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Educational Research

Educational Research . Chapter 8 Causal-Comparative Research Gay, Mills, and Airasian. Topics Discussed in this Chapter. The purpose of causal-comparative research Comparisons with other designs Design issues and procedures Control Data analysis and interpretation. Purpose.

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Educational Research

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  1. Educational Research Chapter 8 Causal-Comparative Research Gay, Mills, and Airasian

  2. Topics Discussed in this Chapter • The purpose of causal-comparative research • Comparisons with other designs • Design issues and procedures • Control • Data analysis and interpretation

  3. Purpose • Attempts to determine the cause for preexisting differences in groups of individuals • Groups already differ on some variable and the researcher attempts to identify a major factor that led to these differences • Students participating in extracurricular activities have higher grade point averages than students who do not participate • Children who attend preschool are more adjusted socially in the first grade than those children who do not attend preschool Objective 1.1

  4. Purpose • The alleged cause and effect have already occurred • Orientations • Retrospective - starts with an effect and seeks possible causes • Prospective - starts with a cause and investigates its effect on some variable Objectives 1.1 & 1.2

  5. Similarities to Correlational Research • Both lack manipulation • Both require caution in interpreting results • Both can support subsequent experimental research Objective 2.1

  6. Correlational No attempt to understand cause and effect Two variables, one is a predictor and one a criterion One group Involves relationships Causal comparative Attempt to understand cause and effect At least one independent variable (i.e., purported cause) and one dependent variable (i.e., purported effect) Two or more groups Involves comparisons Differences from Correlational Research Objective 2.2

  7. Experimental Causal group comparisons Individuals randomly assigned to treatment groups Independent variable manipulated by the researcher Causal comparative Group comparisons – but not causal Individuals already in groups before research begins Independent variable not manipulated Cannot Should not Is not Comparison to Experimental Research Objectives 3.1 & 3.2

  8. Examples of Non-Manipulated Variables • Age • Sex • Ethnicity • Learning style • Socioeconomic status • Parental educational level • Family environment • Preschool attendance • Type of school Objective 3.3

  9. The Value of Causal-Comparative Research • Permits the investigation of variables that cannot or should not be manipulated • Can inform decisions • Results can lead to experimental studies that establish causality • Very cost effective to conduct Objective 3.4

  10. Design • The basic design is an experimental-control group posttest only • (E) X O (C) O • An alternative design is a comparison group posttest only • (E) X1 O (C) X2 O Objective 4.1

  11. Procedures • Select two groups that differ on some independent variable • One group possesses some characteristic that the other does not • Each group possesses the characteristic but in differing amounts • The independent variable must be clearly operationally defined Objective 4.3

  12. Procedures • Randomly sample subjects from each of the two groups • Collect background information on subjects to help determine the equality of the groups • Compare groups on the dependent variable Objective 4.3

  13. Control of Extraneous Variables • Lack of randomization, manipulation, and control are all weaknesses of causal comparative designs • Three ways to control extraneous variables • Matching – pair-wise matching of subjects on a variable likely to influence performance • Two subjects – one from each group - with similar scores on the matching variable are matched and included in the sample • Limited by the potential lack of matches Objectives 5.1, 5.2, & 5.3

  14. Control of Extraneous Variables • Three ways to control (cont.) • Comparing homogeneous groups – create groups that are similar on an important extraneous variable • Limited by a potentially restricted range of scores on the extraneous variable • An alternative is to form subgroups within each group to accommodate a larger range of scores on the extraneous variable • The use of factorial analysis of variance (ANOVA) to analyze the interaction between the independent variable groups and the extraneous variable subgroups Objectives 5.2, 5.4, 5.5, & 5.6

  15. Control of Extraneous Variables • Three ways to control (cont.) • Analysis of covariance (ANCOVA) • Statistically adjusting the scores on the dependent variable for differences on an extraneous variable of importance • Limited by the need to strictly adhere to the statistical assumptions of ANCOVA Objectives 5.2 & 5.7

  16. Descriptive statistics Central tendency Mean Median Mode Variation Standard deviation Inferential statistics t test ANOVA ANCOVA Chi square Data Analysis Objective 5.8 & 5.9

  17. Interpretation of Data • Difficulty establishing cause and effect requires caution in interpreting results • No manipulation of the independent variable has occurred • No randomization • Minimal control of extraneous variables Objective 6.1

  18. Interpretation of Data • Causality and alternative explanations • Order of causation • Reversed causality – difficulty establishing which variable is the cause and which is the effect • Does attitude affect achievement or achievement affect attitude? • Order of occurrence can often be determined logically • Gender can affect social development in young children but social development cannot affect gender • Attending preschool can affect kindergarten performance but kindergarten performance cannot affect preschool attendance • Different causal variable – equate groups on a potential causal variable Objectives 6.2 & 6.3

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