Chapter 3

Research perspectives QuantitativeQualitative DescriptiveInferential True ExperimentalQuasi Experimental Causal ComparativeCorrelational Single SubjectGroup TeacherTraditional Large ScaleSmall Scale

Quantitative and Qualitative Research Differences QuantitativeQualitative ObjectiveSubjective Objective reality to discover Subjective realities to share ProductProcess NumbersWords DeductiveInductive Hypothesis (before) are static Hypothesis (maybe) are dynamic Research is detachedResearcher may participant

Both seek to understand or know the characteristics of a group Participants teach us about the … participants Participants teach us about … the larger population Generalization DescriptiveInferential statistics Descriptive Research and Inferential Research

True Experimental and Quasi-experimental Random Assignment True Experiment uses random assignment Quasi-experimental has no random assignment Manipulation of the Independent Variable Both types involve the manipulation of the IV e.g., the creation of groups of participants based on some characteristic Random assignment strengthens an Experiment Improves control- reduces alternative explanations Difficult to achieve in real-world settings

Causal – Comparative (ex post facto) An attempt to investigate a cause-effect relationship with historical data; data from the past – hence ex post facto IV is an attribute variable that allows participants to be grouped and differentiated (e.g., gender, smokers/non- smokers, Head-start/Non-Head- start students) Since the “treatment” group is based on past: No random assignment No intervention Cause-effect CANNOT be determined by ex post facto. Relationships between variables (IV and DV) can be identified but no cause-effect

Correlational Studies Investigate relationships or associations between variables Individual differences are used to examine the relationships (as opposed to group differences); the statistics are based upon individual scores and not group measures such as the mean (average). Cause-effect CANNOT be determined by ex post facto. Relationships between variables (IV and DV) can be identified but no cause-effect.

Single Case Studies and Large Group Studies Single Case studies Good for studying about one person and effects of treatment on person The participant can serve as a control that one person Cannot generalize or make conclusions about others Can lead to further research that can be generalized beyond the one case Large Group Studies Relationships among variables Trends over time Large numbers of cases (people) are needed to compute the statistics needed for examining relationships among variables. Greatest benefit is that the results can be generalized to the larger population

Teacher Research and Traditional Research Teacher as the Researcher – Action Research Self-reflection Is local Addresses a local research question Involves all Stakeholders Cannot be generalized Does not contribute to the large body of research literature Traditional Research Outside researcher May or may not be local May or may not consider stakeholders May generalize Contributes to the larger body of research literature

Evaluation Research May be local; may be large-scale (e.g., beyond local) Policy evaluation National policy examples: Head Start, DARE Local policy example: Truancy policy, segmentation of grades Both levels follow same basic methodology and considers same concerns Stakeholders Goals or benchmarks Formative & Summative evaluation

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