experimental research

Methods of Research and Enquiry

Experimental Researchby Dr. Daniel Churchill

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Task Presentation

Correlational Research Question

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What is Experimental Research

Test hypotheses concerning cause and effect relationships

A researcher manipulates at least one independent variable, controls other variables and observes effect on one or more independent variables.

Usually there are different groups of subjects who get different treatment

Individuals randomly assigned to treatment groups

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Experimental research

Most studies compare groups When individuals are studies, the studies

are called single-case (or single subject) designs.

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Experimental Process

Six steps to conducting experimental research Selection and definition of the problem

Statement of a hypothesis indicating a causal relationship between variables

Selection of participants and instruments Random selection of a sample of subjects from a

larger population Random assignment of members of the sample to

each group Selection of valid and reliable instruments

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Experimental Process Six steps to conducting experimental

research (cont.) Selection of a research plan

Three types of comparisons Comparison of two different approaches Comparison of new and existing approaches Comparison of different amounts of a single approach

Execution of the research plan Two concerns

Sufficient exposure to the treatment Substantively different treatments

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Experimental Process

Six steps to conducting experimental research (cont.) Analysis of data Formulation of conclusions

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Manipulation and Control Manipulation

The researcher’s decisions related to what constitutes the independent variable

Active and assigned variables Active variables are those the researcher actively

manipulates Choice of an instructional strategy A particular counseling approach

Assigned variables are those that cannot be manipulated by the researcher but are of interest

Gender Race

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Manipulation and Control

Control The researcher’s efforts to remove the influence of any

extraneous variables that might have an effect on the dependent variable

The goal is to be assured the only differences between groups is that related to the independent variable

Participant variables – characteristics of the subjects Pre-existing achievement levels Differences in attitudes

Environmental variables – characteristics of the context Learning materials Differences in the time available for treatment between groups

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Group Designs

Two major classes of group designs Single-variable designs – one independent

variable Factorial designs – two or more independent

variables

Three types of experimental designs Pre-experimental designs Experimental designs Quasi-experimental designs

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Pre-Experimental Designs

Three types One-shot case study

X O

One-group pretest-posttest design O X O

Static group comparison X1 O

X2 O

Threats to internal validity – see Figure 9.1

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True Experimental Designs

Three types Pretest-posttest control group design

R O X O

R O O

Posttest only control group design R X O

R O

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True Experimental Designs Three types (cont.)

Solomon four-group comparison R O X O

R O O

R X O

R O


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Quasi-Experimental Designs Three types

Non-equivalent control group design O X O

O O

Time series design O O O O X O O O O

Counterbalanced design O X1 O X2 O X3 O

O X3 O X1 O X2 O

O X2 O X3 O X1 O


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Factorial Designs Two independent variables and one dependent

variable The effect of teaching strategy and gender on

students’ achievement The effect of a particular counseling technique and

the clients’ ethnicity on the success of the treatment The effect of a specific coaching approach and

children in three age groups on the ability to perform certain physical tasks

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Factorial Designs Interaction

Visually explained by a graph of performance of all levels of both independent variables Parallel lines indicate no interaction Non-parallel lines indicate an interaction

Statistically examined with an F-test of the statistical significance of the interaction

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Visual presentation of a significant interaction

Statistical analysis of this significant interaction: F1,16 = 4.88 (p = .0420)

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Visual presentation of a non-significant interaction

Statistical analysis of this non-significant interaction: F1,16 = 0.97 (p = .340)

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Measurement Scales

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Inferential Statistics

Applied only when groups are compared T-test is used to compare experimental

group to control group, boys to girls, pre-tests to post-tests, etc

The numbers used for comparison are means

Interval or ratio scale derived form the same measure (e.g., same test)

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Hypotheses for t-test

H0 Mean 1= Mean 2

HA Mean 1 Mean 2 T value is calculated using a specific

formula Statistical tables are used to determine

level of significance (check http://www.statsoft.com/textbook/sttable.html)

H0 is kept or rejected (check the table)

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Inferential Statistics

ANOVA is used to compare mean of two or more samples and to test whether the differences are statistically significant.

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Useful reading

Here is a useful reading written by HKU professor

Interesting resource for learning about statistics is available here:http://www.mnstate.edu/wasson/ed602.htm

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Task to be completed before next class

Your group should discuss some possible question that can be classified as Experimental Research. In your blog propose potential experimental research question, how could data for the related variables be collected, and provide argument how answer to that question can contribute to improvements in some aspect of education/teaching and learning.

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References

Gay, L. R., Mills, G. E., & Airasian, P. (2006). Educational Research: Competencies for Analysis and Applications. Upper Saddle River, N.J. : Pearson/Merrill Prentice Hall.

Ravid, R. (2000). Practical statistics for educators. (2nd ed). New York, NY.: University Press of America, Inc.

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