Educational Research: Causal-Comparative Studies

1. Educational Research: Causal-Comparative Studies NasihJaber Ali 25-10-2011

2. The basic steps of research... Scientific and disciplined inquiry is an orderly process, involving: Recognition and identification of a topic to be studied (“problem”) Description and execution of procedures to collection information (“method”) Objective data analysis Statement of findings (“results”)

3. Research methods... Quantitative… Collects and analyzes numerical data obtained from formal instruments

4. Quantitative methods... • Descriptive research (“survey research”) • Correlational research • Causal-comparative research (“ex post facto research”) • Experimental research

5. causal-comparative research (“ex post facto research”) At least two different groups are compared on a dependent variable or measure of performance (called the “effect”) because the independent variable (called the “cause”) has already occurred or cannot be manipulated

6. Research variables... Independent… An activity of characteristic believed to make a difference with respect to some behavior experimental variable, cause, treatment

7. dependent variable… The change or difference occurring as a result of the independent variable criterion variable, effect, outcome, posttest

8. A causal-comparative study… A study in which the researcher attempts to determine the cause, or reason, for pre-existing differences in groups of individuals…. called an “ex post facto” study because both the effect and the alleged cause have already occurred and must be studied in retrospect

9. Differences in causal-comparison and correlational studies… • Causal-comparative studies… * attempt to identify cause-effect relationships • Correlational studies… * attempt to identify relationships

10. Causal-comparative studies… * involve two (or more) groups and one independent variable • Correlational studies… * typically involve two (or more) variables and one group

11. Causal-comparative studies… * involve making comparisons • Correlational studies… * involve establishing relationships

12. Differences in causal-comparison and experimental studies… • Causal-comparative studies… * individuals are not randomly selected but selected because they belong to groups • Experimental studies… * individuals are randomly selected and assigned to two (or more) groups

13. Causal-comparative studies… * the researcher cannot manipulate the independent variable • Experimental studies… * the researcher manipulates the independent variable

14. Causal-comparative studies… * the independent variable has already occurred and cannot be manipulated • Experimental studies… * the researcher manipulates the independent variable to determine its effects

15. Conducting a causal-comparative study… 1. Select the problem 2. Select participants and instrument 3. Design and procedure 4. Data analysis and interpretation

16. 1. select the problem… * The researcher starts with an effect and seeks its causes * The independent variable cannot or should not be manipulated

17. 2. select the participants and instrument * Select samples representative of their respective populations and similar with respect to critical variables other than the independent variable * called “comparison groups”

18. 3.design and procedure… * The performance of the groups is compared using some valid dependent variable measure (“instrument”) * Lack of randomization, manipulation, and control are sources of weakness

19. control * The process by which the researcher attempts to ensure that the findings are as free of researcher bias and error as possible

20. types of control * Random assignment of participants to groups * Pair-wise matching * Comparing homogeneous groups * Comparing homogeneous subgroups * Factorial analysis of variance * Analysis of covariance

21. random assignment of participants to groups * Not possible in causal-comparative studies because the groups already exist and have already received the treatment

22. Pair-wise matching * First: find a participant in the second (third, fourth, etc.) group with the same or similar score on the control (non manipulated) variable as the participant in the first group * Second: if a participant in either group does not have a suitable match, the participant is eliminated from the study

23. comparing homogeneous groups * Control for extraneous variables that are homogeneous with respect to the extraneous variables * Limitation: lowers the number of participants in the study and, of course, limits the generalizability of the findings

24. comparing homogeneous subgroups * Form subgroups within each group that represent all levels of the control (non manipulated) variable * Controls for the variable and also permits the researcher to determine whether the independent variable affects the dependent variable differently at different levels of the control (non manipulated) variable

25. factorial analysis of variance * Building the control (non manipulated) variable into the research design * Then use factorial analysis of variance to analyze the results to determine the effect of the independent and control (non manipulated) variable on the dependent variable, both separately and in combination

26. Factorial analysis of variance Allows the researcher to determine if there is an interaction between the independent variable and the dependent variable such that the independent variable operates differently at different levels of the independent variable building it into the research design

27. analysis of covariance (“ANCOVA”) * Statistically adjusts initial group differences on a dependent variable for initial differences on some other variable related to performance on the dependent variable * Removes initial differences so that the results can be fairly compared as if the two groups started equally

28. 4.Data analysis and interpretation * Researcher uses a variety of descriptive and inferential statistics: Mean Standarddeviation t-test Analysis of variance

29. mean * The descriptive statistic indicating the average performance of an individual or group on a measure of some variable

30. standard deviation * The descriptive statistic indicating the spread of a set of scores around the mean

31. t-test * The inferential statistic indicating whether the means of two groups are significantly different from one another

32. analysis of variance (“ANOVA”) * The inferential statistic indicating the presence of a significant difference among the means of three or more groups

33. References • Jack R. Franenkel, Norman E. Wallen. How to design and evaluate research in education • Louis Cohen, Lawrence Manion. Research methods in education