There are many different types of "experiments." Most are quite different from the common stereotype. All experimental research, however, has several elements in common. One of the most obvious is the division of the subjects into groups (control, experimental, etc.). Another is the use of a "treatment" (usually the independent variable) which is introduced into the research context or manipulated by the researcher. The four research parameters (discussed earlier in this module) will help us understand the other distinguishing characteristics of experimental research.
On the synthetic-analytic continuum, experimental research tends to fall on the analytic end. Unless it is very complicated, an experiment typically focuses on a specific element (a "constituent part") of the larger process of language learning and teaching.
The next parameter deals with the heuristic (hypothesis-generating) vs. deductive (hypothesis-testing) factor. In contrast to qualitative research, virtually all experiments are designed to test hypotheses.
Experiments generally fall on the high end of this scale because they attempt to control the research environment to a considerable degree. This can be both a plus and a minus.
|On the one hand, it allows the researcher to isolate a particular variable and focus on it in order to determine its effect on other variables. Because of this feature, only experimental studies can claim to show any degree of causality. Qualitative and descriptive research can reveal only relationships or processes.||On the other hand, control has several disadvantages. One is that it often makes the research situation unnatural. Consequently, subjects may not behave normally in an experiment. Another disadvantage is that it is virtually impossible to control all the variables in a research situation involving human beings. Finally, controlled experiments often raise serious questions about research ethics.|
The final parameter deals with the level of explicitness in data collection. Here again, experimental research falls toward the high end of the scale. Carefully focused instruments (tests, observations, questionnaires, etc.) that generate precise quantitative data are the norm in experiments. These data can be analyzed using statistical tests of significance in order to accept or reject the hypothesis.