Educational Research Methods Dr. K. A. Korb University of Jos.

Educational Research Methods

Dr. K. A. KorbUniversity of Jos

Introduction

• There is no point to analyzing data from a study that was not properly designed to answer the research question under investigation. In fact, there’s a real point in refusing to analyze such data less faulty results be responsible for implementing a program or policy contrary to what’s really needed.

• Two of the valuable things a researcher can possess are:

1. Knowledge of the principle of good study design 2. The courage to refuse to cut corners

(Dallal, 1998)


Scientific Method1: Ask

Question

2: Design Study

3: Collect Data

4: Analyze Results

5: Reach Conclusions

6: Share Findings


1. Ask a Question

• What is your general research question?• What is the independent variable in the

research question?• What is the dependent variable in the

research question?


2. Design the Study

• Research Design: Structure the research to show how the major parts of the research project work together to address the central research questions– Participants

• What is the population of people I am interested in?– Instruments

• How will I accurately measure my independent and dependent variables?

– Procedure• How will I collect data in an appropriate manner?


Outline

• Types of Research Methodologies– Descriptive– Causal Comparative– Correlation– Experimental– Quasi-Experiment

• Threats to valid Research Design


Descriptive

• Purpose: Carefully describe a naturally occurring educational phenomenon through systematic observation

• Key characteristic: Describes one (sometimes more) variable within a particular population

• Descriptive research designs are sometimes also called Survey Research Designs.


Descriptive

• Research hypotheses are impossible for descriptive designs. Only research questions should be posed.

• There are no independent or dependent variables, simply the key psychological variables that the researchers is interested in.

– Example questions:• What are teachers’ attitude towards a new moral educational

program?• What would counselors recommend be included in an HIV/AIDS

curriculum?• How many students engage in exam malpractice?


Descriptive

1. Select participants: Define the group that possess the variables you want to study

2. Data collection: Administer valid measures of the variables of interest

3. Data analysis: Compute descriptive statistics


Descriptive


Causal Comparative

• Purpose: Determine a cause/effect relationship where the independent variable cannot be manipulated

• Key characteristic: Compare two or more naturally-occurring groups on the dependent variable

• Causal Comparative designs can also be called ex post facto designs


Causal Comparative

• Null hypothesis: There is no significance difference between GROUPS on DEPENDENT VARIABLE.

• Independent variable: Group category• Dependent variable: What the groups are hypothesized to differ

on.– Examples:

• There is no significant differences between boys and girls on interest in mathematics.

• There is no significant differences between children from low and high socioeconomic status in the number of books read in a month.

• There is no significance differences between Nigeria and British children in academic self efficacy.


Causal Comparative

1. Select participants: Obtain a critical number of participants in each group

2. Data collection: Administered valid measures of your variables to all groups of participants

3. Data analysis: Calculate the mean score for each group on the dependent variable.– However, any difference in the mean score between

groups might be due to error.– Therefore, inferential statistics are necessary to

determine if the difference are significant.


Inferential Statistics– The inferential statistics to be depends on how many

groups are being compared• Two groups: t-test• Three or more groups: ANOVA

– If the value is greater than.05, retain the null hypothesis.• There is no significant difference between boys and girls on

interest in math.– If the p-value is less than .05, reject the null hypothesis.

• There is a significant difference between boys and girls on interest in math.– Look at the mean score to determine which group has the stronger

interest.


Causal Comparative


Correlational

• Purpose: Quantity the extent to which two variables are associated

• Key characteristic: The same group of participants are given measures of both key variables in order to calculate the correlation coefficient

• Because of the directionality and third variable problems, there are no independent or dependent variables in correlational designs


Correlational

• Null hypothesis: There is no significant relationship between VARIABLE 1 and VARIABLE 2.

• Examples– There is no significant relationship between number of

books a child reads at home and reading ability.– There is no significant relationship between WAEC scores

and university GPA.– There is no significant relationship between the amount of

time spent in lecture and frequency of exam malpractice.


Correlational

1. Select participants: A homogeneous sample2. Data collection: Administer valid measures

of the variables 3. Data Analysis: Calculate the correlation

coefficient and the significance test for correlation


Interpreting Correlations

• Nature– Positive: Two variables increase or decrease together– Negative: As one variable increases, the other decreases

• Strength– Closer to -1 or +1 is stronger relationship– 0 is no relationship

Negative PositiveNature:

Strength:

0-1 +1



Correlation = .78

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Research Example

• The effect of regular leisure reading on reading achievement in primary school.

• Students in a primary school will be randomly assigned to either a treatment or a control group.– The treatment group will spend 10 minutes everyday reading

a book with an adult.– In an attempt to keep the treatment and control groups as

similar as possible, the control group will also spend 10 minutes with an adult everyday, but will instead do math problems.


Correlational

InterestAcademic

Achievement


Correlation does not prove causation.

InterestAcademic

Achievement

Directionality Problem

InterestAcademic

Achievement

Amount of time spent

studying

Third Variable Problem

Experimental

• Purpose: Establish cause and effect• Key characteristic: Statement about how one

variables affects (causes) another• Three essential components of an experiment– Treatment– Control– Random assignment to treatment and control groups


Experimental• Null hypothesis: There is no significant effect of

TREATMENT on DEPENDENT VARIABLE.– Independent variable: Treatment – Dependent variable: What the treatment should change

• Examples– There is no significant effect of a counseling intervention on

homework completion.• Treatment: Counseling

– There is no significance effect of reading a book a day on reading achievement.• Treatment: Reading a book a day

– There is no significant effective of an anti-exam malpractice campaign on the frequency of exam malpractice.• Treatment: Anti-exam malpractice campaign


Experimental

• Goal: Keep the experiences of the treatment and control groups as identical as possible except for the treatment in order to conclude that the change in the dependent variable is the result of the treatment.

Read a book

every dayReading

Achievement

Experimental Group

Reading Class

ReadingAchievement

Reading Class

Control Group


Experimental

• Random Assignment: Each subject has an equal chance of being assigned to either the treatment or control group– Minimize individual

differences in extra variables that might influence the dependent variable

Read a book

every dayReading

Achievement

Experimental Group

Reading Class

ReadingAchievement

Reading Class

Control Group

Interest


Random Assignment

• Draw names out of a hat

• Random number table

S/No Random Number

Group

1 1 Treatment

2 1 Treatment

3 0 Control

4 1 Treatment

5 1 Treatment

6 0 Control

7 1 Treatment

8 0 Control

9 0 Control

10 0 Control


Experiment• Pretest, Post-test Procedure

1. Random assignment of participants to experimental and control groups

2. Administered valid measure of DV as pretest to all groups

3. Administer treatment to experimental groups(s)4. Administer identical (or conceptually identical) measure

as posttest5. Statistical Analysis

– Descriptive statistics of pretest and post-test score for experiment and control groups separately

– Significance tests to determine significance between differences (Analysis of Covariance: ANCOVA)


Experimental


Experimental• Post-test Only Procedure

1. Random assignment of participants to experimental and control groups

2. Administered treatment to experimental group(s) 3. Administer valid measure of DV post-test4. Statistical Analysis

– Descriptive statistics of post-test score for experimental and control groups separately

– Significance tests to determine significance between differences (Analysis of Variance – ANOVA or t-test)

– The post-test only procedure is typically recommended because of the possibility that the pretest may have an effect on the experiment treatment


Experimental


Quasi-Experiment

• Purpose: Conduct an experiment when random assignment is not possible

• Key characteristic: Treatment and control groups, but no random assignment

• The null hypotheses are exactly the same as the Experimental method


Quasi-Experiment

• Pretest-Posttest Procedure1. Administer valid measure of DV as pretest2. Administer treatment to experimental group(s)3. Administer identical (or conceptually identical) measure

as posttest4. Statistical Analysis

• Descriptive statistical of pretest and posttest score for experiment and control groups separately

• Significance tests to determine significance between difference (ANCOVA)


Review: Research Designs• Descriptive: Carefully describe a naturally occurring

educational phenomenon through systematic observation

• Causal Comparative: Compare two or more groups on a dependent variable

• Correlational: Quantify the extent to which two variables are related

• Experiment: Establish cause and effect– Three requirement:

1. Treatment Groups(s)2. Control Group3. Random Assignment

• Quasi-Experiment: Experiment where random assignment is not possible


Research Designs Conclusion

• Testing the effectiveness of a counseling or teaching intervention MUST either use an experimental or quasi-experimental design

• Simply administering surveys CANNOT establish the quality of a counseling or teaching intervention


Research Example

• The effect of regular leisure reading on reading achievement in primary school

• Students in a primary school will be randomly assigned to either a treatment or a control group.– The treatment group will spend 10 minutes everyday reading a

book with an adult.– In an attempt to keep the treatment and control groups as

similar as possible, the control group will also spend 10 minutes with an adult everyday, but will instead do math problems.

• After one month of the treatment, both groups will be tested on a reading achievement test.


Research Example

ReadingAchievement

ReadingAchievement

Control Group

Experimental Group

Read BookEvery Daywith Adult

IV: RegularLeisureReading

DV:Reading

Achievement

ReadingAchievement

ReadingAchievement

Do MathsEvery Daywith Adult Dr. K. A. Korb

University of Jos

Construct Validity• Construct Validity: Establishing valid operational

measures for the concepts being studied– This relates to:• Independent Variable• Dependent Variable

• Definitions of Variable:– Construct Definition: General explanation of the

construct– Operational Definition: Statement of specifically how

the construct will be measured or implemented in the study


Construct vs. Operational Definitions

AcademicAcademicAchievementAchievement

State ExamsState Exams

NECO ScoresNECO Scores

WAEC ScoresWAEC Scores

Final Course ExamFinal Course Exam

Self-Report of Parents’Self-Report of Parents’Yearly IncomeYearly Income

Public/Private SchoolPublic/Private School

EconomicEconomicStatusStatus

ConstructConstruct Operational DefinitionOperational Definition


Research ExampleConstruct validity focuses on:

ReadingAchievement

ReadingAchievement

Control Group

Experimental Group

Read a BookEvery Day

IV: RegularReading

DV:Reading

Achievement

ReadingAchievement

ReadingAchievement


Construct Validity

• Research studies begin with hypotheses about psychological construct.– There is no significant effect of regular leisure reading on

reading achievement scores.• Independent variable: Regular leisure reading• Dependent variable: Reading achievement score

– The psychological constructs are then operationalized into manipulatable, measurable terms.• Regular leisure reading: Reading a book with an adult everyday

for 10 minutes• Reading achievement score: Classroom exam scores


Construct Validity

• When finished analyzing the data, the result will be translated back into psychological constructs. – The conclusion should not be limited to Reading a book for

10 minutes everyday with an adult leads to higher score on a classroom reading exams.

– The conclusion should be Regular leisure reading will lead to higher reading achievement scores in general.

• However, in order to translate the results back to psychological construct, the study must have construct valid measures of the independent and dependent variables.


Construct Validity• When you develop your research project, you start with a theory.

– For example, regular leisure reading will lead to increased reading achievement scores.

• Then you operationalize your theory into your research study.– You translate “regular leisure reading” into how it will be implemented in your

study – reading a book with an adult everyday for 10 minutes.– You translate “reading achievement scores” into how it will be measured in

your study – classroom exam scores.• When you finish collecting data, you hope to be able to move back to

theory.– You want to be able to say that not only did reading a book for 10 minutes

everyday with an adult lead to higher classroom exam scores on reading achievement, but also that regular leisure reading will lead to higher reading achievement scores in general.

– However, in order to do that, you must have construct valid measures of your independent and dependent variables.


Research Example

IV: RegularReading

DV:Reading

Achievement

Read bookevery day with

an adult for10 min.

Scores onreading sectionof classroom

exams

Constructs:

Operationalized:

IV: RegularReading

DV:Reading

AchievementConstructs:


Construct Validity

• Construct Validity of Research Designs: Allows generalization from the operationalized treatment and measures to the general psychological constructs

• Threats to Construct Validity– Poor construct definitions in the paper– Flawed matching of operationalization to constructs

• The measures do not align with the constructs they were designed to measure.


Construct Validity

• Research studies begin with hypotheses about psychological construct.– There is no significant effect of regular leisure reading on

reading achievement scores.• Independent variable: Regular leisure reading• Dependent variable: Reading achievement score

– The psychological constructs are then operationalized into manipulatable, measurable terms.• Regular leisure reading: Reading a book with an adult everyday

for 10 minutes• Reading achievement score: Classroom exam scores


Construct Validity

• When finished analyzing the data, the result will be translated back into psychological constructs. – The conclusion should not be limited to Reading a book for

10 minutes everyday with an adult leads to higher score on a classroom reading exams.

– The conclusion should be Regular leisure reading will lead to higher reading achievement scores in general.

• However, in order to translate the results back to psychological construct, the study must have construct valid measures of the independent and dependent variables.


Construct Validity• When you develop your research project, you start with a theory.

– For example, regular leisure reading will lead to increased reading achievement scores.

• Then you operationalize your theory into your research study.– You translate “regular leisure reading” into how it will be implemented in your

study – reading a book with an adult everyday for 10 minutes.– You translate “reading achievement scores” into how it will be measured in

your study – classroom exam scores.• When you finish collecting data, you hope to be able to move back to

theory.– You want to be able to say that not only did reading a book for 10 minutes

everyday with an adult lead to higher classroom exam scores on reading achievement, but also that regular leisure reading will lead to higher reading achievement scores in general.

– However, in order to do that, you must have construct valid measures of your independent and dependent variables.


Internal Validity• Internal validity: Extent to which variables other than the

treatment provide plausible explanations to the experimental results– Only relevant for experimental designs

• Primary consideration for interventions– Extraneous variable: Any variable other than treatment variable that,

if not controlled, can affect the experimental outcome– Hold constant or eliminate all extraneous variables that might affect

the posttest– Goal of Research Design: Create set of conditions so any observed

changes in your dependent variable can be attributed to experimental treatment instead of extraneous variables

• Do variables other than the treatment provide plausible explanations to the experimental results?


Research Example

ReadingAchievement

ReadingAchievement

Control Group


IV: RegularReading

DV:Reading

Achievement

ReadingAchievement

ReadingAchievement

Experimental Group

Adult Attention

ReadingAbility

Interest

Maturation


Threats to Internal Validity• History: If treatment lasts over time, other events

may influence dependent variable– To prevent: Keep the control group equivalent in all

aspects but treatment• Maturation: Physical or psychological changes may

influence the dependent variable– To prevent: Use a control group

• Selection Bias: Treatment and control groups are different on an important extraneous variable– To prevent: Random assignment OR Use a pre-test


Threats to Internal Validity• Testing: Giving a pretest may increase performance

on the post-test– To prevent: Don’t use a pre-test OR Use different pre- and

post-tests• Instrumentation: Nature of measuring instrument

has changed between pre- and post-test– To prevent: Do not use a pre-test OR Use the same for

pre- and post-test• Many of these solutions to prevent threats to

internal validity contradict. – Consider the threats that are most relevant to a particular

study and then develop a strategy for overcoming the most important threats.


External Validity

• External Validity: Establishing the group of people to which the research findings can be generalized


Research Example

ReadingAchievement

ReadingAchievement

Control Group


ReadingAchievement

ReadingAchievement

Experimental Group

PopulationPopulation

SampleSampleDr. K. A. KorbUniversity of Jos

Types of External Validity• Population Validity: Generalizing the results from an

experimental sample to a defined population– To establish: Give a thorough explanation of the constitution of

the constitution of the sample and how the sample was selected.• Ecological Validity: Generalizing the results of a study from

the artificial conditions created by researcher to real-life conditions– To establish:

• Give an adequate description of treatment• Give an adequate description of the measure for the dependent

variable– Threats to Ecological Validity:

• Novelty: The treatment was different than typical treatment• Experimenter Effect: The particular person delivering the treatment

affects results


Reliability

• Reliability: Demonstrating that the operations of the study can be repeated with the same results– Conduct research as if someone were always

looking over your shoulder– Report the procedure of your study in explicit

detail


Other Issues in Valid Research Design

• Experimenter Bias: Researcher’s expectations about the outcome of experiment influences participants’ response– To prevent: Use research assistants who are blind to the

study (aka do not know the purpose of the study)• Treatment Fidelity: Extent to which treatment

conditions are implemented according to the researcher’s specifications– To support: • Carefully train research assistants• Periodically check up on research assistants

unexpectedly to determine if they are following guidelines


Other Issues in Valid Research Design

• Strong Experimental Treatments: Developing a treatment that will make a robust effect on the dependent variable– To support:• Develop a thorough understand of the dependent

variable and how it can be influenced.• Spend much thoughtful time developing your

treatment.


Revision• Describe the five types of educational research

designs.• What is construct validity as related to research

designs? How can it be supported?• What is internal validity? What are threats to

internal validity?• What is external validity? What are types of

external validity?• What are some other issues to consider when

conducting educational research?


Educational Research Methods Dr. K. A. Korb University of Jos.

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Transcript of Educational Research Methods Dr. K. A. Korb University of Jos.