Overview of Qualitative Data Analysis <ul><li>Pape Samb </li></ul><ul><li>Ghanem Al-Maadeed </li></ul><ul><li>PUAD 625 Res...
<ul><li>Gathered through descriptions, responses to open-ended questions, photos, videos, case studies, etc. </li></ul><ul...
<ul><li>Deeper insight into a program’s successes and failures </li></ul><ul><li>Understanding the “why?” behind quantitat...
<ul><li>“ PPOIISED Framework” (PPOIISED = POISED) 1 </li></ul><ul><ul><li>P urposes </li></ul></ul><ul><ul><li>P aradigms ...
<ul><li>Know  purposes  of qualitative data  before  analyzing by reviewing: </li></ul><ul><ul><li>Evaluation type:  Descr...
<ul><li>Paradigms should be thought of as, “…worldviews about reality, knowledge, and methods…” (Wholey, Hatry, & Newcomer...
<ul><li>Choose options for analyzing data based on: purpose, paradigms, time & skill available </li></ul><ul><li>3 key dim...
<ul><li>Interpretations make meaning out of the data in terms of: </li></ul><ul><ul><li>Understanding specific pieces of d...
<ul><li>Iterations </li></ul><ul><ul><li>What iterations should be built into analytical process? </li></ul></ul><ul><li>S...
<ul><li>Ethics </li></ul><ul><ul><li>What ethical issues might arise? </li></ul></ul><ul><ul><li>How should ethical issues...
<ul><li>Questions? </li></ul>Thank You
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  • Overview of Qualitative Data Analysis
  • 1 Joseph S. Wholey, Harry P. Hatry, and Kathryn E. Newcomer, Handbook of Practical Program Evaluation , 3 rd Edition (Jossey Bass Publishers, 2010), 430.
  • 2 Wholey, Hatry, Newcomer, 431-434
  • 3 Wholey, Hatry, Newcomer, 434-435
  • 4 Wholey, et al, 435-437
  • 5 Wholey, et al, 437-438
  • 6 Wholey, et al, 430
  • 7 Wholey, et al, 430
  • Ghanem and pape's presentation

    1. 1. Overview of Qualitative Data Analysis <ul><li>Pape Samb </li></ul><ul><li>Ghanem Al-Maadeed </li></ul><ul><li>PUAD 625 Research and Evaluation </li></ul><ul><li>(Program Evaluation) </li></ul><ul><li>Dr. Nancy Kingsbury </li></ul>
    2. 2. <ul><li>Gathered through descriptions, responses to open-ended questions, photos, videos, case studies, etc. </li></ul><ul><li>Observed vs. measured (not based on numerical measurements like quantitative data) </li></ul><ul><li>Focused on quality vs. quantity </li></ul><ul><li>QUALIT(Y)ative vs. QUANTIT(Y)ative </li></ul>Qualitative Data
    3. 3. <ul><li>Deeper insight into a program’s successes and failures </li></ul><ul><li>Understanding the “why?” behind quantitative data </li></ul><ul><li>Evaluated properly + combined with quantitative data = increased effectiveness of program evaluation </li></ul>Uses of Qualitative Data
    4. 4. <ul><li>“ PPOIISED Framework” (PPOIISED = POISED) 1 </li></ul><ul><ul><li>P urposes </li></ul></ul><ul><ul><li>P aradigms </li></ul></ul><ul><ul><li>O ptions </li></ul></ul><ul><ul><li>I nterpretations </li></ul></ul><ul><ul><li>I terations </li></ul></ul><ul><ul><li>S tandards </li></ul></ul><ul><ul><li>E thics </li></ul></ul><ul><ul><li>D isplaying </li></ul></ul>Evaluating Qualitative Data
    5. 5. <ul><li>Know purposes of qualitative data before analyzing by reviewing: </li></ul><ul><ul><li>Evaluation type: Describe processes, performance monitoring, impact evaluation, etc. </li></ul></ul><ul><ul><li>Type(s) of questions to be answered: Descriptive, causal, value, action? </li></ul></ul><ul><ul><li>Users of analysis & how they want information presented: Can affect format, presentation, level of detail </li></ul></ul>PPOIISED Framework: Purposes 2
    6. 6. <ul><li>Paradigms should be thought of as, “…worldviews about reality, knowledge, and methods…” (Wholey, Hatry, & Newcomer, 2010, p.434). </li></ul><ul><ul><li>Potential issues caused by paradigms : Explain possible contradictions/differing meanings in evaluation due to paradigms </li></ul></ul>PPOIISED Framework: Paradigms 3
    7. 7. <ul><li>Choose options for analyzing data based on: purpose, paradigms, time & skill available </li></ul><ul><li>3 key dimensions of options: </li></ul><ul><ul><li>Focus </li></ul></ul><ul><ul><li>Who performs analysis </li></ul></ul><ul><ul><li>Reporting </li></ul></ul>PPOIISED Framework: Options 4
    8. 8. <ul><li>Interpretations make meaning out of the data in terms of: </li></ul><ul><ul><li>Understanding specific pieces of data </li></ul></ul><ul><ul><li>Categorizing data </li></ul></ul><ul><ul><li>Identifying overall patterns in data </li></ul></ul><ul><li>3 ways to categorize data: </li></ul><ul><ul><li>Attribute coding </li></ul></ul><ul><ul><li>Descriptive coding </li></ul></ul><ul><ul><li>Pattern coding </li></ul></ul>PPOIISED Framework: Interpretations 5
    9. 9. <ul><li>Iterations </li></ul><ul><ul><li>What iterations should be built into analytical process? </li></ul></ul><ul><li>Standards </li></ul><ul><ul><li>What standards to use as guides? </li></ul></ul><ul><ul><li>What strategies to ensure standards for quality analysis? </li></ul></ul>PPOIISED Framework: Iterations & Standards 6
    10. 10. <ul><li>Ethics </li></ul><ul><ul><li>What ethical issues might arise? </li></ul></ul><ul><ul><li>How should ethical issues be handled? </li></ul></ul><ul><li>Displaying </li></ul><ul><ul><li>Best ways to display data during analysis? </li></ul></ul><ul><ul><li>Best ways to display data for reporting? </li></ul></ul>PPOIISED Framework: Ethics & Displaying 7
    11. 11. <ul><li>Questions? </li></ul>Thank You

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