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Would you be able to recall the definition given to experimental design studies in the previous unit? If you do, excellent and well done. As was stated in that unit experimental design studies explore the nature and scope of cause – effect

relationships between independent variable and dependent variable. In order for an experimental study to achieve this goal and help the researcher make accurate and verifiable predictions and explanations of events, their causality and so on, the activities which comprise the research itself must possess a high degree of validity

and reliability. It may interest you to know that it may not have this validity if the experiment is threatened. There are two classes of such validity threats namely internal validity threats and external validity threats. We will discuss them now one in this section and another in the next section.

SELF ASSESSMENT EXERCISE 1

Identify the two validity threats to any experimental design study.

3.2 Internal Validity Threats to Experimental Studies

In the last section, you learnt that internal and external validity threats may not allow experimental research studies to possess a high degree of validity and

reliability to achieve its goal of enabling researchers make accurate and verifiable predictions and explanation of research events. This is a very disturbing problem. In this section, you will learn what these internal validity threats are and how to

minimize them. It is when the internal validity threats are removed or minimized that it would be possible for the researcher to assert that it was the experimental treatment that brought about the change of the observed effects on the dependent variable. Generally, eight extraneous variables have been identified to have serious

internal validity threats to experimental research in educational media (Ali, 1996), (Campbell and Standley, 1966); and (Cook and Campbell, 1979).

These extraneous variables are identified as follows:

Pre-testing, History, maturation, instability of instrument, experimental mortality, statistical regression, selection biases arising from differential selection of subjects;

influence of earlier treatment experiences.

We will now discuss them one after the other in this section.

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Pretesting: Pretesting which is administering research test to subjects before the commencement of a study sensitizes them to become aware or suspicious of the purposes of the post-testing aspect of the experiment. In the

educational setting where students prepare for their examinations from previous examination papers, protest questions may be carefully, repetitively and methodically studied by students prior to the posttest almost to the extent that any observed improved performance on the posttest by the subjects may not be because of effects of the experimental treatment. Designs of

experiments which have pretest suffer from this internal validity threat.

History: Certain historical and unique environmental events beyond the

control of the experimental researcher but which may have had profound effects on the student subjects can confound the independent variable of a research study on the dependent variable of the .study Historical events such

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as famine, calamities, economic hardships, change in the school year or curricula, anxiety produced by the forthcoming cxamination can either singly or in combination, as the case may be, enhance, disturb or stimulate student subjects performance on the dependent variable A longer experimental research study stands a higher chance of historical events affecting it.

Maturation: Subjects, and indeed all human beings, do change with time regardless of what treatment conditions they are exposed to.

Between the initial test and subsequent tests, the subjects may have undergone many kinds of changes since they are influenced by several factors of life not just that of the experimental treatment factor. Changes include becoming less or more bored, becoming more or less wise, becoming more or less motivated, as the case may be. And each or all of these changes may produce an observed dependent variable which is then falsely attributed to the experimental treatment rather than these maturational changes.

Instability of Instrument: If an experimental design instrument for data collection is not valid, reliable and appropriate or if the techniques of using the instrument, as well as observing and recording the data are not consistent and systematic, data obtained from such instrument or techniques are unstable. An instrument which is faulty or precise and valid instrument wrongly used will yield unstable data, when used. Similarly, haphazard techniques in data collection yield unstable data. Researchers should guide against any source of error such as instrument decay (faulty, imprecision from overuse etc) which poses an internal validity threat to their work. For instance, if research assistants are used for recording observed data, care must be taken to ensure that they know what to observed, when to observed, what to record, how to record, when to stop recording either because of fatigue, boredom and lack of focus on what to record. Otherwise, serious errors are introduced into the experimental data and become a serious internal validity threat. Under no circumstance should the same assistant be used for recording observation data for experimental and control groups.

Experimental Mortality: Subjects in an experimental research study may reduce in number between the time the experiment commenced and when it ended. Losses in data can arise from illness, parental request, deaths,

movement of some subjects to another school, unwillingness of subjects to continue, and incomplete data set. Imagine that almost all the losses were subjects in the experimental treatment group who had scored low in the pretest. Because those remaining did well in the pretest they would most naturally do well in the posttest not so much because of the effects of

treatment as much as the fact that those students who scored low in the pretest did not do the posttest. Mortality is a problem in experiments which span long period.

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Statistical Regression: If subjects are grouped on the basis of their pretest scores, in addition to the interactive effect between pretest and posttest, there will be problem of statistical regression. Statistical regression is a

phenomenon in a pretest posttest experiment in which extremes of scores in an experiment (e.g. a subjects low pretest score and high posttest score) may be misjudged or misinterpreted as arising from treatment effect. The truth of any pretest-posttest design is, in part, that subjects in any comparative group who score highest on the pretest are likely to score relatively lower on the posttest while subjects in any of research groups being compared who score lowest on the pretest are likely to score higher on a posttest. Thus, the researcher should be aware that the subjects who scored lowest or highest in the pretest are not necessarily the lowest or highest scoring subjects.

Therefore, regression as an internal validity threat occurs inevitably in any pretest-posttest design essentially because there is usually a regression of pretest-posttest means of the subject toward the overall mean of the entire group. Failure to recognize this regression results in wrongly attributing the observed experimental group‟s superior gains scores (difference between pretest and posttest scores) or any observed gain score differences between groups as a direct and entire consequence of the treatment effect

experimental group subjects were subjected to when in fact gain score differences may be affected, even if by a small margin, by regression.

Selection Biases Arising from Differential Selection of Subjects: Even when a researcher may not be aware of this, when he selects and groups subjects, certain criteria unwittingly influence who he selects and puts in a particular research group. When this happens, as it is bound to happen, there is the occurrence of nonequivalent grouping of subjects prior to the commencement of the experiment. The general tendency, among unwary researchers, is for selecting and assigning better subjects into the experimental group, an early advantage which enables these better subjects to do better than the control group subjects who were worse candidates before the commencement of the experiment and who, in any case, would be expected to perform worse at the posttest than their experimental group counterparts. Under this condition, the researcher‟s selection biases threaten the internal validity of his results since his results may well not have been caused by the treatment but more so from the fact that, ab iniitio, the experimental subjects were favoured and consequently better than the control group subjects and so, as would be expected, did better than the control in the posttest result.

Influence of Earlier Treatment Experiences: Many researchers use subjects whose earlier history of exposure to other research conditions they do not know of and care to find out. Such earlier influences may well affect

experimental research finding either negatively or positively to all the research subject, selectively to members of the research subjects or

selectively to members of a particular comparative research group. For

instance, a researcher may unknowingly use and group into experimental group 1, more subjects who had just finished an earlier experiment on

reading and therefore have more reading skills than the control group subjects most of whose members did not participate in the reading

experiment project earlier completed by the earlier researcher. Because of this earlier treatment of reading skill on some subjects and none for other subjects, there is already an ab initio introduction of unfair advantage to the experimental group subjects and unfair disadvantage to the control group, for any research study they are used for, involving reading; an undeserved

advantage or disadvantage especially when later experimental work involve word problems, as in mathematics, study which involve one‟s reading skills, and so on. To avoid this problem, researchers should find out earlier

experiences of their subjects, ensure that these experiences are fairly well distributed in the population they want to work with and then randomly sample from that population. (Ali, 1996)

SELF ASSESSMENT EXERCISE 2

Identify the extraneous variables that constitute internal validity threats to experimental design studies.