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Which of the following questions would be appropriate for experimental research?
Which of the following questions would be appropriate for experimental research?
What is the goal of experimental research?
What is the goal of experimental research?
The goal of experimental research is to determine whether a causal relationship exists between two or more variables.
A dependent variable is the variable that is manipulated by the experimenter.
A dependent variable is the variable that is manipulated by the experimenter.
False
What is an extraneous variable, and why is it important to control in experimental research?
What is an extraneous variable, and why is it important to control in experimental research?
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What are the levels of the independent variable?
What are the levels of the independent variable?
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In what two ways can the levels of the independent variable differ?
In what two ways can the levels of the independent variable differ?
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Why are pre-experimental designs considered weak in terms of internal validity?
Why are pre-experimental designs considered weak in terms of internal validity?
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True experimental designs use random assignment of subjects to groups and control for extraneous variables.
True experimental designs use random assignment of subjects to groups and control for extraneous variables.
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What are quasi-experimental designs, and when are they often used?
What are quasi-experimental designs, and when are they often used?
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The research hypothesis for an experiment predicts that there will be no difference between the treatment and control groups.
The research hypothesis for an experiment predicts that there will be no difference between the treatment and control groups.
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What are comparison groups, and how do they differ from control groups in an experiment?
What are comparison groups, and how do they differ from control groups in an experiment?
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Which type of validity refers to the degree to which the results of an experiment can be generalized to other populations, settings, and times?
Which type of validity refers to the degree to which the results of an experiment can be generalized to other populations, settings, and times?
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A single-variable design has two or more manipulated independent variables.
A single-variable design has two or more manipulated independent variables.
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Which of the following is NOT a classification of experimental designs based on the level of control?
Which of the following is NOT a classification of experimental designs based on the level of control?
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A factorial design can only be used with one independent variable.
A factorial design can only be used with one independent variable.
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What is the purpose of factor analysis?
What is the purpose of factor analysis?
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What is the difference between a census and a sample survey?
What is the difference between a census and a sample survey?
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Longitudinal surveys gather data at a single point in time.
Longitudinal surveys gather data at a single point in time.
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Match the types of longitudinal surveys with their descriptions:
Match the types of longitudinal surveys with their descriptions:
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Study Notes
Experimental Research
- An experiment is a scientific investigation where a researcher manipulates one or more independent variables, controls other relevant variables, and observes the effect of the manipulations on the dependent variable(s).
- The goal of experimental research is to determine if a causal relationship exists between two or more variables.
- Independent variable: manipulated by the experimenter.
- Dependent variable: observed, not manipulated; the effect of changes in the independent variable is observed on this variable.
- Example: to examine the effect of different teaching methods on achievement in reading, an investigator would manipulate method (the independent variable) by using different teaching methods to assess their effect on reading achievement (the dependent variable).
Characteristics of Experimental Research
- Control: Eliminating all other possible explanations by controlling the influence of irrelevant variables.
- Manipulation of the independent variable: Setting up different treatment conditions. Treatment is another word for the manipulation of the independent variable. Levels of the independent variable are the different treatment conditions.
- Observation and measurement: After applying the experimental treatment, observing to determine if the hypothesized change occurred.
Essential Requirements for Experimental Research
- Control
- Manipulation of the independent variable
- Observation and measurement
Control Variables
- Eliminating all other possible explanations by controlling the influence of irrelevant variables.
- Purpose: To arrange a situation in which the effect of a manipulated variable on a dependent variable can be investigated.
Extraneous Variable
- A variable that is not related to the study's purpose but may affect the dependent variable.
- Aptitude is a relevant extraneous variable (in the example given).
- Randomly assigning subjects to the two groups is the best way to control for an extraneous variable such as aptitude.
Experimental Comparison
- An experiment begins with an experimental hypothesis: A prediction that the treatment will have a certain effect.
- The research hypothesis expresses expectations as to results from the changes introduced, that treatment and no-treatment groups will differ because of the treatment's effects.
- For the simplest experiment, two groups are needed: experimental group and control group.
- The experimental group receives a specific treatment, the control group receives no treatment.
- Researchers commonly compare groups receiving different treatments. These are called comparison groups.
- The majority of educational experiments study the difference in the results of two or more treatments rather than just one treatment versus no treatment.
Validity of Research Designs
- Internal validity: Validity of the inferences about whether the effect of variable A (the treatment) on variable B (the outcome) reflects a causal relationship.
- External validity: The validity of the inference about whether the cause-effect relationship holds up with other subjects, settings, and measurements.
Classifying Experimental Designs
- Based on the number of independent variables:
- Single-variable designs: one manipulated independent variable.
- Factorial designs: two or more independent variables, at least one which is manipulated.
- Based on control of threats to internal validity:
- Pre-experimental designs: do not use random assignment of subjects to groups, and do not control extraneous variables.
- True experimental designs (randomized designs): use random assignment of subjects to groups and control extraneous variables.
- Quasi-experimental: do not use random assignment of subjects to groups but control extraneous variables (when intact classrooms are used).
Notational Conventions for Designs
- X: independent variable (experimental variable or treatment)
- Y: dependent variable
- Y₁: dependent variable (before manipulation of the independent variable, pretest)
- Y₂: dependent variable (after manipulation of the independent variable, posttest)
- S: subject or participant used in the experiment
- E: experimental group
- C: control group
- R: indicates random assignment of subjects to the experimental groups, and indicates random assignment of treatments to the groups.
- M₁: indicates subjects are matched, then members of each pair are assigned to the comparison groups at random.
Preexperimental Designs
- Design 1: One-Group Pretest-Posttest Design: Three steps: (1) Administering a pretest measuring the dependent variable, (2) Applying the experimental treatment X to the subjects, (3) Administering a posttest to again measure the dependent variable.
Static Group Comparison Design
- Design 2: Static Group Comparison: Uses two or more preexisting or intact groups, only one of which is exposed to the experimental treatment.
True Experimental Designs
- Design 3: Randomized Subjects, Posttest-Only Control Group Design: No pretest; randomization controls possible extraneous variables. After random assignment to groups, only the experimental group is exposed to the treatment.
- Design 4: Randomized Matched Subjects, Posttest-Only Control Group Design: Similar to Design 3, but uses a matching technique to form equivalent groups. The matching variables are ones likely to correlate significantly with the dependent variable. Useful for studies with small samples where Design 3 is inappropriate.
- Design 5: Randomized Subjects, Pretest-Posttest Control Group Design: Random assignment to experimental and control groups. Administers a pretest on the dependent variable. The treatment is introduced only to the experimental subjects, after which the dependent variable is measured in both groups.
- Design 6: Solomon Four-Group Design: Similar to Design 5, but employs a second control group (not pretested and exposed to the treatment). Main purpose is to overcome any pretesting x treatment interaction.
Factorial Designs
- Design 8: Simple Factorial Design: The simplest factorial design is the 2x2. Has two factors, and each factor has two levels.
Quasi-Experimental Designs
- Design 9: Nonrandomized Control Group, Pretest-Posttest Design: One of the most used quasi-experimental designs in educational research. Similar to Design 5, but does not permit random assignment of subjects to experimental and control groups.
- Design 10: Counterbalanced Design: Used with intact class groups; the groups receive treatments in a different order in replications.
Ex Post Facto Research
- Derived from Latin for "after the fact."
- Conducted after variation in the variable of interest has already been determined.
- Sometimes called causal comparative research, its purpose is to investigate cause-and-effect relationships between independent and dependent variables.
- Attribute independent variables are variables such as home environment, motivation, intelligence, parental reading habits, age, ethnicity.
Planning an Ex Post Facto Research Study
- State the research problem as a question.
- Select two or more groups to be compared. These groups should differ on the variable of interest, but be similar on any extraneous variables.
- Determine whether proactive (start with subjects based on independent variables) or retroactive (start with subjects based on dependent variables) design is needed.
Correlational Research
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Employing data derived from preexisting variables (similar to ex post facto).
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No manipulation of the variables.
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Assessing relationships among two or more variables in a single group.
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Uses an index called a correlation coefficient.
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Positive coefficient: direct relationship.
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Negative coefficient: inverse relationship.
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Zero coefficient: no relationship.
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Values of a correlation coefficient range from -1.00 to +1.00.
Correlation Coefficients
- Pearson Product Moment Coefficient (Pearson r): Assumes data pairs approximately fall on a straight line, measured at the interval or ratio level, variables have a joint normal distribution.
- Spearman Rho Coefficient (Spearman p): Assumes data are measured at the ordinal level, or interval/ratio level but doesn't meet normality condition.
- Phi (4): Used when both variables are genuine dichotomies..
Multiple Regression and Factor Analysis
- Multiple Regression: Examines the relationships among several variables; finds the best possible weighting of predictors for a dependent variable.
- Factor Analysis: Detects patterns in a set of interval-level variables. Begins with pairwise correlations among variables, creating a correlation matrix and reducing to a smaller set of underlying factors.
Survey Research
- Asking questions about people's beliefs, opinions, characteristics, behavior.
- May investigate how various characteristics (age, education, social class, race) relate to attitudes toward certain issues.
- Generally, doesn't make causal inferences, only describes distributions of variables.
- Types:
- Census: covers the entire population of interest.
- Sample survey: studies a portion of the population.
- Types based on time dimension:
- Longitudinal: gather information at different points in time, to study changes. Designs include panel studies, trend studies, cohort studies.
- Cross-Sectional: study a cross section (sample) of a population at a single point in time.
Important Notes
- There are examples and discussion of different types of surveys provided in the document that can be further studied
- The document provides tables to analyze the data with examples
- Different types of research questions are provided and the best approach to each type of question is identified
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Description
This quiz covers the basics of experimental research, focusing on the definitions and roles of independent and dependent variables, as well as the characteristics that define this method of investigation. Participants will learn how control and manipulation contribute to determining causal relationships in research.
