Data Collection & Analysis Flashcards
7 cards from real CPE practice questions. Tap to flip, then mark Knew It or Still Learning โ missed cards come back until you master them.
Read the first 7 Data Collection & Analysis flashcards as text
A program evaluator wants to capture participant experiences in depth without constraining responses. Which data collection method is most appropriate?
Answer: Open-ended interview
Open-ended interviews allow participants to express experiences in their own words without predefined constraints.
When analyzing Likert-scale data from a program evaluation survey, which statistical measure is most appropriate for the central tendency?
Answer: Mode or median
Likert-scale data is ordinal, so mode or median is more appropriate than mean for central tendency.
A CPE evaluator conducts focus groups but is concerned about dominant participants skewing results. What technique best mitigates this?
Answer: Using a skilled facilitator with structured turn-taking
A skilled facilitator using structured turn-taking ensures all voices are heard and prevents dominance bias.
In program evaluation, 'triangulation' of data primarily serves to:
Answer: Increase validity by using multiple data sources
Triangulation uses multiple sources, methods, or analysts to cross-verify findings and strengthen validity.
A program shows statistically significant improvement in test scores. What additional consideration is critical before concluding the program caused the improvement?
Answer: Ruling out alternative explanations through design
Statistical significance alone does not establish causation; rival explanations must be ruled out through evaluation design.
Which type of validity refers to whether a data collection instrument measures what it is intended to measure?
Answer: Construct validity
Construct validity assesses whether an instrument actually measures the theoretical construct it is designed to measure.
An evaluator uses existing program records rather than collecting new data. This approach is called:
Answer: Secondary data analysis
Secondary data analysis involves examining pre-existing data collected for another purpose rather than gathering new data.