Experimental Research

Experimental Research

It is a collection of research designs which use manipulation and controlled testing to understand causal processes. Generally, one or more variables are manipulated to determine their effect on a dependent variable.

The experimental method

is a systematic and scientific approach to research in which the researcher manipulates one or more variables, and controls and measures any change in other variables.

Experimental Research is often used where:

1. There is time priority in a causal relationship (cause precedes effect)
2. There is consistency in a causal relationship (a cause will always lead to the same effect)
3. The magnitude of the correlation is great.

The word experimental research has a range of definitions. In the strict sense, experimental research is what we call a true experiment.

This is an experiment where the researcher manipulates one variable, and control/randomizes the rest of the variables. It has a control group, the subjects have been randomly assigned between the groups, and the researcher only tests one effect at a time. It is also important to know what variable(s) you want to test and measure.

A very wide definition of experimental research, or a quasi experiment, is research where the scientist actively influences something to observe the consequences. Most experiments tend to fall in between the strict and the wide definition.

A rule of thumb is that physical sciences, such as physics, chemistry and geology tend to define experiments more narrowly than social sciences, such as sociology and psychology, which conduct experiments closer to the wider definition.

Aims of Experimental Research

Experiments are conducted to be able to predict phenomenon’s. Typically, an experiment is constructed to be able to explain some kind of causation. Experimental research is important to society - it helps us to improve our everyday lives.

BASIC CONCEPTS of Experimental Research

The experimental research involves some basic concept

And terminologies which are discussed briefly here:

¨    Experimental group:

A group of individuals, objects or events, exposed to the influence of

The Factor under consideration, is called an Experimental group.

¨    Controlled group:

A group of individuals, objects or events not exposed to the influence

Of the factor under consideration, is called a Controlled group.

¨    Variable:

 a situation, number or quantity that can vary or be varied.

Types of Variables

n  Independent variables:

n  Dependent variables:

n  Confounding Variables:

n  Intervening Variables:

n  Extraneous Variables:

Independent variables:

·         They are also called Experimental or Treatment Variables.

·         These are the variables which an experimenter manipulates or controls him/herself and observes their impact on the phenomenon under consideration.

·         For example, “the effect of A.V Aids on the academic achievements of the students”,

·         here, the A.V Aids are independent variables, which are controlled or manipulated by the researcher.

Dependent variables:

·         They are also called the Criterion or Outcome Variables.

·         These are the variables which change, appear or disappear by the influence of the independent variables.

·         The dependent variables can only be observed or recorded

·         in the above example; the academic achievements are dependent upon the effect of A.V. Aids,

·         here the academic achievements refer to the dependent variables.

Confounding Variables:

• Those aspects of the study or sample that might influence the dependent variable (outcome measure) and whose effect may be confused with effects of the independent variable.

 Intervening Variables

·         Variables which cannot be controlled or measured directly may have an important effect upon the outcome.

·         These modifying variables intervene between the cause and the effect.

§  Anxiety

§  Fatigue

§  Motivation

·         May be controlled upto some extent by using appropriate designs.

Extraneous variables:

• Those uncontrolled variables that may have a significant influence upon the results of a study.
• Teacher competence or enthusiasm
• Age
• Socioeconomic level
• Academic ability

METHODS TO CONTROL EXTRANEOUS VARIABLES

• Extraneous variables can’t be totally controlled, however, their effect can be minimized by using some technique like the following.
• Elimination:
• Randomization:
• Matching cases:
• Balancing cases:

Elimination:

n  If possible, remove the extraneous variables completely, for example consider the same example i.e. “The effect of A.V. Aids on the academic achievements of students,” Here the gender factor may be an extraneous variable, so remove this factor completely i.e. undertake the research only on male or female students. So this method of removing the extraneous variables is called elimination.

Randomization:

It means to minimize the effect of extraneous variables by taking random samples. For example, the extraneous variables may be present in both experimental as well as controlled groups. So, the effect of extraneous variables will not produce an error in the results.

Matching cases: It means to take the groups matching with each other, i.e. the groups are equal in all respects. For example, we have to study the effect of drill on the improvement of spellings, so, in order to minimize the effect of extraneous variables; the students of almost equal intelligence are selected in the experimental as well as controlled group. This is called matching case, which is done wherever randomization is not possible.

Balancing cases: It means that the two groups are balanced with each other. Consider for example, the above study i.e. “the effect of Drill on the improvement of spellings”. If there is a group of eight students (the experimental group) in which five students are of high intelligence and three are feeble minded. So, while taking the controlled group, there must be a total of eight students including five of high intelligence and three feeble minded, so that the two groups are matched equally.

PROCESS AND PROCEDURE OF EXPERIMENTAL RESEARCH

¨  Studying the problematic situation

¨  Problem selection

¨  Specification of objectives

¨  Hypothesis

¨  Measuring instruments

¨  Planning and selecting experimental design

¨  Pilot-test of the instrument

¨  Execution

¨  Data analysis

¨  Conclusion

¨  Further verification of results

Experimental Design

n  An experimental design means a blue-print of the experimental procedure to be followed, in order to determine the cause-effect relationship.

Types of Experimental Designs

n  Pre-Experimental

n  True Experimental

n  Quasi-Experimental

Pre Experimental:

n  The essential ingredient of a true experiment is random assignment of subjects to treatment groups

n  Random assignments is a powerful tool for controlling threats to internal validity

Designs of Pre-Experimental 

·         One-Shot case study

·         Randomized pretest-posttest control group design

·         The Static Group Comparison Design

True Experimental

n  The True Experimental designs involve the equivalent experimental and controlled groups for comparison. In educational and behavioral sciences, it is very difficult to achieve the two groups exactly similar in all aspects, however, True Experimental designs are further sub-divided into 2.

Ø  Randomized matched control group design

Ø  Factorial design

Quasi-experimental Designs

n  One group posttest-only design

n  One group pretest-posttest design

n  Non-equivalent control group design

n  Non-equivalent control group pretest-posttest design

n  Time series

n  Single subject designs (Case study)

Identifying the Research Problem

After deciding the topic of interest, the researcher tries to define the research problem. This helps the researcher to focus on a more narrow research area to be able to study it appropriately. Defining the research problem helps you to formulate a research hypothesis, which is tested against the null hypothesis.

The research problem is often operationalizationed, to define how to measure the research problem. The results will depend on the exact measurements that the researcher chooses and may be operationalized differently in another study to test the main conclusions of the study.

Constructing the Experiment

There are various aspects to remember when constructing an experiment. Planning ahead ensures that the experiment is carried out properly and that the results reflect the real world, in the best possible way.

Sampling Groups to Study

Sampling groups correctly is especially important when we have more than one condition in the experiment. One sample group often serves as a control group, whilst others are tested under the experimental conditions.

Deciding the sample groups can be done in using many different sampling techniques. Population sampling may chosen by a number of methods, such as randomization, "quasi-randomization" and pairing.

Reducing sampling errors is vital for getting valid results from experiments. Researchers often adjust the sample size to minimize chances of random errors.

Here are some common sampling techniques:

• probability sampling
• non-probability sampling
• simple random sampling
• convenience sampling
• stratified sampling
• systematic sampling
• cluster sampling
• sequential sampling
• disproportional sampling
• judgmental sampling
• snowball sampling
• quota sampling

Creating the Design

The research design is chosen based on a range of factors. Important factors when choosing the design are feasibility, time, cost, ethics, measurement problems and what you would like to test. The design of the experiment is critical for the validity of the results.

Typical Designs and Features in Experimental Design

• Pretest-Posttest Design
  Check whether the groups are different before the manipulation starts and the effect of the manipulation. Pretests sometimes influence the effect.
• Control Group
  Control groups are designed to measure research bias and measurement effects, such as the Hawthorne Effect or the Placebo Effect. A control group is a group not receiving the same manipulation as the experimental group. Experiments frequently have 2 conditions, but rarely more than 3 conditions at the same time.
• Randomized Controlled Trials
  Randomized Sampling, comparison between an Experimental Group and a Control Group and strict control/randomization of all other variables
• Solomon Four-Group Design
  With two control groups and two experimental groups. Half the groups have a pretest and half do not have a pretest. This to test both the effect itself and the effect of the pretest.
• Between Subjects Design
  Grouping Participants to Different Conditions
• Within Subject Design
  Participants Take Part in the Different Conditions - See also: Repeated Measures Design
• Counterbalanced Measures Design
  Testing the effect of the order of treatments when no control group is available/ethical
• Matched Subjects Design
  Matching Participants to Create Similar Experimental- and Control-Groups
• Double-Blind Experiment
  Neither the researcher, nor the participants, know which is the control group. The results can be affected if the researcher or participants know this.
• Bayesian Probability
  Using bayesian probability to "interact" with participants is a more "advanced" experimental design. It can be used for settings were there are many variables which are hard to isolate. The researcher starts with a set of initial beliefs, and tries to adjust them to how participants have responded

Pilot Study

It may be wise to first conduct a pilot-study or two before you do the real experiment. This ensures that the experiment measures what it should, and that everything is set up right.

Minor errors, which could potentially destroy the experiment, are often found during this process. With a pilot study, you can get information about errors and problems, and improve the design, before putting a lot of effort into the real experiment.

If the experiments involve humans, a common strategy is to first have a pilot study with someone involved in the research, but not too closely, and then arrange a pilot with a person who resembles the subject(s). Those two different pilots are likely to give the researcher good information about any problems in the experiment.

Conducting the Experiment

An experiment is typically carried out by manipulating a variable, called the independent variable, affecting the experimental group. The effect that the researcher is interested in, the dependent variable(s), is measured.

Identifying and controlling non-experimental factors which the researcher does not want to influence the effects, is crucial to drawing a valid conclusion. This is often done by controlling variables, if possible, or randomizing variables to minimize effects that can be traced back to third variables. Researchers only want to measure the effect of the independent variable(s) when conducting an experiment, allowing them to conclude that this was the reason for the effect.

Conducting the Experiment

An experiment is typically carried out by manipulating a variable, called the independent variable, affecting the experimental group. The effect that the researcher is interested in, the dependent variable(s), is measured.

Identifying and controlling non-experimental factors which the researcher does not want to influence the effects, is crucial to drawing a valid conclusion. This is often done by controlling variables, if possible, or randomizing variables to minimize effects that can be traced back to third variables. Researchers only want to measure the effect of the independent variable(s) when conducting an experiment, allowing them to conclude that this was the reason for the effect.

The aim of an analysis is to draw a conclusion, together with other observations. The researcher might generalize the results to a wider phenomenon, if there is no indication of confounding variables "polluting" the results.

If the researcher suspects that the effect stems from a different variable than the independent variable, further investigation is needed to gauge the validity of the results. An experiment is often conducted because the scientist wants to know if the independent variable is having any effect upon the dependent variable. Variables correlating are not proof that there is causation.