Category: Paul McAfee

Excel & Word for qualitative data analysis

6/16/2019

I have continued to experiment with the use of MS Excel and Word to analyze qualitative date -- in this case, interview data for my PhD dissertation. The method described by Ose (2016) is amazing, although it has a few disadvantages.

Disadvantages include having online one major code for each interviewee quote. In my spreadsheet, I have an additional column for a secondary code, but I do not include that column when going through Ose's (2016) steps to convert the Excel file for Word. I use the added column as a reference as I work with the Word file during my secondary coding, categorizing, and creation of themes.

If you use her method as described in her paper, you will need to enlarge the Figure 10 and 11 screen shots. The concatenation instructions are complex, but trust what she writes, and pay special attention to the following on page 9:
F1 cell: =CONCATENATE(D1;"(";A1;"_";B1;"_";C1;")")
The "_" underscore symbols represent spaces, not use of the symbol, and in my instance of Excel, the semicolons were commas when I used the Function feature to create this string.

This is what the formula looks like in my file:
=CONCATENATE(D1,"(",A1," ",B1," ",C1,")")

The screen shot below is Ose's (2016) Figure 6 image on page 9. Keep in mind that there are additional "Text" boxes that aren't visible in this image.

Reference
Ose, S. O. (2016). Using Excel and Word to Structure Qualitative Data. Journal of Applied Social Science, 10(2), 147–162. https://doi.org/10.1177/1936724416664948

#dataanalysis #qualitativedata #interviewdata

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Analyzing qualitative data - excel & word (QDA)

6/2/2019

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I have struggled to find the best way to compile and structure my interview data for analysis. The analytic methods will follow the direction provided by Saldaña (2015, pp. 14-15). These methods will include transcription of the recorded interviews, coding the transcribed data, categorizing the data, and developing themes and concepts. See Figure 3 below from Saldaña (2015, p. 14) for a graphic illustration of the process. The written report on the data will follow the recommendations of Saldaña (2015) and Seidman (2013). See the first figure below. This shows the process of developing categories and themes following coding of the interview data.

The challenge is in the process of finding an efficient method to analyze as many as 38 interviews, comprising first and second interviews from 19 participants. For researchers with similar challenges, I am sharing an article by Solveig Ose (2016) that provides a process to convert the MS Word transcripts of the interviews into tables in Excel for coding and analysis. See the second figure below. This is an illustration of the data copied from Word to Excel. This is part of the qualitative data analysis (QDA) process.

Figure 1. A model for moving from data through codes to themes and theories (Saldaña, 2015, p. 14).

Figure 2. Example of transcribed text in Excel (Ose, 2016, p. 5).

Ose, S. O. (2016). Using Excel and Word to Structure Qualitative Data. Journal of Applied Social Science, 10(2), 147–162. https://doi.org/10.1177/1936724416664948

Saldaña, J. (2015). The coding manual for qualitative researchers (Third ed.): Sage.

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Interview Highlights

5/23/2019

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Following are highlight quotes from my experiential learning research interviews.

Instructor
Talking about the comments in student evaluations of the course at the end of a semester:

"I always have a student or two who are like, 'She didn't teach anything. We just discussed things in small groups. Why do I pay to have discussion?'"

I'll add to this list as work through my analysis.

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Writing my Experiential Learning Dissertation

4/22/2019

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The research for my PhD dissertation is almost complete. The analysis starts in one week, along with starting to write. The research subject and questions are:

Exploring definitions and perceived value of experiential learning at an American university in Asia.

1) What definitions of experiential learning are expressed by students, faculty, and administrators?

2) Within a classroom learning context, how do participants describe teaching and learning related to experiential learning? Specifically, how do:

a. students describe their own classroom experiences with experiential learning?

b. instructors describe their experiences with experiential learning?

c. administrators describe their understandings of the ways in which instructors and students experience and engage in experiential learning?

3) What value, if any, do students, faculty, and administrators ascribe to experiential learning?

During this research, which involved interviews of students, instructors, and academic administrators, I was impressed by the insights and thoughtfulness of many of the students. Interview questions included asking about the value of experiential learning, its challenges, and definitions from the students' perspectives. Here is one student's statement of value:

"I think it enables me to ... be more adaptable. Yeah, because it puts me in a situation likes there's no predictability. I have no idea what I'm going to face next. So it keeps me on my toes ... enables me to think fast and be more ... malleable, yeah."

Here is another quote from a student who is defining experiential learning:

"I think experiential learning is ... a more active form of learning ... it doesn’t involve just like the lectures and the spoon-feeding that most Asian education systems are like ... Asian education system is ... it’s very common to have the lecture style of teaching in Asian schools, but I feel that the program [I am in now] is more of interactive ... We did class group projects and discussions in class. So it’s more about like an active engagement in the content that we’re learning. It’s not simply just memorizing from the textbooks. So I feel that yeah, it’s like we get to interact first hand with practicalities of the content that we’re learning."

Several students identified social loafers among the challenges of experiential learning. For example:

"I guess one of those would be social loafer where people do not put in as much effort as you do, and perhaps also the level of motivation, because maybe some people are not as motivated to accomplish this task."

There is so much more. For the next two months, I will be analyzing the interview data to code and categorize the interviews, and then to identify themes. Listening to the students during the interviews was a treat. I look forward to revisiting the interview transcripts and the recordings to conduct the analysis. More updates will follow.

Image reference
Bergsteiner, H., et al. (2010). "Kolb's experiential learning model: critique from a modelling perspective." Studies in Continuing Education 32(1): 29-46.

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Excel & Word for qualitative data analysis

Analyzing qualitative data - excel & word (QDA)

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