Evalution checklist
Planning and Preparation
Data Collection
Data Analysis
- Create a spreadsheet or database to store the collected data
- Remove any duplicate or irrelevant data
- Check for any missing or incomplete data and fill in or remove as necessary
- Determine the type of data (e.g. continuous, categorical)
- Calculate descriptive statistics such as mean, median, and standard deviation
- Conduct inferential statistics tests such as t-tests or ANOVA if applicable
- Read through the qualitative data to familiarize yourself with the content
- Identify and label recurring themes or patterns
- Code the data by assigning labels or tags to segments that relate to each theme
- Review the analyzed data to understand the findings
- Compare the findings to the evaluation objectives and identify any connections or discrepancies
- Provide an interpretation of what the data suggests in relation to the objectives
- Look for any unexpected or new themes that emerge from the analysis
- Take note of any patterns or trends that were not initially anticipated
- Document these emerging themes and patterns for further exploration or discussion
Use in Manifestly