EXPERIMENTS

© LOUIS COHEN, LAWRENCE MANION & KEITH MORRISON

STRUCTURE OF THE CHAPTER

• Designs in educational experimentation• True experimental designs• A quasi-experimental design: the non-equivalent

control group design• Single-case research: ABAB design• Procedures in conducting experimental research• Threats to internal and external validity in

experiments• The timing of the pretest and the post-test• Examples from educational research• The design experiment• Internet-based experiments

CAUSALITY

• Experiments are held up to be able to identify causality through control and manipulation of variables.

• Examine the effect of an independent variable on a dependent variable.

• Identifying the effects of causes by implementing interventions in a controlled environment.

• Held up to be able to offer explanations for outcomes.

INDEPENDENT AND DEPENDENT VARIABLES

Developmentplanning

School Effectiveness

Parents and

community

Teaching andlearning

Professionaldevelopment

Management LeadershipCulture and

climate

RANDOMIZATION

• Random sampling and random allocation to either a control or experimental group.

• Randomization allows for the many additional uncontrolled and, hence, unmeasured, variables that may be part of the make-up of the groups in question.

• Randomization operates the ceteris paribus condition (all other things being equal), assuming that the distribution of extraneous variables is more or less even and perhaps of little significance.

• Randomization strives to address Holland’s (1986) ‘fundamental problem of causal inference’, which is that a person may not be in both a control group and an experimental group simultaneously.

CONCERNS IN EXPERIMENTS

• It may not be possible or desirable to isolate and control variables under laboratory conditions.

• The ‘real world’ is not the antiseptic, artificial world of the laboratory.

• Cannot assume that a single cause produces a single effect.

• The setting affects the outcomes.

BLIND AND DOUBLE-BLIND EXPERIMENTS

• Blind experiment: participants do not know to which group they are assigned.

• Double blind experiment: neither the researcher nor the participants know to which group the participants are assigned.

KINDS OF EXPERIMENT• Laboratory experiments (controlled, artificial conditions):

– Pretest-post-test control and experimental group– Two control groups and one experimental group pretest-post-test– Post-test control and experimental group– Post-test two experimental groups– Pretest-post-test two treatment– Matched pairs;– Factorial design;– Parametric design;– Repeated measures design;

• Field experiments (controlled conditions in the ‘real world’): – one-group pretest-post-test; – non-equivalent control group design;– time series

• Natural experiments (no control over real world conditions)

FEATURES OF A TRUE EXPERIMENT• Random allocation of the sample to control or

experimental groups;• Identification and isolation of key variables;• Control of the key variables;• Exclusion of any other variables;• Special treatment (the intervention) given to the

experimental group (i.e. manipulating the independent variable) whilst holding every other variable constant for the two groups;

• Ensuring that the two groups are entirely separate throughout the experiment (non-contamination);

• Final measurement of outcomes to compare the control and experimental groups and to look at differences from the pre-test results (the post-test);

• Comparison of one group with another.

Randomly assign subjects to two matched groups:

control and experimental group

Conduct pre-test

Isolate and control variables, exclude other variables

Administer intervention to experimental group

Conduct post-test and compare control and experimental groups

Stages in an experiment

‘TRUE’ EXPERIMENTAL DESIGN

CONTROL CONTROL

EXPERIMENT EXPERIMENTIntervention

Matched on Pre-test

Random group assignation

Isolate, control and manipulatevariables

Post-test

PLUS

MEASURING EFFECTS

Average causal effect (A):(A) = (E1E2) (C1C2)

where: – E1 = post-test for experimental group; – E2 = pretest for experimental group; – C1 = post-test for control group; – C2 = pretest for control group.

CAMPBELL’S AND STANLEY’S NOTATION

• X represents the exposure of a group to an experimental variable or event, the effects of which are to be measured.

• O refers to the process of observation or measurement.• Xs and Os in a given row are applied to the same

persons.• Left to right order indicates temporal sequence.• Xs and Os vertical to one another are simultaneous.• R indicates random assignment to separate treatment

groups.• Parallel rows unseparated by dashes represent

comparison groups equated by randomization, while those separated by a dashed line represent groups not equated by random assignment.

CAMPBELL’S AND STANLEY’S SYMBOLIC REPRESENTATION OF

‘TRUE’ EXPERIMENTS

RO1 X O2

RO3 O4

Campbell, D. T. and Stanley, J (1963) Experimental and Quasi-experimental Designs for Research on Teaching. Boston: Houghton Mifflin Co.

TWO CONTROL GROUPS AND ONE EXPERIMENTAL GROUP PRETEST-

POST-TEST DESIGN

Experimental RO1 X RO2

Control1 RO3 RO4

Control2 X RO5

THE POST-TEST CONTROL AND EXPERIMENTAL GROUP DESIGN

Experimental R1 XO1

Control R 2

O2

THE POST-TEST TWO EXPERIMENTAL GROUPS DESIGN

Experimental1 R1 X1 O1

Experimental2 R2 X2 O2

THE PRETEST―POST-TEST TWO TREATMENT DESIGN

Experimental1 RO1 X1 O1

Experimental2 RO3 X2 O4

THE TRUE EXPERIMENT ONE CONTROL AND TWO EXPERIMENTAL

GROUPS

Experimental1 RO1 X1 O1

Experimental2 RO3 X2 O4

Control RO5

O6

THE PRE-TEST TWO TREATMENT DESIGN

Experimental1 RO1 X1 O1

Experimental2 RO3 X2 O4

MATCHED PAIRS DESIGNStep One: Measure the dependent variable.Step Two: Assign participants to matched pairs, based on the scores and measures established from Step One.Step Three: Randomly assign one person from each pair to the control group and the other to the experimental group.Step Four: Administer the intervention to the experimental group and, if appropriate, a placebo to the control group. Ensure that the control group is not subject to the intervention.Step Five: Carry out a measure of the dependent variable with both groups and compare/measure them in order to determine the effect and its size on the dependent variable.

INDEPENDENT

VARIABLE

LEVELONE

LEVELTWO

LEVELTHREE

Availability of resources

limited availability (1)

moderate availability (2)

high availability (3)

motivation for the subject studied

little motivation (4)

moderate motivation (5)

high motivation (6)

FACTORIAL DESIGN Performance in an examination may depend on availability of

resources and motivation for the subject studied

9 combinations: 1+4; 1+5; 1+6; 2+4; 2+5; 2+6; 3+4; 3+5; 3+6

0

20

40

60

80

100

15 16 17 18

Age

Mo

tiv

ati

on

fo

r m

ath

em

ati

cs

Males

Females

Difference for motivation in mathematics is not constant between males and females, but varies according to age of participants: an interaction effect (age and sex)

Factorial designs must address the interaction of the independent variables.

PARAMETRIC DESIGN

• Participants are randomly assigned to groups whose parameters are fixed in terms of the levels of the independent variable that each receives.

• Parametric designs are useful if an independent variable has different levels or a range of values which may have a bearing on the outcome (confirmatory research) or if the researcher wishes to discover whether different levels of an independent variable have an effect on the outcome (exploratory research).

REPEATED MEASURES

• Participants in the experimental groups are tested under two or more experimental conditions.

• The order in which the interventions are sequenced may have an effect on the outcome (e.g. the first intervention may have an influence – a carry-over effect – on the second, and the second intervention may have an influence on the third).

• Early interventions may have a greater effect than later interventions.

• Repeated measures designs are useful if it is considered that order effects are either unimportant or unlikely.

REPEATED MEASURES(two groups receiving both conditions)

Group 1With no

intervention

Matched on pre-test

Random allocation to groups

Group 2With

intervention

Group 2With no

intervention

Post-test

Group 1With

intervention

Independent groups

Noise condition No noise condition

Sara Rob Peter

Jane Jack Jim

Joan Susan John

Lyn Sally Alan

Repeated measures

Noise condition No noise condition

Sara Rob Peter

Jane Jack Jim

Joan Susan John

Lyn Sally Alan

Jane Jack Jim

Sara Rob Peter

Lyn Sally Alan

Joan Susan John

QUASI-EXPERIMENTS: NON-EQUIVALENT CONTROL GROUP

DESIGN• Pre-experimental design: the one-group

pretest―post-testExperimental O1 X O2

• Pre-experimental design: the one-group post-test only design

Experimental O1

• The Post-Tests only non-equivalent groups design

Experimental O1

- - - - - - - - - - Control O2

QUASI-EXPERIMENTS: NON-EQUIVALENT CONTROL GROUP

DESIGN• The pre-test―post-test non-equivalent

group design

Experimental O1 X O2

- - - - - - - - - -

Control O3 O4

PROCEDURES IN CONDUCTING EXPERIMENTS

1. Identify research problems2. Formulate hypotheses3. Select appropriate levels at which to test the

independent variables 4. Decide which kind of experiment to adopt 5. Decide population and sampling6. Select instruments for measurement7. Decide how the data will be analyzed8. Pilot experimental procedures9. Carry out the refined procedures10.Analyze results11.Report the results

A TEN-STEP MODEL FOR CONDUCTING EXPERIMENTS

Step One: Identify the purpose of the experiment.Step Two: Select the relevant variables.Step Three: Specify the level(s) of the intervention

(e.g. low, medium high intervention).Step Four: Control the experimental conditions and

environment.Step Five: Select appropriate experimental design.Step Six: Administer the pretest.Step Seven: Assign the participants to the group(s).Step Eight: Conduct the intervention.Step Nine: Conduct the post-test.Step Ten: Analyze the results.

PROCEDURES IN CONDUCTING EXPERIMENTS: HYPOTHESES

• Null hypothesis (H1)• Alternative hypothesis (H0)• Direction of hypothesis: states the kind of

difference or relationship between two conditions or two groups of participants

• One-tailed (directional): e.g. ‘people who study in silent surroundings achieve better than those who study in noisy surroundings’

• Two-tailed (no direction): e.g. ‘there is a difference between people who study in silent surroundings and those who study in noisy surroundings’

OPERATIONALIZING HYPOTHESES

• Hypothesis: ‘people who study in quiet surroundings achieve better than those who study in noisy surroundings’

• What do ‘work better’, ‘quiet’ and ‘noisy’ mean? Define the operations:– ‘work better’ = obtain a higher score on the

Wechsler Adult Intelligence Scale – ‘quiet’ = silence– ‘noisy’ = CD music playing

• Operationalized hypothesis: ‘people who study in silence achieve a higher score on the Wechsler Adult Intelligence Scale than those who study with CD music playing’

DIRECTIONAL AND NON-DIRECTIONAL HYPOTHESES

Directional (one-tailed):

People who do homework without the TV on produce better results than those who do homework with the TV on.

Non-directional (two-tailed):

There is a difference between work produced in noisy or silent conditions.

DIRECTION OF CAUSALITY

MATURATION TESTING

THREATS TO VALIDITY AND

RELIABILITY

TYPE 1 AND TYPE 2

ERRORS

INSTRUMENT-ATION

OPERATIONAL-IZATION

REACTIVITY

HISTORY

EXPERIMENTAL MORTALITY

CONTAMIN-ATION

TIMING OF PRE-TEST AND POST-TEST

• Pre-test: as close to the start of the experiment as possible (to avoid contamination of other variables).

• Post-test: as close to the end of the intervention as possible.

• Too soon a post-test: misses long-term/delayed effect and only measures short-term gain (which may be lost later).

• Too long a time lapse before a post-test: becomes impossible to determine whether it was a particular independent variable that caused a particular effect, or whether other factors have intervened since the intervention, to produce the effect.

INTERNET-BASED EXPERIMENTS

Four types: 1. Those that present static printed materials

(e.g. printed text or graphics)2. Those that make use of non-printed

materials (e.g. video or sound)3. Reaction-time experiments4. Experiments that involve some form of

interpersonal interaction

INTERNET-BASED EXPERIMENTS

• Check download speeds and time, anticipate problems of different browsers and platforms.

• Can experience greater problems of dropout than conventional experiments.