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Explore validity, reliability, instrument classification, norm-referenced vs criterion-referenced instruments, and experimental research in quantitative methods.
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Part 2: Quantitative Methods October 9, 2006
Validity • Face • Does it appear to measure what it purports to measure? • Content • Do the items cover the domain? • Construct • Does it measure the unobservable attribute that it purports to measure?
Validity • Criterion • Predictive • Concurrent • Consequential
Types of validity (cont.) Here the instrument samples some and only of the construct
Types of validity Here the instrument samples all and more of the construct
The construct Here the instrument fails to sample ANY of the construct The instrument
The construct Here the instrument samples some but not all of the construct The instrument
In groups of 3 to 4 • Sampling • What is the target population? • What sampling procedure was used? • Do you think the sample is representative? • Why or why not? • Measurement • What types of reliability and validity evidence are provided? • What else would you like to know?
Ways to Classify Instruments • Who Provides the Information? • Themselves: Self-report data • Directly or indirectly: from the subjects of the study • From informants (people who are knowledgeable about the subjects and provide this information)
Rating scales Interview schedules Tally sheets Flowcharts Performance checklists Observation forms Types of Researcher-completed Instruments
Excerpt from a Behavior Rating Scale for Teachers Instructions: For each of the behaviors listed below, circle the appropriate number, using the following key: 5 = Excellent, 4 = Above Average, 3 = Average, 2 = Below Average, 1 = Poor. A. Explains course material clearly. 1 2 3 4 5 B. Establishes rapport with students. 1 2 3 4 5 C. Asks high-level questions. 1 2 3 4 5 D. Varies class activities. 1 2 3 4 5
Excerpt from a Graphic Rating Scale Instructions: Indicate the quality of the student’s participation in the following class activities by placing an X anywhere along each line. Always Frequently Occasionally Seldom Never 1. Listens to teacher’s instructions. Always Frequently Occasionally Seldom Never 2. Listens to the opinions of other students. Always Frequently Occasionally Seldom Never 3. Offers own opinions in class discussions.
Questionnaires Self-checklists Attitude scales Personality inventories Achievement/aptitude tests Performance tests Projective devices Types of Subject-completed Instruments
Item Formats • Questions used in a subject-completed instrument can take many forms but are classified as either selection or supply items. • Examples of selection items are: • True-false items • Matching items • Multiple choice items • Interpretive exercises • Examples of supply items are: • Short answer items • Essay questions
Norm-Referenced vs. Criterion-Referenced Instruments • All derived scores give meaning to individual scores by comparing them to the scores of a group. • The group used to determine derived scores is called the norm group and the instruments that provide such scores are referred to as norm-referenced instruments. • An alternative to the use of achievement or performance instruments is to use a criterion-referenced test. • This is based on a specific goal or target (criterion) for each learner to achieve. • The difference between the two tests is that the criterion referenced tests focus more directly on instruction.
The (Never-Ending) Search for Causation • Establishing causation among variables : • Produces increased understanding of those variables • Results in the ability to manipulate conditions in order to produce desired changes
Experimental Research • Can demonstrate cause-and-effect very convincingly • Very stringent research design requirements • Experimental design requires: • Random assignment to groups (experimental and control) • Independent treatment variable that can be applied to the experimental group • Dependent variable that can be measured in all groups
Quasi-Experimental Research • Used in place of experimental research when random assignment to groups is not feasible • Otherwise, very similar to true experimental research
Fundamentals of Experimental and Quasi-Experimental Research • Cause and effect: • Incorporates a temporal element—the cause is a condition that exists prior to the effect; effect is a condition that occurs after the cause • There exists a “logical connection”—cause-and-effect is demonstrated when manipulation of the independent variable results in differences in the dependent variable (as evidenced by comparing the experimental group to the control group)
What Aids Our Causal Arguments? • Theory • "causes certainly are connected to effects; but this is because our theories connect them, not because the world is held together by cosmic glue. The world may be glued together by imponderables, but that is irrelevant for understanding causal explanation." Hanson, 1958. • Temporal Elements • Design • "No causation without manipulation" Rubin & Holland
Fundamentals of Experimental and Quasi-Experimental Research • Random selection and random assignment : • Distinguish between “selection” and “assignment” • Random selection helps to assure population validity • If you incorporate random assignment Experimental research • If you do not use random assignment Quasi-experimental research
Fundamentals of Experimental and Quasi-Experimental Research (cont’d.) • When to use experimental research design : • If you strongly suspect a cause-and-effect relationship exists between two conditions, and • The independent variable can be introduced to participants and can be manipulated, and • The resulting dependent variable can be measured for all participants
Internal and External Validity • “Validity of research” refers to the degree to which the conclusions are accurate and generalizable • Both experimental and quasi-experimental research are subject to threats to validity • If threats are not controlled for, they may introduce error into the study, which will lead to misleading conclusions
Threats to External Validity • External validity—extent to which the results can be generalized to other groups or settings • Population validity—degree of similarity among sample used, population from which it came, and target population • Ecological validity—physical or emotional situation or setting that may have been unique to the experiment • If the treatment effects can be obtained only under a limited set of conditions or only by the original researcher the findings have low ecological validity.
Threats to External Validity • Selection bias • if sample is biased you cannot generalize to the population. • Reactive effects • Experimental setting - differs from natural setting. • Testing – pretest influences how subjects respond to the treatment. • Multiple-treatment inference • If the subjects are exposed to more than one treatment, then the findings could only be generalized to individuals exposed to the same treatments in the same order of presentation.
Threats to Internal Validity • Internal validity—extent to which differences on the dependent variable are a direct result of the manipulation of the independent variable • History—when factors other than treatment can exert influence over the results; problematic over time • Maturation—when changes occur in dependent variable that may be due to natural developmental changes; problematic over time • Testing—pretest may give clues to treatment or posttest and may result in improved posttest scores • Instrumentation – Nature of outcome measure has changed.
Threats to Internal Validity (cont’d.) • Regression – Tendency of extreme scores to be nearer to the mean at retest • Differential selection of participants—participants are not selected/assigned randomly • Attrition (mortality)—loss of participants • Experimental treatment diffusion – Control conditions receive experimental treatment.
Experimental and Quasi-Experimental Research Designs • Commonly used experimental design notation : • X1 = treatment group • X2 = control/comparison group • O = observation (pretest, posttest, etc.) • R = random assignment
Common Experimental Designs • Single-group pretest-treatment-posttest design: O X O • Technically, a pre-experimental design (only one group; therefore, no random assignment exists) • Overall, a weak design • Why?
Common Experimental Designs (cont’d.) • Two-group treatment-posttest-only design: R X1 O R X2 O • Here, we have random assignment to experimental, control groups • A better design, but still weak—cannot be sure that groups were equivalent to begin with
Common Experimental Designs (cont’d.) • Two-group pretest-treatment-posttest design: R O X1 O R O X2 O • A substantially improved design—previously identified errors have been reduced
Common Experimental Designs (cont’d.) • Solomon four-group design: R O X1 O R O X2 O R X1 O R X2 O • A much improved design—how?? • One serious drawback—requires twice as many participants
Common Experimental Designs (cont’d.) • Factorial designs: R O X1g1 O R O X2g1 O R O X1g2 O R O X2g2 O • Incorporates two or more factors • Enables researcher to detect differential differences (effects apparent only on certain combinations of levels of independent variables)
Common Experimental Designs (cont’d.) • Single-participant measurement-treatment-measurement designs: O O O | X O X O | O O O • Purpose is to monitor effects on one subject • Results can be generalized only with great caution
Common Quasi-Experimental Designs • Posttest-only design with nonequivalent groups: X1 O X2 O • Uses two groups from same population • Questions must be addressed regarding equivalency of groups prior to introduction of treatment
Common Quasi-Experimental Designs (cont’d.) • Pretest-posttest design with nonequivalent groups: O X1 O O X2 O • A stronger design—pretest may be used to establish group equivalency
