THE STEPS THAT INVOLVE DATA ANALYSIS

1. Before we go into initial data analysis, lets review the general steps in most qualitative research: ******GENERAL STEPS IN QUALITATIVE RESEARCH****** 1. Observe events/ask questions with open-ended answers, 2. Record/log what is said and/or done 3. Interpret (personal reactions, write emergent speculations or hypotheses, monitor methods) OR Look for Regularities (analyze for patterns) 4. Return to observe, or ask more questions of people 5. [recurring cycles of 2-4--iteration] 6. Formal theorizing [emerges out of speculations and hypotheses] 7. Draw conclusions THE STEPS THAT INVOLVE DATA ANALYSIS

2. DATA ANALYSIS USUALLY MEANS 1.REVIEWING 2. SORTING, 3. CLASSIFYING OR CATEGORIZING, 4. ANALYZING AND THEN 5. SYNTHESIZING YOUR DATA IN SOME SYSTEMATIC WAY THAT LEADS TO CONCLUSIONS ABOUT THE RESEARCH QUESTIONS.However, this process of reviewing, sorting, classifying, analyzing and synthesizing is not done haphazardly!!!!you must identify – ahead of time how will you go about this.first data must be ‘transcribed’. This means it must be put in a form that is ‘reviewable’. Audiotapes are often used in focus groups. However, after the group someone – usually you, although it is better to pay someone for this tedious task – must put them in written form.

3. 1. REVIEWING • make sure that the data is separated, based on the methods (or sources) that you used. For example, all of my observation ‘field notes’ are kept together in one pile, my in-depth interviews with clients in another, and my transcription of my video/audio tape of staff ‘focus groups’ in a third pile. • then all data, from all sources and all methods are reviewed by the evaluator or some others hired by the evaluator. During this first reading, you are not looking for answers to the research questions. All you are doing is ‘sensitizing yourself to the data’. This is known as ‘immersion’. THIS PROCESS OF IMMERSING ONESELF IN THE DATA CAN TAKES WEEKS! • This is a good time to take personal notes!!!! As you are reviewing the data (step 6), note anything- ANYTHING- that jumps out at you or that you think is interesting.

4. 2. SORT, AND 3. CLASSIFY USUALLY MEANS THESE Phases of Initial Analysis: 1. Code Various Units--can have multiple codes for a unit (codes are not mutually exclusive, at least at first, but work towards exhaustive coding, at least eventually). Theory--preexisting or emergent--influences coding, but can push self to code broadly, thus less bound by theory. May need to code same data several times--computers definitely help. 2. Develop Categories, Subcategories, Superordinate Categories. These require definitions. Categories and definitions will probably need to be revised many times as you continue analysis. Keep track of the revisions and reasons for revisions of categories and definitions in theoretical notes (revisions occur because data indicates that previous definitions were not sufficient). 3. Give Examples of Categories in your theoretical notes, indexed specifically to pages, line numbers, etc. of field notes/video data/other sources of data. Include exemplars--best examples that represent the core of the category. Also include outliers--poor examples, but nevertheless examples of the category, as they define the limits of the category. 4. Linkages Between Categories need to be specified, and also note the kinds of linkages involved. Consider these kinds of linkages, among others:

5. 4. ANALYZING-AFTER I SET UP MY CATEGORIES AND HAVE SORTED THE DATA • Set the data aside. Go back to it. Later. Review again, according to piles (step 5). Except this time you are looking for specific answers to the research questions. Here is where you begin to take ‘theory notes’. • In reviewing the data this time (step 8), YOU ARE LOOKING FOR COMMONALITIES OR THEMES WITHIN THE PILES. TAKE NOTES. In analyzing and note –taking, you are looking for the strength of an assertion. For example, if your research question is “how relevant are the activities in “X” program?”, you might find that most ‘staff’ see the activities as ‘highly relevant’. This gives strength and credibility to the notion that the activities are highly relevant. Whereas, if only half of the staff see the activities as relevant, this would indicate that there is ‘mixed support among staff’ for the relevancy of activities. Additionally, for example, you might note that staff responses contain subtle criticisms of each other! That would tell you, perhaps, that there are some conflicts among staff that may be interpersonal or around commitment to how the program is being implemented. You would do this for each method or data source.

6. 5. SYNTHESIZING After you have done this for each data source, then begin to compare your notes for each source. Look for commonalities (strength of support for the research question-one way or another) or disagreements (lack of strength of support). For example, you might find that most staff see the activities as highly relevant and most clients see them as highly irrelevant. Then you know there is a strong disagreement between clients and staff about the activities. HOWEVER, lets say that in your observations, you note that the activities – based on your lit review and observations – really do not fit the program objectives and that staff seem to be doing activities that they like or are convenient for them, rather than meeting the needs of the client. Then you might conclude that the activities are not meeting the needs of the clients and program objectives. ON THE OTHER HAND, lets say your observation (field notes) indicate that the activities are relevant and the staff is really trying, but the clients seem disinterested, you might conclude that EITHER THE CLIENTS DO NOT UNDERSTAND HOW THE ACTIVITIES FIT WITH THE PROGRAM OR THAT THE CLIENTS ARE NOT BEING ENGAGED ON THEIR LEVEL. SEE HOW THIS WORKS? THEN YOU BEGIN DRAWING AND WRITING YOUR CONCLUSIONS.