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Foundations of Research

Quantitative Research

Numerical data
Casual Comparative
Single Subject Experiment
Multiple Regression

Mixed Method Research

Action Research
Both Quantitative and Qualitative

Qualitative Research

Case Study
Grounded Theory


The scientific description of the customs of peoples and cultures.

Basic and Applied Research (for theories)

Basic- use to develop or refine a theory
Applied- use to apply or test theory

Education Research (Formative and Summative)

Formative: use to improve a program/product under development.
Summative: use to evaluate the overall quality of a program/product to make decisions

Research and Development (R&D)

Use to research consumer needs and develop a product to fulfill those needs.
*Is not to test a theory.

Action Research

Use to solve everyday problems.
*not to test theory and result are not to generalized to other settings.

choice of paradigms (quanitative, qualitative, or action)

not a matter of personal preferences; rather, it is a matter of the research question that is being answered.

Which research design is best for educators?

The type of research one chooses is really based on the research question they want to answer. That is the first, most important, consideration.


a perspective based on a set of assumptions, concepts, and values that are held by a community or researchers.


something that takes on different values or categories
the opposite of constants


something that cannot vary, such as a single value or category of a variable

quantitative variables

vary in degree or amount (e.g., annual income- varies from zero to very high income)

categorical variables

vary in type or kind (e.g., gender).

independent variables

the presumed cause of another variable
example: amount of studying affects test grade.

Dependent variables

the presumed effect or outcome.
are influenced by one or more independent variables.

Example of Independent and dependent variables

Dependent:Lung Cancer

intervening variables

also called mediator or mediating variables.
are variables that occur between two other variables.
example, tissue damage is an intervening variable in the smoking and lung cancer relationship.
Smoking---->Tissue Damage---->Lung Cancer

purpose of experimental research

to study cause and effect relationships

random assignment

which creates "equivalent" groups
used in the strongest experimental research designs

active manipulation of an independent variable

it is only in experimental research that "manipulation" is present

extraneous variable

a variable that may compete with the independent variable in explaining the outcome. Remember this, if you are ever interested in identifying cause and effect relationships you must always determine whether there are any extraneous variables you need to worry about.

confounding variable

it has confused or confounded the relationship we are interested in.

moderator variable

delineates how a relationship of interest changes under different conditions.
Perhaps the relationship between studying(IV) and test grades (DV) changes according to different levels of use of a drug such as Ritalin (MV).

nonexperimental research

no manipulation of the independent variable. There also is no random assignment of participants to groups.
if you ever see a relationship between two variables in nonexperimental research you cannot jump to a conclusion of cause and effect because there will be too many other alternative explanations for the relationship.

case of correlational research

one quantitative IV and one quantitative DV.
Example: Self-esteem (IV) and class performance (DV).

· You would look for the relationship by calculating the correlation coefficient.

· The correlation coefficient is a number that varies between -1 and +1, and 0 stands for no relationship. The farther the number is from 0, the stronger the relationship.

· If the sign of the correlation coefficient is positive (e.g., +.65) then you have a positive correlation, which means the two variables move in the same direction (as one variable increases, so does the other variable). Education level and annual income are positively correlated (i.e., the higher the education, the higher the annual income).

· If the sign of the correlation coefficient is negative (e.g., -.71) then you have a negative correlation, which means the two variables move in opposite directions (as one variable increases, the other decreases). Smoking and life expectancy are negatively correlated (i.e., the higher the smoking, the lower the life expectancy).

"basic case" of causal-comparative research

one categorical IV and one quantitative DV
Example: Gender (IV) and class performance (DV).

· You would look for the relationship by comparing the male and female average performance levels.

3 Necessary Conditions for Causation

To conclude changes in variable A cause changes in variable B.
Condition 1:Relationship conditon - Variable A and Variable B must be related.
Condition 2: Temporal Antecedent Condition - proper time order must be established.
Condition 3: Lack of alternative explanation condition- the relationship between variable A and B must not be due to some confounding extraneous or third variable

Qualitative Research Methods

1- Phenomenology
2- Ethnography
3- Case study research
4- Grounded theory
5- Historical research


a form of qualitative research in which the researcher attempts to understand how one or more individuals experience a phenomenon. For example, you might interview 20 widows and ask them to describe their experiences of the deaths of their husbands.


is the form of qualitative research that focuses on describing the culture of a group of people. Note that a culture is the shared attitudes, values, norms, practices, language, and material things of a group of people. For an example of an ethnography, you might decide to go and live in a Mohawk communities and study the culture and their educational practices.

Case study research

is a form of qualitative research that is focused on providing a detailed account of one or more cases. For an example, you might study a classroom that was given a new curriculum for technology use.

Grounded theory

is a qualitative approach to generating and developing a theory form data that the researcher collects. For an example, you might collect data from parents who have pulled their children out of public schools and develop a theory to explain how and why this phenomenon occurs, ultimately developing a theory of school pull-out.

Historical research

research about events that occurred in the past. An example, you might study the use of corporeal punishment in schools in the 19th century.

Mixed Research Methods

general type of research in which quantitative and qualitative methods, techniques, or other paradigm characteristics are mixed in one overall study.

Advantages of Mixed Research

First of all, we advocate the use of mixed research when it is feasible. We are excited about this new movement in educational research and believe it will help qualitative and quantitative researchers to get along better and, more importantly, it will promote the conduct of excellent educational research

Mixed method research

is research in which the researcher uses the qualitative research paradigm for one phase of a research study and the quantitative research paradigm for another phase of the study. For example, a researcher might conduct an experiment (quantitative) and after the experiment conduct an interview study with the participants (qualitative) to see how they viewed the experiment and to see if they agreed with the results. Mixed method research is like conducting two mini-studies within one overall research study.

Mixed model research

is research in which the researcher mixes both qualitative and quantitative research approaches within a stage of the study or across two of the stages of the research process. For example, a researcher might conduct a survey and use a questionnaire that is composed of multiple closed-ended or quantitative type items as well as several open-ended or qualitative type items. For another example, a researcher might collect qualitative data but then try to quantify the data.

Types of Quantitative Research

1- Experimental
2- Nonexperimental

Methods of Knowing

-Authority (someone we know and trust tells us)
*All limited so as researchers we use Scientific Method

Inductive Reasoning

Developing generalizations based on observation of a limited number of related events or experiences.
An instructor reviews research methods texts and notices sampling content in each text and concludes that all research methods texts have sampling
A teacher knows several student athletes who are good students and concludes that all student athletes are good students

Deductive Reasoning

Arriving at specific conclusions based on general principles, observations, or experiences.
All research textbooks contain a chapter on sampling. The book you are reading is a research text and therefore must contain a sampling chapter.
All student athletes are good students. Mary is a student athlete and therefore she must be a good student.

Steps of the Scientific Method

Recognition and identification of a problem
Formulation of hypothesis
Data collection
Data analysis
Statement of conclusions
Confirm or disconfirm hypothesis


an explanation for the occurrence of certain behaviors, phenomena, or events

Limitations of the Scientific Method

The scientific method can not answer all questions, especially those of a philosophical or ethical nature.
•Application of the scientific method can never capture the full richness of the context.
•Measurement error is a limitation of the scientific method.

goal of educational research

describe, explain, predict, and control situations involving human beings.

Selection and definition of a problem

A problem is a question of interest.
•The problem can be tested or the question answered through the collection and analysis of data.
•Generally researchers use a review of the existing literature to generate hypotheses related to their question.

Execution of research procedures

Research procedures are dictated by the research problem and the identified variables.
•Procedures include activities related to collecting data about the problem.

Analysis of Data

Data are analyzed such that the researcher can test the hypothesis or answer the research question.
•Data analysis often includes statistical techniques.

Drawing and stating conclusions

-Conclusions are based upon analyses of our data and are stated in terms of the original hypothesis or research question.
Conclusions should indicate whether the hypothesis was rejected or supported.
-For those studies that include synthesis of verbal data, conclusions may be more tentative.

Educational research is often broadly categorized as qualitative or quantitative.

Both quantitative and qualitative researchers collect and analyze data.
Both quantitative and qualitative researchers derive conclusions and interpretations.

Approaches to Educational Research-Quantitative

Numerical data
Describes, predicts or controls variables of interest
The world is relatively uniform, stable, and predictable
Researchers state hypothesis, specify research procedures, and control context.
Researchers identify large samples.
Researchers are interested in statistical significance

Approaches to Educational Research-Qualitative

Narrative and visual data
Gains insights into phenomenon of interest
Knowledge is situated and contextual. There are different perspectives
Researchers form foreshadowed problems. They don't control but explain context.
A large amount of data is collected over an extended time in a natural setting.
Data are categorized and organized into patterns

Example of Quantitative

Are there differences in the amount of discipline referrals between girls and boys with Autism Spectrum Disorders?
What variable best predicts whether first generation college students stay continually enrolled in college until graduation?
Do students exposed to animated science materials learn more if the animation is accompanied by sound or no sound?

Example of Qualitative

What are the social experiences of middle school girl with an Autism Spectrum Disorder?
What challenges do first generation college students from small rural schools experience as they enroll in college?
How do students describe their experiences learning from animated science materials?

Survey Research

-determines and reports the 'current status' of the subject of study.
-often collects numerical data to test hypotheses or answer questions.
-may examine preferences, attitudes, or opinions
How do parents feel about national teacher certification?
To what degree do students report test anxiety before the SAT exam?

Correlational Research

-provides a quantitative measure of relationship between or among variables.
-This measure is expressed as a correlation coefficient.
Ranges from -1 to 1; 0 indicates no relationship
-do not indicate cause-effect relations among variables.
A high correlation between self-concept and achievement does not mean that self-concept causes higher achievement.

Causal-Comparative Research

-attempts to determine the cause or reason for existing differences.
-The grouping variable is the potential cause.
-The dependent variable is the effect.
Are there differences in final exam performance between students given a practice exam and those given more time for independent study?
Are there differences between elderly men and women who recently experienced a stroke in the amount of minutes of exercise during rehabilitation prior to release from hospital?

Causal-Comparative Research

-provides limited cause-effect data but true cause-effect findings can be determined only through experimental research.
-Sometimes it is impossible to conduct true experiments such as when grouping variables:
Cannot be manipulated.
e.g., year in school, age, gender
Should not be manipulated.
e.g., attended rehabilitation or not; exposed to verbal abuse or not

Experimental Research

includes at least one independent variable and the effect is measured on at least one dependent variable.
In experimental research extraneous variables are controlled.
researchers select participants, group participants, administer treatments, control the research setting, control the length of treatment exposure, select research measures, and are able to draw cause-effect conclusions.

Examples of Experimental Research

Sometimes experimental research is not possible in educational contexts because of difficulties with random selection and random assignment.
Are there differences in achievement between students randomly assigned to one of two problem solving strategy conditions?
The independent variable is problem solving strategy conditions.
The dependent variable is achievement.
Is there an effect of corrective feedback on students' achievement on final physics test scores and interest in physics?
The independent variable is corrective feedback.
The dependent variables are final test scores and interest.

Single-Subject Research

used to study behavior change within a person or a group as they are exposed to an intervention or a treatment.
In single-subject research the size of the sample is one.
The effects of graphing intervention on off-task behavior.
The effects of a cessation program on smoking.

Qualitative Research

-seek rich understandings.
-conducted through sustained in-depth, in-context, research.
-numerous approaches: historical research, symbolic interaction, grounded theory, ethology, phenomenology

Narrative Research

-study how different people experience their world.
-allows for people to tell the story of their lives.
-often focus on one person and collect stories of that person's life.
-establish a trusting personal relationship with their participants.
-The narrativeis the story of the phenomenon being investigated and also the method of inquiry.

Narrative Research-Examples

What is the experience of students in a new co-ed dormitory?
How does a winning coach react when faced with a less skilled team and a losing season?

Ethnographic Research

-the study of cultural patterns and perspectives of participants in their natural settings.
-avoid interpretations early and enter the setting slowly.
-have personal relationships with their participants.
-collect data in waves, re-entering the site several times.
-resultant ethnography is a narrative that presents participants' everyday events.
-During data collection the ethnographer identifies categories and enters themes into these categories.

Ethnographic Research Examples

How does the returning student population adjust to technology enhanced instruction in entry level college courses?

Case study

-qualitative approach that examines a bounded system for study.
-includes specific design, data collection techniques, and data analysis strategies.
What are the challenges faced by a school board with shrinking district population and mandated facility renovations?

Qualitative Research Process

1.Identifying a research topic
•The initial topic is often narrowed.
2.Reviewing the literature
•Previous research is examined to garner important information.
3.Selecting participants
•Generally fewer purposely sampled participants than in quantitative studies.
4.Collecting data
•Generally interviews, observations, and artifacts serve as data
5.Analyzing and interpreting data
•Researchers analyze for themes and generate interpretations.
6.Reporting and evaluating the research
•Researchers summarize and integrate the data in narrative and visual form.

Qualitative Research

1.Qualitative researchers spend a great amount of time in the field and engage in person-to-person interactions.
2.Qualitative data are analyzed inductively.
3.Qualitative researchers avoid making assumptions and remain open to alternative explanations.

Classification of Research

The approach used in a study is determined by the research problem.
Often the same general problem can be approached from several different types of study.
Research methods are selected after the topic or question is determined

Example of how to choose which type of research to use...

Given the general topic of year-round schooling, suggest how this topic can be addressed differently by each one of the types of research :
Survey: What are parents' opinions about year-round schooling?
Correlational: Is there a relationship between standardized test scores and year-round schooling?
Causal-Comparative: Are there differences in amount of content mastered between children enrolled in year-round schooling versus those in traditional schooling?
Experimental: Are there differences in self-esteem between those students randomly assigned to districts with year-round schooling versus those assigned to traditional schooling?
Single subject: What are the effects of year-round schooling on the vocabulary use of students who are reading disabled?

Research by Purpose

Basic and applied research
Basic research is conducted to develop or refine theory.
Applied research is conducted to apply or test a theory.
Evaluation research
Evaluation research is a form of applied research that involves data collection for decision making.
Evaluation research may be formative or summative
Research and Development (R & D)
Research and development is the process of researching needs and developing products to fit those needs.
Action Research
Action research is a systematic inquiry conducted by teachers, principals, or other stakeholders.

Ethics of Educational Research

Ethical considerations are an important part of research.
Researchers must be aware of and attend to ethical considerations.
Two main overarching ethical rules guide researchers.
Participants should not be harmed.
Researchers obtain participants' informed consent.
Researchers must submit their proposal for review and approval.
Deception poses an ethical dilemma. If the participants know the purpose of a study, it may change their behavior.
e.g., gender, race, attitudes, medical status
When a study must use deception it causes problems for informed consent. These types of studies must undergo strict ethical review.

Ethics of Educational Research-societies

behavioral researchers have similar codes for ethical research largely due to the National Research Act of 1974 which Created a code for the protection of human subjects.

Ethics of Educational Research-institutions

have review groups that assure participant protections.
IRB (Institutional Review Board) or HSRC (Human Subjects Review Committee)

Participants should not be harmed.

Physically, mentally, socially
Research participants freely agree to participate
Researchers ensure freedom from harm
No undue risks

Informed consent

: Researchers provide information about the study and any potential dangers

Personal privacy and confidentiality

Limit access of data to those who 'need to know'
Participants' involvement should not be reported
Study participants have complete anonymity when their identities are unknown to the researcher.
Study participants are known to researcher but are not disclosed.
e.g., removing names from data

The Buckley Amendment (The Family Educational Rights and Privacy Act of 1974)

Data that identifies a student is not available without written permission
Must describe what data, for what purposes, and to whom

Ethics of Qualitative Research

In addition to ethics of educational research generally, qualitative research often poses additional ethical challenges.
The nature of the research changes so informed consent is challenging.
The close relationship between the researcher and the participant may allow the researcher to know personal and perhaps ill-acts of the participant that may pose ethical challenges.

Ethical Guideposts

A researcher should have an ethical perspective with regard to the research that is very close to her personal ethical position.
Informed consent should be obtained through a dialogue between the researcher and the participants
Be cognizant of the broader social principles that define your ethical stance. Potential results do not drive ethical standards.
Minimize the potential for harm to your participants.
Attend to confidentiality and omit deception.

Gaining Entry to the Research Site

Researchers need cooperation to conduct their studies.
Identify and follow procedures for gaining approval at any given site.
e.g., superintendent or school board
Procedures generally require filling out forms that describe the study.
Researchers may need permission from principals or teachers.
Written permission from parents is often required.
Gaining entry and obtaining permission often takes considerable time.
Schools and other research communities may request something in return for their participation in your study.
e.g., a final report prior to dissemination, professional development, parent education

What are some advantages of using quantitative data?

Some examples include that you can analyze vast amount of information quickly, the data can more easily be gathered, and you can more easily compare the results of different groups

What are examples of qualitative research data collection instruments?

Examples of qualitative data collection instruments are surveys; interviews notes , recordings, and transcripts; and field observation protocols.

What is quantitative data?

Quantitative data are anything that provides a quantity or numerical score, such as the scores from a test or rubric.

Survey Research

-involves collecting data
to test hypotheses or to answer questions
about people's opinions on some topic or
-an instrument to collect data that describes characteristics of a population.
-challenging to conduct
and findings from survey research are not always easily interpreted.

Types of Survey Research

A sample survey is designed to sample participants and generalize to a population.
A census survey samples every member of the population.
Census surveys are generally done with small and accessible populations.

Survey Research Designs

-Cross-Sectional Surveys
-Longitudinal Surveys

Cross-Sectional Surveys

Example: A study that examines the self-concept of all pre-service teachers at a given university.
Data are collected from selected participants at a single point in time.
These studies provide a snapshot of current beliefs or opinions.
These survey studies are not intended to provide insight into trends or changes over time.

Longitudinal Surveys

Data are collected at two or more time points.
One of the challenges when conducting longitudinal studies is attrition

Several types of longitudinal survey designs.

-Trend studies
-Cohort studies
-Panel studies
-Follow-up studies

Trend studies

examine changes over time in a particular population defined by some trait.
e.g., entering kindergartners

Cohort studies

examine one population selected at a particular time period.
e.g., A researcher could study children that received speech and language support as first graders in 2007. She might examine some participants from the population in 2008 and then sample others from that population in 2010.

Panel studies

involve the same sample of individuals over a set time.
e.g., A researcher might conduct a five-year panel study of the first class of law students at a new institution. He might survey them each spring for five years.

Follow-up studies

investigate change in a previously studied population.
e.g., A researcher might be interested in a follow-up study in 2015 of those participants involved in the cohort study of first-graders in speech and language support during 2007.

Ways of Conducting Survey Research

-Questionnaires are a written collection of survey questions answered by a group of participants.
-Interviews are oral, in-person question and answer sessions between the researcher and a respondent.

Conducting a Questionnaire Study

-Stating the problem
Developing a questionnaire requires skill and time.
Researchers should plan content and format of the questionnaire.
Most surveys include one of two types of items.

Stating the problem in questionnaire study

Participants are more likely to respond to questionnaires that they perceive address a sufficiently relevant topic or problem.
Researchers should set objectives for the type of information desired from a questionnaire.

surveys include one of two types of items.

Structured items or closed-ended items for which participants choose among possible responses (e.g., Likert scale).
Unstructured items in which participants have freedom of response (e.g., fill-in answer).

Guidelines to consider when constructing a questionnaire

Include only items that relate to the objectives of the study.
Focus each question on a single concept.
Collect demographic information.
Define terms.
Include a point of reference or comparison for participants.
Avoid leading questions.
Avoid sensitive questions to which respondents might not answer honestly.
Don't ask a question that assumes something that may not be true.
Organize items from general to specific.
Have others read your instrument and provide feedback.
Write directions for the respondents.
Include the purpose of the study at the top of the instrument.
Pilot test the questionnaire.

Conducting a Questionnaire Study-Pilot testing the questionnaire

Pilot test with members of the intended sample population.
Ask respondents to make suggestions for any content to add or to delete.
Incorporate feedback from your pilot administration and make any appropriate changes.

Conducting a Questionnaire Study-Preparing the cover letter

Cover letters should accompany all surveys.
Cover letters should be brief.
Cover letters should be addressed to a specific person.
The cover letter should explain the purpose of the study.
The cover letter should include a statement regarding the importance and significance of the study.
The cover letter should include how results from the study will be shared with respondents and interested others.
Pilot test the cover letter.

Administering the Questionnaire

Selecting participants
Appropriate sampling strategies should be followed.
Distributing the questionnaire
Personal administration

Administering the Questionnaire-Mail

Can be confidential or anonymous
Standardized items and procedures
Easy to score most items
Response rate may be small
Cannot follow up items
Response sets possible
Limited to those who read

Administering the Questionnaire-E-Mail

Easy to target respondents
Quickly administered
Can be confidential or anonymous
Standardized items and procedures
Easy to score most items
Not everyone has email
Multiple replies from same participant possible
Response rate may be small
May get sorted to trash
Cannot follow up items
Response sets possible
Limited to those who read

Administering the Questionnaire-Telephone

High response rates
Quick data collection
Can reach a range of locations and respondents
Can use 800 call in numbers to increase response rates
Requires phone number lists
Difficult to get in-depth data
Administrators must be trained
Cell phones versus landlines

Administering the Questionnaire-Personal Administration

Efficient when respondents are in close proximity
Personal connection with respondents
Time consuming
Personal connection with respondents

Administering the Questionnaire-Interviews

Can follow-up responses and probe for additional information or clarity
May be recorded
Response rate
Personal connection with respondents
Time consuming
Interviewer bias possible
Unstructured data analysis
Personal connection with respondents

Conducting Follow-Up Activities

The higher the return rate the better your study.
Low response rates limit generalizability.
Send out a reminder postcard to increase response rates.
Send out a second complete mailing to increase response rates.
Consider phone-call reminders to increase response rates.
Response rates vary.
First mailings usually return about 30%-50%.
Second mailings add an additional 20%.
Most times additional mailings are not cost-effective.
Researchers should try to determine possible reasons for nonresponse.
Nonresponse may be at the survey or item level.
Researchers should carefully look for patterns of nonresponse.

Tabulating Questionnaire Responses

Use scannable answer sheets if possible.
Enter answers into spreadsheet or statistical package.
Code open-ended answers.
Consider available qualitative software analysis packages.

Analyzing Results

Report total sample size.
One way to report results from surveys is to share overall percentage of return and response rates per item.
e.g., Percentage that answered 'yes' and percentage that answered 'no'
Alternative reports can include total scores or mean scores by cluster or area of a survey. Such as comparisons by participant characteristics.
e.g., Percentage of men or women with a particular response.
Reports of survey studies will vary by the underlying purpose of the survey.

Correlational Research

-determine the nature of relations among variables or to use these relations to make predictions.
-often examine numerous variables believed to be related to complex variables (e.g., achievement).
Unrelated variables are discarded from future studies while those related may be examined further through causal-comparative or experimental studies.
High correlations among variables do not imply causation (e.g., self-concept and achievement).
Correlational procedures are also used to examine reliability and validity.

Correlational Research Process

Problem selection
Participant and instrument selection
Design and procedure
Data analysis and interpretation
Correlation coefficients

Correlational Research Process-Problem selection

Correlational studies are designed to explore whether and how variables are related.
Correlational studies are designed to test hypotheses regarding expected relations among variables.

Correlational Research Process-Participant and instrument selection

Samples are derived from acceptable sampling methods.
Sample must include at least 30 participants.
When reliability and validity of instrumentation is lower, sample size must be larger.

Correlational Research Process-Design and procedure

Correlational studies share a simple design. Scores for two or more variables of interest are obtained for each member of the sample and these scores are then correlated (e.g., self-concept and achievement).

Correlational Research Process-Data analysis and interpretation

The meaning of a correlation coefficient will vary depending upon purpose.
Sample size effects the strength of a correlation coefficient.
Some correlation coefficients that are statistically significant may not represent meaningful significance.
Correlation coefficients do not represent percentage of relation between variables.
The square of the correlation coefficient indicates the amount of variance shared by the variables (shared variance).
e.g., a correlation of .50 indicates 25% shared variance.

Correlational Research Process-Correlation coefficients

Correlation coefficients range from -1 to 1.
A correlation of 0 indicates no relationship.
Correlation coefficients between +.35 and -.35 represent a weak relationship or norelationship.
Correlation coefficients between +.35 and +.65 or between -.35 and -.65 represent moderaterelationships.
Correlation coefficients between .65 and 1.0 or between -.65 and -1.0 represent strongrelationships.

Relationship Studies

-gain insight into variables or factors that are related to a complex variable (e.g., retention, academic achievement).
-help researchers to determine which variables may be suitable for future research.
-provide insight into which variables should be controlled for in future causal-comparative or experimental studies.

Relationship Studies-Data collection

Researchers first identify variables to be correlated.
Variables should be purposely identified.
A smaller number of carefully identified variables is preferable to a larger number (e.g., shotgun approach).
After identifying variables the researcher next identifies the appropriate population and sampling procedure to select participants for the study.
In some relationship studies data are collected all at one time or in several sessions conducted in close succession.

Relationship Studies-Data analysis and interpretation

In relationship studies scores from one variable are correlated with scores for another variable; or scores for several variables are correlated with a particular variable of interest.
The result is a single correlation coefficient or a number of correlation coefficients.
The method of calculating a correlation coefficient depends upon the nature of the data.

Relationship Studies-Data analysis and interpretation
-Correlation coefficients

Correlation coefficients
The Pearson r coefficient is the most common and most precise coefficient. Pearson r is used for continuous variables.
The Spearman rho coefficient is appropriate to use when one of the variables are represented by rank-order data.
The phicoefficient is used when both variables are expressed as a categorical dichotomy.
Other correlation coefficients are appropriate given characteristics of the data collected, sample size, and underlying data distribution.
e.g., Kendall's tau, Biserial, Point biserial, Tetrachoric, Intraclass, eta.

Relationship Studies-Data analysis and interpretation-inaccurate estimates of relation among variables.

Several factors may contribute to inaccurate estimates of relation among variables.
Underlying relationships that are curvilinear will effect coefficients.
Attenuation occurs when measures have low reliability and may provide inaccurate correlation coefficients.
Restricted range in scores generally leads to underestimates of relations.

Prediction Studies

When two variables are highly related, scores on one variable can be used to predict scores on the other variable.
The variable used to predict is called the predictor.
The variable that is predicted is called the criterion.
*used to determine which variables are the most highly correlated with a criterion variable.
More than one variable can be used to make predictions.

Prediction Studies-Data collection

In prediction studies all measures should be valid measures.
It is especially critical that the criterion variable be validly measured.
In prediction studies, sometimes the predictor variables are administered prior to the criterion variable (e.g., SAT and university GPA).
Attrition is a problem in some prediction studies.
Shrinkage, or the tendency to find less accuracy in predicting criterion variables in subsequent samples, is often noted in prediction studies.
Cross-validation is the process of conducting subsequent prediction studies with new samples to verify effects found in an initial prediction study


-The action or process of gradually reducing the strength or effectiveness of someone or something through sustained attack or pressure.
-a reduction or decrease in numbers, size, or strength

Prediction Studies-Data analysis and interpretation

In prediction studies, data analysis involves correlating predictor variables with the criterion variable.
Multiple regression is used when a combination of variables is used to predict a criterion variable (e.g., Success in Algebra may be predicted by prior knowledge, prior achievement, aptitude, etc.)
Intervening variables may lower prediction accuracy (e.g., teacher).
The amount of common variance shared by predictors is the squared correlation of the predictors and the criterion and is referred to as the coefficient of determination.

Prediction Studies-Data analysis and interpretation-single variable prediction equation

Y= a+bX
Y= Predicted criterion score for an individual
X= An individual's score on the predictor variable
a= A constant calculated from scores of all participants
b= A coefficient that indicates the contribution of the predictor variable to the criterion variable

Other Correlation-Based Analyses

In discriminate function analysis, continuous variables are used to predict a categorical variable.
Canonical analysis produces a correlation based upon a group of predictor variables and a group of criterion variables.
Path analysis provides a diagram that illustrates how variables are related to one another.
Structural equation modeling, or LISREL, extends path analysis and predicts relations among variables with added precision.
Factor analysis is used to decrease the number of variables under consideration by grouping variables into clusters called factors.

Interpreting Correlation Coefficients

Was the proper correlation method used?
Do the variables have high reliabilities? Low reliabilities lower the chance of finding significant relations.
Is the validity of the variables strong? Invalid variables produce meaningless results.
Is the range of scores to be correlated restricted or extended? Narrow or restricted score ranges lower correlation coefficients, whereas broad or extended score ranges raise them.
How large is the sample? The larger the sample the smaller the value needed to reach statistical significance. Large samples may yield correlations that are statistically significant but practically unimportant.

Causal-Comparative Research

-researcher attempts to determine the cause or reason for existing differences in groups or individuals.
-Retrospective casual-comparative research studies start with effects and investigate causes
-Prospective casual-comparative research studies start with the causes and investigate the effects.
-does not establish cause-effect relations.
-generally includes more than two groups and at least one dependent variable.
-the independent variable is not manipulated by the researcher.

Causal-Comparative Research

-can be conducted when variables cannot or should not be experimentally manipulated.
-can facilitate decision making.
-provide insight into conducted or potential experimental studies.
-generally less costly than are experimental studies.

Causal-Comparative Research-Ex of retrospective causes and investigate the effects..

More common in educational research.
e.g., A researcher interested in the benefits of an exercise program on reducing stress may select a group of people who had enrolled in a stress-reduction exercise class and those who had not and compares their stress levels.

Causal-Comparative Research-Ex of prospective causes and investigate the effects.

What is the effect of X?
e.g., A researcher may hypothesize that those children that attend dance classes during elementary school have higher self-esteem when in middle school. She would identify a group of middle-school children who had dance classes in elementary school and a group of those who did not, and compare their self-esteem.

Causal-Comparative Research-independent variable is not manipulated

The independent variable has occurred or is already formed.
Independent variable in causal-comparative studies is often referred to as the grouping variable.

Examples of variables investigated in Causal-comparative studies:

Organismic variables (e.g., age, ethnicity, sex)
Ability variables (e.g., achievement)
Personality variables (e.g., self-concept)
Family-related variables (e.g., SES)
School-related variables(e.g., type of school, size of school)

Causal-Comparative Research Example

Ethnicity, birth order, spatial ability, teacher education level, goal orientation
Ethnicity (organismic), birth order (family-related), spatial ability (ability), teacher education level (school-related), goal orientation (personality)

Limitations of causal-comparative research.

The experimenter has limited control.
Caution in interpretation is necessary as cause-effect relations cannot be established.
Only relations are established.

Conducting a Causal-Comparative Study

The basic causal-comparative design involves selecting two groups that differ on a variable of interest and comparing them on a dependent variable.
Definition and selection of comparison groups is critical in causal-comparative research.
Grouping variables must be operationally defined (e.g., training versus no training).
Researchers should test for differences between groups (e.g., prior knowledge).
Basic causal-comparative designs
There are several control procedures that researchers can employ to strengthen their causal-comparative designs.

Conducting a Causal-Comparative Study-test for differences between groups

The more similar the groups are on extraneous variables, the fewer alternative explanations there may be for research findings.

Conducting a Causal-Comparative Study-Basic causal-comparative designs

In one design: One group is exposed to an independent variable while the other group is not. Both groups are measured on a dependent variable.
(E) (X) O
(C) O
In a second design: Two groups are exposed to different independent conditions. Both groups are then measured on a dependent variable.
(E) (X1) O
(C) (X2) O

Conducting a Causal-Comparative Study-control procedures that researchers can employ to strengthen their designs.

Matching: Researchers can attempt to equate groups and control for one or more variables.
For example, a researcher comparing two types of instruction might control for prior achievement. To do this, he would do pair-wise matching and would place an equal number of high achieving students in each condition.
Comparing homogeneous groups or subgroups: Researchers can also compare groups that are homogeneous with respect to an extraneous variable.
For example, the researcher may select only high-achieving students for his study.
Analysis of Covariance (ANCOVA): Researchers can use this statistical technique to adjust scores on a dependent variable for initial differences on a related variable.
For example, the researcher could measure prior knowledge and use those scores as a covariate.

Conducting a Causal-Comparative Study
-Data analysis and interpretation

Descriptive and inferential statistics are used to analyze data from causal-comparative studies.

Conducting a Causal-Comparative Study-
Descriptive and inferential statistics

Descriptive statistics often include the mean and the standard deviation.
Inferential tests used include t-tests, analyses of variance, and chi square.

Experimental Research

-the only type of research that can test hypotheses to establish cause-effect relations.
In experimental research studies the independent variable is also called the treatment, causal, or experimental variable.
In experimental research studies the dependent variable is also called the criterion, effect, or posttest variable

Experimental Research

-the most structured of all research.
-can provide evidence for cause-effect relations.
-Several experimental studies taken together can provide support for generalization of results.

Experimental Research-test hypotheses to establish cause-effect relations

The researcher manipulates at least one independent variable and controls other relevant variables, and observes the effect on one or more dependent variables.
The researcher manipulates the treatment.
The researcher has control over selection and assignment.

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