A Short Guide to Action Research 4 th Edition

1. A Short Guide to Action Research4th Edition Andrew P. Johnson, Ph.D. Minnesota State University, Mankato www.OPDT-Johnson.com

2. Chapter 8: Quantitative Design in Action Research

3. Quantitative research is based on the collection and analysis of numerical data • Three quantitative research designs can fit within the action research paradigm: 1. correlational research 2. causal–comparative research 3. quasi-experimental research

4. CORRELATIONAL RESEARCH • Seeks to determine whether and to what degree a statistical relationship exists between two or more variables • Used to describe an existing condition or something that has happened in the past

5. Correlation Coefficient • Correlation coefficient = the degree or strength of a particular correlation • Positive correlation = when one variable increases, the other one also increases • Negative correlation = when one variable increases, the other one decreases • Correlation coefficient of 1.00 = a perfect one-to-one positive correlation • Correlation coefficient of .0 = absolutely no correlation between two variables • Correlation coefficient of –1.00 = a perfect negative correlation

6. Misusing Correlational Research • Correlation does not indicate causation • Just because two variables are related, we cannot say that one causes the other Negative Correlation • Increase in one variable causes a decrease in another

7. Making Predictions • Correlation coefficient identified by the symbol r • When r = 0 to .35, the relationship between the two variables is nonexistent or low • When r = .35 to .65, there is a slight relationship. • When r = .65 to .85, there is a strong relationship

8. CAUSAL-COMPARATIVE RESEARCH • Used to find reason for existing differences between two or more groups • Used when random assignment of participants for groups cannot be met • Like correlational research, used to describe an existing situation • compares groups to find a cause for differences in measures or scores

9. QUASI-EXPERIMENTAL RESEARCH • Like true experiment; but no random assignment of subjects to groups • random selection is not possiblein most schools and classrooms • Pre-tests and matching used to ensure comparison groups are relatively similar

10. Five Quasi-Experimental Designs • Exp = experimental group • Cnt = control group • O = observation or measure • T = treatment

11. Pretest-Posttest Design

12. Pretest-Posttest Group Design

13. Time Series Design

14. Time Series Group Design

15. Equivalent Time-Sample Design

16. THE FUNCTION OF STATISTICS • Descriptive statistics = statistical analyses used to describe an existing set of data • Measures of central tendency describes a set of data with a single number a. mode - score that is attained most frequently b. median - 50% of the scores are above and 50% are below c. mean - the arithmetic average

17. Frequency Distribution = all the scores that were attained and how many people attained each score

18. Line graph for frequency distribution

19. Measures of variability = the spread of scores or how close the scores cluster around the mean Range = the difference between the highest and lowest score Variance = the amount of spread among the test scores standard deviation = how tightly the scores are clustered around the mean in a set of data

20. Scores with a Small Variance Scores with a Large Variance

22. Small Standard Deviation: Closely Distributed Scores

23. Large Standard Deviation: Widely Distributed Scores

24. INFERENTIAL STATISTICS • Inferential statistics = statistical analyses used to determine how likely a given outcome is for an entire population based on a sample size • make inferences to larger populations by collecting data on a small sample size • Statistical significance = that difference between groups was not caused by chance or sampling error