Case Study Analysis - Analyzing Qualitative Data

How does one analyze real qualitative data from the case study?

Quantitative data was reviewed first, so that the process of collecting data that comes in number-formats could be shown, then added to the tables, and through the process of cross-tabulation, analyzed.

Next, raw words or sentences need to be collected and made sense of as another type of data, through sorting according to similarity.

Example of Qualitative Data Collected:

The following is qualitative data that was collected through a survey of the teachers of the after-school program. Notice that some of the data is missing:

1) Although it was challenging to work out a consistent system of discipline and consequences, I do feel that bending the rules for certain children (names deleted to protect the privacy of the students), definitely benefitted those students (Futures teacher).

2) The homework help can be a bit more structured. The kids just sit there and talk because they claim they have no work. Maybe work should be provided (Hip hop dance instructor).

3) The biggest challenges I faced in Futures were inconsistent attendance and behavior problems (Futures teacher).

4) Student commitment and participation could improve. I think this has to deal a lot with students showing/gaining respect for artform, teachers, each other and themselves (String teacher).

5) I mentioned screening earlier and I’m going to have to mention it again (Teacher).

6) I abandoned a more ambitious curriculum when I realized that many of the students were just in the program to pass the time and were not fully devoted to the art that I was teaching them. It may have been their age as well, that contributed to that sense. SA (Smart Arts) needs to feel more like an arts program, not an after-school holding tank (Recording Studio teacher).

7) I liked this program (Teacher).

8) Blank

9) Good program offerings and staff, good staff and student relations (Teacher).

10) Basically I feel that the staff was welcoming, supportive and stimulating but that we did not succeed in creating a safe space where the students felt comfortable to open up and explore their interests (Dance teacher).

11) The long classes allowed me to cover a lot of material (Dance teacher).

12) Rewards and consequences were inconsistent (Actor).

13) If there was some kind of screening in place that ensured that the kids participating in the program were doing it for the right reasons (and not, for example, just because their parents needed babysitters), we could focus on art and less on the discipline (teaching job unmarked).

14) The homework component was a minor disaster. There was no way to force kids to do their homework, and limitless energy was required to try, so most teacher just tried to quarantine problem kids from those who worked, with limited success (Tutor/Coach).

15) The inconsistent attendance, or arriving to find student fighting (verbally and sometimes physically) or running through the halls or outside the building skipping were negatives (Dance teacher).

16) Again, we only need to be taking on kids who are serious about the arts (Recording Studio teacher).

17) Blank

18) A large amount of time spent on behavior issues and disruptions (Teacher).

19) Blank

20) This program is a great idea and I am committed to seeing it flourish (Actor).

21) We had a great discussion about creating rewards and consequences (Tutor/Coach).

22) The courses I taught, after a rocky start, seemed successful (Tutor/Coach).

23) Good field-trip opportunities (Teacher).

24) Good community showcase performances (Teacher).

Analyze by Building Categories

How can one build qualitative categories from this participation data?

One can look for similarities.

Take the raw data from above and analyze it according to similarity of statements that could create categories. For example, the first analytic sort could be all the comments that can be sorted for the category, “teacher praise of the program:”

Teacher Praise for the Program

  • I liked this program (Teacher).
  • Good program offerings and staff, good staff and student relations (Teacher).
  • The long classes allowed me to cover a lot of material (Dance Teacher).
  • This program is a great idea and I am committed to seeing it flourish (Actor).
  • The courses I taught, after a rocky start, seemed successful (Tutor/Coach).
  • Good field-trip opportunities (Teacher).
  • Good community showcase performances (Teacher).
Consequences
  • Basically I feel that the staff was welcoming, supportive and stimulating but that we did not succeed in creating a safe space where the students felt comfortable to open up and explore their interests (Dance Teacher).
  • Rewards and consequences were inconsistent (Actor).
  • We had a great discussion about creating rewards and consequences (Tutor/Coach).
Discipline
  • Although it was challenging to work out a consistent system of discipline and consequences, I do feel that bending the rules for certain children (names deleted to protect the privacy of the students), definitely benefitted those students (Futures teacher).
Screening
  • If there was some kind of screening in place that ensured that the kids participating in the program were doing it for the right reasons (and not, for example, just because they’re parents needed babysitters), we could focus on art and less on the discipline (teaching job unmarked).

Breaking It Down Further

This category of “Teacher Praise for the Program” could be further broken down by coding the data. This involves analyzing each statement from the teachers, and making a table of similarities, such as by type of praise and by staff position. Look at the table below:

Teacher Praise for the Program—Cross Tabulation—Table 3

Staff Position

Types of Praise for the Program

 

General

Specific

Complex

Teachers

I liked this program (Teacher).

Good community showcase performances (Teacher).

Good field-trip opportunities (Teacher).

 

Good program offerings and staff, good staff and student relations (Teacher).

Others (Actors, Dance Teacher, Tutor/Coach)

This program is a great idea and I am committed to seeing it flourish (Actor).

 

The long classes allowed me to cover a lot of material (Dance Teacher).

 

The courses I taught, after a rocky start, seemed successful (Tutor/coach).

 

The qualitative statements were coded for the type of praise (general, specific, complex) and from whom the statement was given (teachers vs. others). In coding these, the similarity of the type of comment, and the similarity of who they were, defined their coding.

Coding Qualitative Data Leads to Analysis

Coding is one of the most powerful ways to track qualitative statements because one now knows how to analyze these statements! This is just the beginning of the analytical power that can be harnessed, even for qualitative data, through cross-tabulations.

Findings

Now craft a summary, from the analysis above, into one-sentence statements of findings:

  • The most useful teacher comments tended to be ones that gave specific praise for the program; for example, “Good community showcase performances” (Teacher), “Good field-trip opportunities” (Teacher) and “The long classes allowed me to cover a lot of material” (Dance teacher).

Conclusions

When one is ready to conclude, describe the discoveries found through analysis, in paragraph format:

  • Teachers offered a variety of comments about the program, but one of the most helpful types of comments were specific praise for the program. In the future, we should help direct all teacher comments to be as specific as, “The long classes allowed me to cover a lot of material” (Dance Teacher). 

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