My Freshman (Ch. 1-3)

In Chapter 1-3, Cathy Small (1997) successful presents specific reasons for writing this book. As a professor, Cathy Small researched in detail student’s culture and life from interviews with students and observation by registering as a freshman in college to take courses and participate in dormitory and on-campus activities. She employed ethnographic research method. Unfortunately, Cathy Small’s research, as detailed and efficacious as it may be, was carried out deceptively in that her identity as a professor was kept secret. This paper attempts to identify a major flaw in this research: research ethics.

I greatly respect the author’s love for students and passion for their education. Frankly, I was deeply moved by the following statement by the author: “I felt that the world I wanted to penetrate would be precluded if I were imply an interested professor “doing research” on students. I decided then to become a student by formally applying to the university, by registering for an taking courses, and by moving into a dorm- hence setting the stage to view undergraduate life as both an observer interviewer and a participants” (p. x).

I felt there was a parallel between the author’s heart and Christ’s incarnation in which He became man to save sinners (Phil. 2:5-11). The decision by the author to lay the generational gap and self-esteem aside to know students and effectively educate them was inspirational.
As worthwhile as its cause is, I could not help but look at the author’s observations and this research with doubtful eyes. Her pseudonym, interviewees, and the contents of the interviews remain undisclosed as “anonymity.” Furthermore, no observation or research models are mentioned (p. 19; pp. 56-57).

In this respect, I would like to raise this question to the author and the readers, “What is the purpose of this research?” Also, I would like to discuss the possible need for ethical boundaries in research.

In spite of worthwhile cause and objective, research devoid of ethics will raise issues of credibility. Research must be objective, clear, and ethical.

The publication of this book must have brought joy to those who discovered new findings through the author’s research as well as disappointment and hurt to those who newly discovered the author’s identity. Research lacking in ethics cannot impart credibility. Therefore, researchers must take into consideration ethical standards in undertaking research.

Qualitative Research Design (Creswell, 2007- Ch. 8)

 

In Chapter 8, Creswell (2007) successfully presented how to deal with data analysis and representation. Creswell explained effective three analysis strategies in 3 steps (p. 148):

Step #1: Data analysis in qualitative research consists of preparing and organization the data

Step #2: Reducing the data into themes through a process of coding and condensing the codes

Step #3: representing the data in figures, tables, or a discussion.

Also, explaining in detail developing codes or categories, and coding process required in qualitative research, Creswell mentions several cautionary issues arising from such courses of actions.

Unfortunately, Creswell’s “interpreting the data (interpretation)” exhibited limitation in which it must be contrasted with a social science construct or idea through the scope of a social science construct or idea or a combination of personal views. Concerning this weakness, the author insists that data analysis may appear tentative, inconclusive, and questionable to postmodern and interpretive researchers. This observation is reminiscent of my memo on Creswell’s comments written on Jan 29^th of 2009:

“The basic concept is that knowledge claims must be set within the conditions of the world today and in the multiple perspectives of class, race, gender, and other group affiliations” (Croswell 207, p. 25), I had asked the following questions: Then, can the world provide “The Truth” that we can completely believe and accept? This is vague (January 29, 09).

 

Today, people possess various and different perspectives. For this reason, interpretation must take into consideration making sense of the data, the “lesson learned” as the author asserts. However, in qualitative research, the points of emphasis brought by postmodern and interpretive researchers are too broad thus perpetuating repetitive questions and ambiguous interpretations rather than seeking plausible interpretation and effective method through research. The purpose of research, I believe, is to suggest credible truth attained through research of discovered or undiscovered facts, theories, and phenomena within the vernacular of research methodology. However, the perspectives and interpretations of postmodern and interpretive researchers are prone to cause errors of creating utter confusion instead of embracing diverse perspectives. Perhaps, what postmodern and interpretive researchers need is dependable truth, not different perspectives.

Feb 16, 09 (Summary of Interpreting the Data- Creswell)

Crewell (2007) shows us another methodology that how we can interpret the data in qualitative research in this book.

 

 

Researchers engage in interpreting the data when they conduct qualitative research: (p. 154).

 

-       Interpretation involves making sense of the data, the “lessons learned,” as described by Lincoln and Guba (1985). Several forms exist, such as interpretation based on hunches, insights, and intuition.

-       Interpretation might be within a social science construct or idea or a combination of personal views as contrasted with a social science construct or idea.

-       In the process of interpretation, researchers step back and form larger meanings of what is going on in the situations or sites.

-       For postmodern and interpretive researchers, these interpretations are seen as tentative, inconclusive, and questions.

 

 

In the final phase of the spiral, Researchers present the data, a packaging of what was found in text, tabular, or figure form: (p. 154)

 

[EXAMPLE]

Creating a visual image of the information, a researcher may present a comparison table or a matrix- for example, a 2 x 2 table that compares men and women in terms of one of the themes or categories in the study.

 

 

Hypotheses or propositions that specify (상술, 명기) the relationship among categories of information also represent information (p. 154).

 

[EXAMPLE]

In grounded theory, investigators advance propositions that interrelate the causes of a phenomenon with its context and strategies.

 

-       Authors present metaphors to analyze the data, literary devices in which something borrowed from one domain applies to another. Qualitative writers may compose entire studies shaped by analyses of metaphors.

-        

 

 

[중요: SUMMARY of Data analysis and Representation, by Research Approaches]

 

Phenomenology

·      Step #1: Create and organize files for data

·      Step #2: Read through text, make margin notes, form initial codes

·      Step #3: Describe personal experiences through epoche

·      Step #4: Describe the essence of the phenomenon

·      Step #5: Develop significant statements

·      Step #6: Group statements into meaning units

·      Step #7: Develop a textural description, “What happened”

·      Step #8: Develop a structural description, “How” the phenomenon was experienced

·      Step #9: Develop the “essence”

·      Step #10: Present narration of the “essence” of the experience; in tables, figures, or discussion

 

 

Case Study

·      Step #1: Create and organize files for data

·      Step #2: Read through text, make margin notes, form initial codes

·      Step #3: Describe the case and its context

·      Step #4: Use categorical aggregation to establish themes or patterns

·      Step #5: Use direct interpretation

·      Step #6: Develop naturalistic generalizations

·      Step #7: Present in=depth picture of the case (or cases) using narrative, tables, and figures

 

 

[중요 Phenomenological & Case Study Analysis and Representation]- (Creswell, 2007, pp. 159-164)

 

Feb. 14-15, 09 (Summary: Data Analysis in QR)-Important!

 Ok, try to summarize what Creswell talks about how to deal with data analysis in qualitative research (Ch. *) in his book. It is complicated but multiple reading may be needed for understanding and practicing in my research. 

1.     Analytic memos:

Creswell (2007)- Ch. 8 (pp, 148)

THREE ANALYSIS STRATEGIES

-       Step #1: Data analysis in qualitative research consists of PREPARING and ORGANIZATION the DATA

-       Step #2: Reducing the data into themes through a process of coding and condensing the codes

-       Step #3: representing the data in figures, tables, or a discussion.

 

Examples of qualitative researchers:

1.     Madison (2005) presents a perspective taken from critical ethnography.

2.     Huberman and Miles (1994) adopt a systematic approach to analysis.

3.     Wolcott (1994b) uses a more traditional approach to research from ethnography and case study analysis.

 

 

Analytic Strategy:

-       Sketching ideas

-       Taking notes

-       Summarizing field notes

-       Working with words

-       Identifying codes

-       Reducing codes to themes

-       Counting frequency of codes

-       Relating categories

-       Relating categories to analytic framework in literature

-       Creating a point of view

-       Displaying the data

 

The processes of data collection, data analysis, and report writing are not distinct steps in the process.

 

Qualitative researchers often “learn by doing” (Dey, 1993, p. 6) data analysis. This leads critics to claim that qualitative research is largely intuitive, soft, and relativistic or that qualitative data analysts fall back on the three “I’s”- “insight, intuition, and impression” (Dey, 1995, p. 78). – p. 150

 

 

Following the organization of the data, continue analysis by getting a sense of the whole database. “… read the transcripts in their entirety several times. Immerse (파묻다, 액체에 집어넣은) yourself in the details, trying to get a sense of the interview as a whole before breaking it into parts.” (p 150)

 

 

Writing memos in the margins of fieldnotes or transcripts or under photographs helps in this initial process of exploring a database. These memos are short phrases, ideas, or key concepts that occur to the reader.

 

 

Developing CODES or Categories (p. 152):

 

Researchers develop a short list of tentative codes (e.g., 12 or so) that match text segments, regardless of the length of the database.

 

 

CODING PROCESS (Develop codes)

 

1.     Description becomes a good place to start in a qualitative study (after reading and managing data), and it plays a central role in ethnographic and case studies (p. 151).

2.     Develop elaborate lists of codes when they review their databases.

* Creswell suggests that I do not develop more than 25-30 categories of information, and I find myself working to reduce and combine them into the 5 or 6 themes that I will use in the end to write my narrative.

 

 

Several Issues in Coding Process (p. 152):

 

1.     Whether qualitative researchers should count codes.

[SUGGESTION: investigators make preliminary counts of data codes and determine how frequently codes appear in the database.]

[REASON: This is because counting conveys a quantitative orientation of magnitude and frequency contrary to qualitative research.]

 

2.     The use of pre-existing or a priori codes that guide my coding process.

[REASON: A continuum of coding strategies that range from “prefigured” categories to “emergent” categories.]

[SUGGESTION: If a “prefigured” coding scheme is used in analysis, I typically encourage the researchers to be open to additional codes emerging during the analysis.]

 

3.     The question so to the origin of the code names or labels

[REASON: Code labels emerge from several sources. They might be in vivo codes, names that are the exact words used by participants.]

[SUGGESTION: I encourage qualitative researchers to look for code segments that can be used to describe information and develop themes.]- e.g.,

 

·      Represent information that researchers expect to find before the study

·      Represent surprising information that researchers did not expect to find

·      Represents information that is conceptually interesting or unusual to researchers (and potentially participants and audiences)

 

 

As a popular form of analysis, classification involves identifying five to seven general themes.

 

[SUGGESTION: Reducing the data to a small, manageable set of themes to write into my final narrative.]- (p. 153)

 

A related topic is the types of information a qualitative researcher codes and develops into themes:

 

[EXAMPLES]

·      The researcher might look for stories (as in narrative research)

·      The researcher might look for individual experiences and the context of those experiences (in phenomenology)

·      The researcher might look for processes, actions, or interactions (in grounded theory)

·      The researcher might look for cultural themes and how the culture-sharing group works that can be described or categorized (in ethnography)

·      The researcher might look for a detailed description of the particular case or cases (in case study research)

 

Types of information to analyze from qualitative data in all approaches: (pp. 153-154).