separated. Those
comments that deal with the question are clustered into themes (Moustakas, 1994).
Following the Phenomenological Reduction, the researcher uses imaginative variation. The
task of imaginative variation is to seek possible meanings through the utilization of imagination,
varying frames of reference, employing polarities and reversals, and approaching the
phenomenon from divergent perspectives, different positions roles or functions. The aim is to
arrive at structural descriptions of an experience, the underlying and precipitating factors that
account for what is being experienced; in other words, the “how” that speaks to conditions that
illuminate the “what” of experience. How did the experience of the phenomenon come to be
what it is? Through the use of imaginative variation the researcher examines the data collected
from participants from different views, changing the frames of reference, using polarities and
reversals, and looking at the phenomenon from different perspectives, positions, roles, or
functions. Employ universal structures as themes: time, space, materiality, relationship to self,
relationship to others, bodily concerns, causal and intentional structures.
The final step of the process is called intuitive integration. Intuitive integration is the process by
which the researcher develops textural-structural synthesis that represents the essence of the
experience of the phenomenon under inquiry (Moustakas, 1994).
The steps to the modified Stevick-Colaizzi-Keen Method of Analysis of
Phenomenological Data are as follows:
1) Set aside all preconceived ideas about what is being experienced and described
by the participant (Epoche).
2) Consider each statement with the emphasis on the importance for description of
the experience.
3) Record all of the relevant statements dealing with the experience.
4) Make a list of every non-repetitive, non overlapping statement. These constitute
the invariant horizons or meaning units of the experience.
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5) Cluster the invariant meaning units into themes.
6) Organize the invariant meaning units and themes into a description of the
textures of the experience (textural description). Include direct quotes and
verbatim passages from the participants.
7) Reflect on the textual descriptions. Through the use of imaginative variation,
develop a description of the structures of these experiences (structural
description).
8) Construct a textural-structural description of the meanings and essences of the
experiences for the individual participant.
9) Once this process is completed for the data collected from each participant in the
study, synthesize all of these descriptions into a composite textural-structural
description of the experience representing the essence of the experience of the
participants in the study as a whole. Thus, developing a composite textural-
structural synthesis, which represents the lived experience of the subject under
investigation for participants involved in the study.
(Adapted from Moustakas, 1994)
References
Brennan, J. (1998). History and systems of psychology. Prentice-Hall: New Jersey.
Giorgi, A. (1985). Phenomenology and psychological research. Pittsburgh, PA: Duquesne University
Press.
Giorgi, A. (1997). The theory, practice and evaluation of phenomenological methods as a qualitative
research procedure. Journal of Phenomenological Psychology, 28, 235-281.
Giorgi, A.P. & Giorgi, B.M. (2003). The descriptive phenomenological psychological method. In Camic,
P.M., Rhodes, J.E. & Yardley, L. (Eds.), Qualitative research in psychology: Expanding
perspectives in methodology and design (pp. 243-273).
Washington, DC: American Psychological Association.
Moustakas, C. (1994). Phenomenological research. Thousand Oaks, CA: Sage.
Van Manen, M. (1990). Researching lived experience: Human science for an action sensitive
pedagogy. Albany, NY: State University of New York Press.
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Appendix B Flow chart of Keen’s version of transcendental phenomenological data
analysis
Step 1:
Epoche
Step 2: Phenomenological
reduction
Step 3: Imaginative Variation
Step 4: Intuitive synthesis
Epoche is the first step in the phenomenological method and is a process in which the researcher sets
aside all preconceived ideas about what is being experienced and described by the participants.
Phenomenological researchers develop their own techniques, often involving meditative or awareness
techniques (such as mindfulness meditation, journaling, and the like) to become aware of the arising of
biases or biasing thoughts).
Phenomenological Reduction is the process by which the participant describes in textual language just
what one sees, not only in terms of the external objects but also the internal act of consciousness, the
experience under inquiry as such, the rhythm and relationship between phenomenon and self. During
this step in the phenomenological process, the textural qualities of the lived experience of the
participant are separated and a textural description is developed.
The task of imaginative variation is to seek possible meanings through the utilization of imagination,
varying frames of reference, employing polarities and reversals, and approaching the phenomenon
from divergent perspectives, different positions roles or functions. The aim is to arrive at structural
descriptions of an experience, the underlying and precipitating factors that account for what is being
experienced; in other words, the “how” that speaks to conditions that illuminate the “what” of
experience.
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The final step of the process is called intuitive integration. Intuitive integration is the process by which
the researcher develops textural-structural synthesis that represents the essence of the experience of
the phenomenon under inquiry
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Appendix C Flow chart of Generic thematic analysis of Qualitative Data
Step 1: Patterns of experience are identified: recurring
words and phrases are identified and summarized.
These are called meaning units.
Step 2: Confirming data (specific words, phrases, etc.) are
linked to the meaning units from step 1.
Step 3: Related patterns or meaning units (steps 1 & 2) are combined into
themes.
Step 4: Themes are synthesized to form a comprehensive
description of the phenomenon.
Patterns of experience or meaning units
Once the data are collected by observations, interviews (audio taped and transcribed), field notes, or
any other sources, patterns of experience (recurring words, phrases, descriptions, etc.) are identified
and listed. These patterns are derived from direct quotes and paraphrases of recurring ideas emerging
from the data. These patterns form the first level of thematic analysis.
Linking the data themselves to the meaning units (confirming the meaning units)
Next, the researcher identifies data that correspond to the identified patterns. If, in a study of the culture
of a corporation, a pattern is noted such as “males defer to hierarchically superior males, but not to
hierarchically superior females,” examples that confirm this – that show it is both recurring and an
accurate description of events – are located in the data (transcripts, notes, etc.) and annotated with the
listed pattern (as quotes along with citation of their source). This step is critical, because it provides
confirming evidence that the meaning units have emerged directly from the data themselves and not
from the researcher’s biases or preconceptions. This step also provides the material for substantiating
the “results” section of the dissertation (typically Chapter Four).
Creating Themes
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Now, the researcher combines and catalogues related patterns into themes. This is a more abstract
step, during which the researcher must beware the intrusion of bias, preconceptions, beliefs, etc.
Themes are comprised of combinations and distillations of the descriptive meaning units derived from
the patterns in the data. For example, if along with the earlier example this pattern emerged: “males
repeatedly initiate flirting behavior with females regardless of the females’ rank and the females return
the flirtation, even when they dislike it,” two themes or meaning units might be constructed as follows:
“Males impose rank-dominance on subordinate males” and “males impose sexual-dominance on all
females.”
Synthesis of themes
Finally, at the highest level of abstraction, themes that emerge from the patterns or meaning units
(which emerged from the original data) are synthesized together to form a comprehensive
representation of the element of the culture that is being investigated. The above meaning units or
themes might constellate with other descriptive themes of the male and female interactions in the
organization into a rich and textured description of the rules, customs, attitudes, and practices around
gender in that organization.
This distillation of the practice of thematic analysis is adapted from Taylor and Bodgan (1984) and
Aronson (1994)
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Appendix D Moustakas’ Description of Data Analysis in Heuristic Research
1) Place all the material drawn from one participant before you (recordings, transcriptions,
journals, notes, poems, art work, etc.). This material may either be data gathered by self-search
or by interviews with co-researchers.
2) Immerse yourself fully in the material until you are aware of and understand everything that is
before you.
3) Put the material aside for a while. Let it settle in you. Live with it but without particular attention
or focus. Return to the immersion process. Make notes where these would enable you to
remember or classify the material. Continue the rhythm of working with the data and resting
until an illumination or essential configuration emerges. From your core or global sense, list the
essential components or themes that characterize the fundamental nature and meaning of the
experience. Reflectively study the themes, dwell inside them, and develop a full depiction of
the experience. The depiction must include the essential components of the experience.
4) Illustrate the depiction of the experience with verbatim samples, poems, stories, or other
materials to highlight and accentuate the person’s lived experience.
5) Return to the “raw material” of your co-researcher (participant). Does your depiction of the
experience fit the data from which you have developed it? Does it contain all that is essential?
Complete the above steps for each participant. Then:
a) Place the Reflective Depiction for each participant before you.
b) Immerse yourself completely in the Reflective Depictions until you are fully aware of and
understand what they contain.
c) Put the material aside and engage in a rhythm of rest and work until the essential invariant and
non-repetitive themes of the material stand out.
d) Make a list of the essential components of the experience (these should portray the qualities,
nature, and meanings that characterize the experience).
e) From the above, develop a full reflective depiction of the experience, one that characterizes the
participants as a group, reflecting core meanings not only for the individuals but the group of
persons as a whole. Include in the depiction, verbatim samples, poems, stories, etc., to
highlight and accentuate the lived nature of the experience. This depiction will serve as the
creative synthesis, which will combine, in an esthetically pleasing way, the themes and patterns
into a representation of the whole. This synthesis will communicate the essence of the lived
experience under inquiry. The synthesis is more than a summary – it is like a chemical
reaction, a creation of anew.
f) Return to the individuals, select two or three and develop portraits of these persons that are
consistent with the composite depiction of the group as a whole, in such a way that the
phenomenon and the person emerge as real.
(Adapted from Moustakas, 1990)
References
Moustakas, C. (1990). Heuristic research. Newbury Park, CA: Sage.
Data Analysis Methods in Heuristic Inquiry
Douglass, B. & Moustakas, C. (l985). Heuristic inquiry: The internal search to know. Journal of humanistic psychology, 25(3), 39-55.
Moustakas, C. (1967) Heuristic research. In J.F.T. Bugental (Ed.) Challenges of Humanistic Psychology. McGraw-Hill.
Moustakas, C. (1981) Heuristic methods of obtaining knowledge. In C. Moustakas, Rhythms, Rituals, and Relationships. Center for Humanistic Studies.
Moustakas, C. (1990) Heuristic Research: Design, methodology and applications. Newbury Park, CA: Sage.
Moustakas, C. (2001) Heuristic research: Design and Methodology. In K.J. Schneider, J.F.T. Bugental & J.F. Pierson, (Eds.) The Handbook of Humanistic Psychology: Leading edges in theory, research, and practice. Sage.
Polanyi, M. (l966). The tacit dimension. Garden City, New York: Anchor Books Doubleday and Company, Inc.
Detailed Step-by-Step Procedures for Data Analysis
Three Models of Phenomenological Analysis
Brennan, J. (1998). History and systems of psychology. Prentice-Hall: New Jersey.
Giorgi, A. (1985). Phenomenology and psychological research. Pittsburgh, PA: Duquesne University Press.
Giorgi, A. (1997). The theory, practice and evaluation of phenomenological methods as a qualitative research procedure. Journal of Phenomenological Psychology, 28, 235-281.
Giorgi, A.P. & Giorgi, B.M. (2003). The descriptive phenomenological psychological method. In Camic, P.M., Rhodes, J.E. & Yardley, L. (Eds.), Qualitative research in psychology: Expanding perspectives in methodology and design (pp. 243-273).
Washington, DC: American Psychological Association.
Moustakas, C. (1994). Phenomenological research. Thousand Oaks, CA: Sage.
Van Manen, M. (1990). Researching lived experience: Human science for an action sensitive pedagogy. Albany, NY: State University of New York Press.
Moustakas, C. (1990). Heuristic research. Newbury Park, CA: Sage.
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Example
Data Analysis Strategies – Peer Review – Alex Bratty, I/O Psychology
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This posting will discuss the key elements of data analysis for a phenomenological investigation, the specific data analysis strategy that would be used with this methodology, and an evaluation of its effectiveness. A brief overview of the research topic, question, and sampling is provided for context.
Overview of Research Topic, Question, & Sampling
The proposed research topic is to explore the experience of flourishing in the workplace for full-time corporate managers. As such, a question derived from the research topic that would be suitable for a phenomenological investigation could be, what is the essence of flourishing at work for corporate managers? The primary form of data collection would be open-ended, in-depth interviews, and it is proposed that at least n = 10 corporate managers would be interviewed, consistent with the range of 3 to 25 participants recommended for phenomenology (Creswell & Poth, 2018).
Data Analysis for Phenomenology
Although a phenomenological study includes more detailed steps, it still follows the general qualitative data analysis approach. This consists of five broad phases, including (1) preparing and organizing the data, (2) reviewing the data and creating notes, (3) identifying/coding themes, (4) interpretation, and (5) generating written and visual representation of the findings (Creswell & Poth, 2018). Thus, for the proposed research study, this would involve transcribing the interviews, reading these transcriptions and making notes in the margins and elsewhere related to emergent ideas, identifying themes, interpreting what these imply, and synthesizing these findings into an in-depth understanding of the essence of flourishing at work among corporate managers. However, this is just a general overview of the phenomenological data analysis process, and because numerous types of phenomenology exist, different and specific procedures are used for data analysis depending on the model that is followed. For the purpose of this discussion and the proposed study, the model of empirical phenomenology (Giorgi, 1997) would be used, and this is consistent with permitted data analysis methods at Capella University (Percy, Kostere, & Kostere, 2015).
Data Analysis Strategy
The data analysis strategy recommended for the proposed study is that of empirical phenomenology developed by Giorgi (1997). This method is thought of as two levels of description, including (a) the raw data collected from interviews and (b) the researcher’s account of the essence of the phenomenon based on analysis and interpretation (Percy et al., 2015). Or, it can be characterized as three broad phases: “(1) the phenomenological reduction, (2) description, and (3) search for essences” (Giorgi, 1997, p. 239). However, to address these two levels (Percy et al., 2015) or three phases (Giorgi, 1997), seven detailed steps are involved. First, the data must be transcribed and organized, and second, the researcher must engage in phenomenological reduction (Percy et al., 2015). This means that the researcher must reflect on and minimize any bias or preconceptions, and bracket pre-existing knowledge of the phenomenon to allow for inductive analysis (i.e., the findings emerge from the data) (Giorgi, 1997). Once these initial preparatory steps have been taken, the researcher moves through the remaining five stages of data analysis.
The first of these five stages is to read through all the interviews in their entirety to achieve a holistic impression of the data. Next, the researcher reads through the interviews again and identifies psychological “meaning units.” Essentially, in this stage, the researcher is looking for moments where transitions in meaning occur during the participants’ responses. The meaning units are then examined in relation to one another and the holistic sense of the data. Additionally, the units are clarified, and any redundancies are removed. The third stage involves some interpretation from the researcher by reflecting on the meaning units to generate the essence of the participants’ experience and converting these units into psychological language. The fourth stage is to synthesize the converted meaning units into a summary statement that captures each participant’s experience of the phenomenon. In the fifth and final stage, all the statements about each participant’s experience are synthesized to produce a detailed statement that describes the essential lived experience being investigated (Percy et al., 2015). Thus, there are five crucial stages of data analysis and two preparatory steps that comprise Giorgi’s (1997) data analysis strategy of empirical phenomenology.
Evaluation of Data Analysis Strategy
An evaluation of Giorgi’s (1997) empirical data analysis strategy for phenomenology reveals both strengths and limitations. Perceived strengths include the foundational step of phenomenological reduction and the systematic way in which the data are analyzed. Indeed, the use of phenomenological reduction helps to ensure that the data are analyzed inductively. Otherwise, if preconceptions and prior knowledge were included in this process, the analysis could become more deductive in nature (i.e., seeking to confirm or refute what is already known). Additionally, the use of a systematic step-by-step procedure provides a uniform framework that can help researchers develop an audit trail of their analysis (Patton, 2015). Consequently, the inclusion of these aspects—phenomenological reduction and systematic analysis—can contribute to the reliability of a phenomenological study (Leedy & Ormrod, 2019). However, there are also limitations to this data analysis strategy. Unlike the data analysis methods used by Moustakas or Stevick-Colaizzi-Keen (as cited in Percy et al., 2015), Giorgi’s (1997) model does not differentiate between textural and structural descriptions of the experience being studied, nor does it use imaginative variation, which invites the researcher to experiment with meaning units/themes and examine them from multiple angles. Finally, consistent with most qualitative studies, Giorgi’s (1997) data analysis method is subjective. Even when using the standards of phenomenological reduction and a systematic approach, ultimately, each researcher makes his/her own judgments and interpretation of the data (Patton, 2015). Moreover, phenomenological reduction is unlikely to eliminate or decrease a researcher’s implicit bias because, by its very definition, implicit bias is unconscious to an individual (Kassin, Fein, & Markus, 2017). Thus, the data analysis approach used in empirical phenomenology has both strengths and limitations.
In conclusion, data analysis for phenomenology fits with the general approach to analyzing data in any qualitative study (Creswell & Poth, 2018). However, it also has specific and detailed procedures that must be followed, and there are several different types of phenomenology that have their own method of data analysis (Patton, 2015). The proposed study would use empirical phenomenology (Giorgi, 1997), which means that two preliminary steps (i.e., data preparation and phenomenological reduction) along with five stages of analysis must be closely followed (Percy et al., 2015). This systematic approach contributes to the reliability of the study (Leedy & Ormrod, 2019), but it also has some limitations that are consistent with the subjective nature of qualitative research (Patton, 2015), and in comparison to other phenomenological approaches (Percy et al., 2015).
References
Creswell, J. W., & Poth, C. N. (2018). Qualitative inquiry and research design: Choosing among five approaches (4th ed.). Thousand Oaks, CA: Sage.
Giorgi, A. (1997). The theory, practice, and evaluation of the phenomenological method as a qualitative research procedure. Journal of Phenomenological Psychology, 28(2), 235-281.
Kassin, S., Fein, S., & Markus, H. R. (2017). Social psychology (10th ed.). Boston, MA: Cengage.
Leedy, P. D., & Ormrod, J. E. (2019). Practical research: Planning and design (12th ed.). New York, NY: Pearson.
Patton, M. Q. (2015). Qualitative research & evaluation methods (4th ed.). Thousand Oaks, CA: Sage.
Percy, W.H., Kostere, K., & Kostere, S. (2015). Qualitative research approaches in psychology. Retrieved from
http://assets.capella.edu/campus/doctoral-programs/PsychologyQualitativeResearchApproaches
Professor feedback
This is a great response to the questions posed within this discussion, Alex. This method is used to analyze the data for the structure and texture of experience. This isn’t the same as identifying patterns and themes. Two key elements of Giorgi’s method include phenomenological reduction and imaginative variation. These methods are sometimes confused with the identification of patterns and themes, but these steps are not a part of this type of analysis. Within this method the data is broken down into meaning units and examined in an attempt to make sense of what was experienced. It is then put back together in a way that ‘gets at’ the essence of what was experienced. These steps are often misunderstood and sometimes misrepresented in reprinted texts. This is why it is always a good idea to locate and review the primary source that is being referenced so that you can verify what is stated and acquire an in-depth understanding of what is communicated within that source. From what I can tell, you are off to a great start. To advance your knowledge even further and help you build your library, attached is another article that you might find interesting. Thank you for your contribution to this discussion.
Dr. Roberts
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