The two main paths
Analysis is often broken into two types - analysis of qualitative data (not numbers) or quantitative data (numbers).
Under these two subheadings, there are many different ways to approach the actual analysis. The strongest approaches combine both, especially in place-based WP. Numbers tell us what happened, while stories help explain why it happened and bring community voice into the evaluation.
Data type: Numbers, percentages, and counts.
Goal: To test theories and measure facts.
Common methods: Surveys with rating scales, tests, and math models.
Main question: How much, how many, or how often?
Examples:
Total participant numbers
Numbers of schools and organisations engaged
Participant groups represented
Repeat participation
Did confidence, awareness and aspiration increase?
In practice:
Analysis involves taking the raw data you have collected, and turning it into a story.
For example:
Attendance data: Of 200 participants across five schools, 145 of those students participated came from just four schools on the one side of town.
Pre and post data: Average confidence before the workshop was rated 3.65 / 5, while the average confidence after was rated 4.1 / 5, showing an increase.
Ask yourself:
What patterns can we see?
Did scores increase or decrease?
Were outcomes different for different groups?
What do the numbers tell us?
Data type: Words, sentences, videos, and audio.
Goal: To explore ideas, meanings, and reasons.
Common methods: Interviews, focus groups, and open-ended text.
Main question: Why or how did it happen?
Examples:
Notes from observers (facilitators, teachers, etc)
Comments from a survey
Interview transcripts
Focus group transcripts
Work samples from students
In practice:
Analysis involves taking the raw data you have collected, and turning it into a story.
For example:
Confidence: 10 out of 12 participants surveyed noted an increase in confidence due to the program - "Until this, I didn’t realise university was an option for me.”
Broadened horizons: In interviews, educators consistently spoke of broadened horizons as a strong outcome.
Ask yourself:
What themes appear repeatedly?
What surprised us?
What did participants value most?
What examples illustrate the impact best?
Choosing how to analyse
Grouping interview responses by theme, calculating the average of a response, or matching pre and post responses to measure change, all require a specific approach.
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