• Most evaluations include qualitative data
• Gathered through descriptions, responses to open
ended questions, transcripts, notes, questionnaires,
photos, videos, e-mails, program documentation, etc.
• Provides deeper insight into how programs, policies work
or fail to work
• Analysis occurs throughout the
data collection process
PPOIISED Framework for Analysis of
Qualitative Data (a series of questions)
(See page 430 of your text book)
Know purposes of qualitative data before analyzing
• Evaluation type: Describe processes, performance
monitoring, impact evaluation, etc.
• Type(s) of questions to be answered: Descriptive,
causal, value, action?
• Users of analysis & how they want information
presented: Can affect format, presentation, level of
detail PPOIISED Framework.
• Paradigms should be thought of as, “…worldviews about
reality, knowledge, and methods…”
• Potential issues caused by paradigms: Explain possible
contradictions/ differing meanings in evaluation due to
(See page 434 of your text book)
• Choose options for analyzing data based on:
purpose, paradigms, time & skill available
• 3 key dimensions of options:
– Who performs analysis
• Interpretations make meaning out of the data in
– Understanding specific pieces of data
– Categorizing data
– Identifying overall patterns in data
• 3 ways to categorize data:
– Attribute coding (demographic if needed)
– Descriptive coding (attach tags)
– Pattern coding (relationship and patterns)
Keep Track of Data Iterations
– What iterations should be built into
– What standards to use as guides?
– What strategies to ensure standards
for quality analysis?
• What ethical issues might arise?
• How should ethical issues be handled?
• Best ways to display data during analysis?
• Best ways to display data for reporting?
• Useful data displays
– Charts, tables, figures,