Cs comp&experiemental2011 12

Educational Research: Causal-Comparative & Experimental Studies ELT-718 Research Methods Asst. Prof. Dr. Hasan BEDİR

Research... The systematic application of a family of methods employed to provide trustworthy information about problems … an ongoing process based on many accumulated understandings and explanations that, when taken together lead to generalizations about problems and the development of theories

The basic steps of research... Scientific and disciplined inquiry is an orderly process, involving:  description and execution of procedures to collection information (“ method ”)  objective data analysis  statement of findings (“ results ”)  recognition and identification of a topic to be studied (“ problem ”)

Research methods... Quantitative … … collects and analyzes numerical data obtained from formal instruments

Quantitative methods... descriptive research (“survey research”) correlational research causal-comparative research (“ ex post facto research”) experimental research

Research Methodologies A continuum rather than “either/or” Qualitative Goal: To Understand, Predict Descriptive accounts Similarities and Contrasts Applied and Theoretical Research Questions Field study Natural conditions Quantitative Goal: To Predict and Control Measure and Evaluate Generalize to population, reproduction Basic and Theoretical Hypothesis testing Emprical study Controlled, contrived

Data Collection Quantitative Emphasis on numerical data, measurable variables Data is collected under controlled conditions in order to rule out the possibility that variables other than the one under study can account for the relationships identified Qualitative Emphasis on observation and interpretation. Data are collected within the context of their natural occurrence.

Causal-Comparative Research The Purpose Purpose of explaining educational phenomena through the study of cause-and-effect relationships. The presumed cause is called the independent variable and the presumed effect is called the dependent variable . Designs where the researcher does not manipulate the independent variable are called ex post facto research .

Causal-Comparative Research ( Continued ) Causal-Comparative research is also a type of non-experimental investigation in which researchers seek to identify cause-effect relationships by forming groups of individuals in whom the independent variable is present or absent and than determining whether the groups differ on the dependent variable.

causal-comparative research (“ ex post facto research”) … at least two different groups are compared on a dependent variable or measure of performance (called the “effect”) because the independent variable (called the “cause”) has already occurred or cannot be manipulated

Research variables... Independent … … an activity of characteristic believed to make a difference with respect to some behavior … (syn.) experimental variable, cause, treatment

dependent variable … … the change or difference occurring as a result of the independent variable … (syn.) criterion variable, effect, outcome, posttest

Data analysis and interpretation… … researcher uses a variety of descriptive and inferential statistics : mean standard deviation t-test analysis of variance chi squared

mean … the descriptive statistic indicating the average performance of an individual or group on a measure of some variable

standard deviation … the descriptive statistic indicating the spread of a set of scores around the mean

t-test … the inferential statistic indicating whether the means of two groups are significantly different from one another

analysis of variance (“ANOVA”) … the inferential statistic indicating the presence of a significant difference among the means of three or more groups

chi squared ( Χ 2 ) … the inferential statistic indicating that there is a greater than expected difference among group frequencies

Research Design s “ True” Experimental Design : The Researcher actually manipulates the independent variable Non-Experimental Design: Passive Observation by Researcher Quasi-Experimental Design: Assignments to experimental conditions are not random

Experimental Designs Experimental research design: The researcher has control over the experiment in terms of sample selection, treatment, environment, etc. Experimental designs are typical in psychology, medicine, education, etc.

Experimental Designs Experiments often discuss pre and post test observations POST-TEST ONLY X O 1 Where: 0 t = Observation in time t of experimental group X = Treatment 0 c = Control group

experimental research … the researcher selects participants and divides them into two or more groups having similar characteristics and, then, applies the treatment(s) to the groups and measures the effects upon the groups

Types of experimental comparison… 1. comparison of two different approaches ( A versus B ) 2. comparison of an existing approach to a new approach ( A and ~ A ) 3. comparison of differing amounts of a single approach ( A and a or a and A )

where: A – experimental (“treatment”) group B – control (“no treatment,” “nonmanipulated”) group

Group experimental designs… 1. single-variable 2. factorial

types of pre-experimental designs one-shot case study X O … a single group exposed to a treatment ( X ) and then posttested ( O )

one-group pretest-posttest design O X O … a single group is pretested ( O ), exposed to a treatment ( X ) and, then, is posttested ( O )

static group comparison X 1 O X 2 O … involves at least two groups ( X ), one receiving a new, or experimental treatment ( X 1 ) and another receiving a traditional, or control treatment ( X 2 ) and, then, are posttested ( O )

“ True” experiments defined An experiment that utilizes random assignment to conditions in an effort to ensure that the participants in each condition are statistically identical. In doing so, any differences observed in the dependent variable are attributable only to the presence/absence of the independent variable. Campbell & Stanley’s taxonomy RO 1 X O 2 RO 3 O 4 where R = random assignment, O = observation, X = treatment

types of true experimental designs pretest-posttest control group design R O X 1 O R O X 2 O

… at least two groups are formed by random assignment ( R ), administered a pretest ( O ), receive different treatments ( X 1 , X 2 ), are administered a posttest, and posttest scores are compared to determine effectiveness of treatments

posttest-only control group design R X 1 O R X 2 O

… at least two groups are formed by random assignment ( R ), receive different treatments ( X 1 , X 2 ), are administered a posttest, and posttest scores are compared to determine effectiveness of treatments

Solomon four-group design R O X 1 O R O X 2 O R X 1 O R X 2 O

… four groups are formed by random assignment ( R ) of participants, two groups are pretested ( O ) and two are not, one pretested and one unpretested group receive the experimental treatments ( X 1 , X 2 ), each group is are administered a posttest on the dependent variable, and posttest scores are compared to determine effectiveness of treatments

factorial designs … involve two or more independent variables with at least one independent variable being manipulated by the researcher

Experimental Design Factorial Design Diagram Independent Variable #1: Teaching Method Independent Variable #2: Aptitude Randomly assigned 3 rd graders scoring below 60 on an aptitude test. Randomly assigned 3 rd graders scoring below 60 on an aptitude test. Randomly assigned 3 rd graders scoring about 85 on an aptitude test. Randomly assigned 3 rd graders scoring above 85 on an aptitude test. Reading/Lecture/Etc. Lecture Only High Low

Independent Variable #1 Teaching Method How many possible Teaching Methods are there? Which will be the methods used in the study? If more than one will be used, each method may be considered a factor of the variable known as Teaching Method. Teaching Method Lecture only Lecture & Small Group Discussion

Independent Variable #2 Aptitude How many possible levels of aptitude are there? How many may be represented in the group of subjects participating in the study? Once identified, levels of aptitude may be considered factors of the variable known as Aptitude. Low High Aptitude

Lecture only Lecture & Small Group Discussion Low High

examples of factorial designs two-by-two factorial design (four cells) 2 X 2 … two types of factors (e.g., method of instruction) each of which has two levels (e.g., traditional vs. innovative)

A 2 X 2 factorial design… Independent Variable A B Dependent Variable O O Group #1 Group #2 Group #3 Group #4 Cells not manipulated manipulated

A 2 X 2 factorial design… A No interaction between factors B

A 2 X 2 factorial design… A Interacting factors B

two-by-three factorial design (six cells) 2 X 3 … two types of factors (e.g., motivation; interest) each of which has three levels (e.g., high, medium, low)

Single-subject experimental designs… 1. A – B – A withdrawal 2. multiple baseline designs 3. alternating treatments designs

simple A – B design … baseline measurements ( O ) are repeatedly made until stability is established, then the treatment ( X ) is introduced and an appropriate number of measurements ( O ) are made during treatment implementation

simple A – B design O O O X O X O X O baseline treatment phase phase A | B

A – B – A withdrawal designs … baseline measurements ( O ) are repeatedly made until stability is established, then the treatment ( X ) is introduced and an appropriate number of measurements ( O ) are made during treatment implementation, followed by an appropriate number of baseline measurements ( O ) to determine stability of treatment ( X )

A – B – A withdrawal designs O O O X O X O X O O O baseline treatment baseline phase phase phase A | B | A

multiple-baseline designs … used when a return to baseline conditions is difficult or impossible since treatment effects oftentimes do not disappear when a treatment is removed

…“ multiple” refers to the study of more than one behavior, participant, or setting

… instead of collecting baseline data on one specific behavior, data are collected on: (1) several behaviors for one participant, (2) one behavior for several participants, or (3) one behavior and one participant in several settings

… then, over a period of time, the treatment is systematically applied to each behavior (or participant, or setting) one at a time until all behaviors (or participants or settings) have been exposed to the treatment

multiple baseline design Example: one treatment for three behaviors in three settings behavior 1 O O OXOXOXOXOXOXOXOXOXOXOXO setting #1 behavior 2 O O O O O OXOXOXOXOXOXOXO setting #2 behavior 3 O O O O O O O O OXOXOXO setting #3 A B the baseline remains the same… … while the treatment is applied at other settings

Threats to validity… … internal : factors other than the independent variable that affect the dependent variable … external : factors that affect the generalizability of the study to groups and settings beyond those of the experiment

Threats to internal validity… 1. history 2. maturation 3. testing 4. instrumentation 5. statistical regression 6. differential selection of participants 7. mortality 8. selection-maturation interaction

history … the occurrence of events that are not part of the experimental treatment but that occur during the study and affect the dependent variable

maturation … the physical, intellectual, and emotional changes that occur naturally in a study’s participants over a period of time

testing … refers to improved scores on a posttest as a result of having taken a pretest

instrumentation … the unreliability or lack of consistency in measuring instruments that can result in an invalid assessment of performance

statistical regression … the tendency of participants who score highest on a test to score lower on a second, similar test and vice versa

differential selection of participants … the outcome when already formed groups are compared raising the possibility that the groups were different before a study even begins

mortality … the case in which participants drop out of a study which changes the characteristics of the groups and may significantly affect the study’s results

selection-maturation interaction … if already-formed groups are used in a study, one group may profit more (or less) from a treatment or have an initial advantage because of maturation, history, or testing factors

Threats to external validity… 1. pretest-treatment interaction 2. selection-treatment interaction 3. multiple treatment interference 4. specificity of variables 5. treatment diffusion 6. experimenter effects 7. reactive effects

pretest-treatment interaction … the situation when participants respond or react differently to a treatment because they have been pretested

multiple-treatment interference … the situation when the same participants receive more than one treatment in succession

selection-treatment interference … the situation when participants are not randomly selected for treatments

specificity of variables … the situation when a study is conducted with (1) a specific kind of participant; (2) is based on a particular operational definition of the independent variable; (3) uses specific dependent variables; (4) transpires at a specific time; and, (5) under a specific set of circumstances

treatment diffusion … the situation when different treatment groups communicate with and learn from each other

experimenter effects … the situation when the researchers present potential threats to the external validity of their own studies

reactive arrangements … the situation when a number of factors associated with the way in which a study is conducted interacts with or shapes the feelings and attitudes of the participants involved

Types of reactive arrangements… … Hawthorne effect : any situation in which participants’ behavior is affected not by the treatment per se but by their knowledge of participating in a study … compensatory rivalry : the control group is informed that they will be the control group for a new, experimental study (“ John Henry effect ”)

… placebo effect : the situation in which half of the participants receive no treatment but believe they are … novelty effect : the situation in which participant interest, motivation, or engagement increases simply because they are doing something different

Controlling for extraneous (confounding) variables… 1. randomization 2. matching 3. comparing homogeneous groups or subgroups 4. using participants as their own controls 5. analysis of covariance (ANCOVA)

randomization … the process of selecting and assigning participants in such a way that all individuals in the defined population have an equal and independent chance of being selected for the sample

matching … a technique for equating groups on one or more variables, usually the ones highly related to performance on the dependent variable (e.g., pairwise matching)

comparing homogeneous groups or subgroups … a technique to control an extraneous variable by comparing groups that are similar with respect to that variable (e.g., stratified sampling)

using participants as their own controls … exposing a single group to different treatments one treatment at a time

Data analysis and interpretation… for single-subject research … a visual inspection and analysis of graphical presentations of results … focuses upon: adequacy of the design; an assessment of treatment effectiveness ( clinical vs. statistical significance )

Mini-Quiz… True and false… … causal-comparative studies attempt to identify the cause-effect relationships; correlational studies do not True

… causal-comparative studies typically involve two (or more) groups and one independent variable, whereas correlational studies typically involve two (or more) variables and one group True

… causal-comparative studies involve relation, whereas correlational studies involve cause False

… oftentimes, causal-comparative research is undertaken because the independent variable could be manipulated but should not True

… one of the most important reasons for conducting causal-comparative research is to identify variables worthy of experimental investigation True

…“ lack of control” means that the researcher can and should manipulate the independent variable False

… each group in a causal-comparative study represents a different population True

… the more similar two groups are on all relevant variables except the independent variable, the stronger the study is True

… there is random assignment to treatment groups from a single population in causal-comparative studies False

… lack of randomization, manipulation of the independent variable, and control are all sources of weakness in a causal-comparative design True

… matching, comparing homogenous groups or subgroups, and covariate analysis are strategies that enable researchers to overcome problems of initial group differences on an extraneous variable True

… interpretation of the findings in a causal-comparative study requires considerable caution because the cause may be the effect and the effect may be the cause True

… extraneous variables or confounding factors may be the real “cause” of both the independent and dependent variables True

Fill in the blank… … groups selected for a causal-comparative study which differ on some independent variable and comparing them on some dependent variable comparison groups

Fill in the blank… … unexplained variables that influence a dependent variable confounding factors extraneous variables

Fill in the blank… … a method for controlling extraneous variables by comparing groups that are homogeneous with respect to the extraneous variable comparing homogeneous groups

Fill in the blank… … a method for controlling extraneous variables by forming subgroups within each group that represent all levels of the control variable comparing homogeneous subgroups

Fill in the blank… … a statistical tool to determine the effects of the independent variable and the control variable on the dependent variable, both separately and in combination factorial analysis of variance

Fill in the blank… … the descriptive statistic indicating the average performance of a group on a measure of some variable mean

Fill in the blank… … the descriptive statistic indicating how clustered or spread out around the mean a set of scores is standard deviation

Fill in the blank… … the inferential statistic determining whether there is a significant difference between the means of two groups t-test

Fill in the blank… … the inferential statistic determining whether there is a significant difference between the means of three or more groups analysis of variance

Fill in the blank… … the inferential statistic determining whether there is a greater than expected difference among group frequencies chi squared

Fill in the blank… … activities by which a researcher endeavors to ensure that the results of a causal-comparative study are not tainted by extraneous variables control

Cs comp&experiemental2011 12

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