Research Design
Let us now learn about the different types of research designs. Choosing the right design for your research is important to avoid problems on writing down a research work.
Research Designs:
1. True experimental design is regarded as the most accurate and used form of experimental research, it tries to prove or disprove a hypothesis mathematically , with statistical analysis.
For some of the physical sciences, such as physics, chemistry and geology, they are standard and commonly used. For social sciences, psychology and biology, they can be a little more difficult to set up.
For an experiment to be classed as a true experimental design, it must fit all of the following criteria.
Groups must be assigned via random sampling.
There must be a control group.
Only one variable can be manipulated and tested. It is possible to test more than one, but such experiments and their statistical analysis tend to be cumbersome and difficult.
The tested subjects must be randomly assigned to either control or experimental groups.
ADVANTAGES
The results of a true experimental design can be statistically analyzed and so there can be little argument about the results. It can be manipulated. It is also much easier for other researchers to replicate the experiment and validate the results. For physical sciences working with mainly numerical data, it is much easier to manipulate one variable, so true experimental design usually gives a yes or no answer.
DISADVANTAGES
Whilst perfect in principle, there are a number of problems with this type of design. Firstly, they can be almost too perfect, with the conditions being under Complete and not being representative of real world conditions. For psychologists and behavioral biologists, for example, there can never be any guarantee that a human or living organism will exhibit ‘normal’ behavior under experimental conditions. True experiments can be too accurate and it is very difficult to obtain a complete rejection or acceptance of a hypothesis because the standards of proof required are so difficult to reach. True experiments are also difficult and expensive to set up. They can also be very impractical.
While for some fields, like medicine, there are not as many variables so the design is easy, for social sciences and biological sciences, where variations are not so clearly defined it is much more difficult to exclude other factors that may be affecting the manipulated variable.
2. Quasi-experimental design is a form of experimental research used extensively in the social sciences and courses that focuses on behaviors like psychology.
Quasi - Experimental design involves selecting groups, upon which a variable is tested, without any random pre-selection processes.
For instance to perform an educational experiment, a group might be arbitrarily divided by alphabetical selection. The division is often convenient and, especially in an educational situation, causes as little disruption as possible.
After this selection, the experiment proceeds in a very similar way to any other experiment, with a variable being compared between different groups, or over a period of time.
ADVANTAGES
Especially in social sciences, where pre-selection and randomization of groups is often difficult, they can be very useful in generating results for general trends.
Example if we study the effect of maternal cigarette use when the mother is pregnant, we know that cigarette does harm the baby and the mother. A a strict experimental design would include that mothers were randomly assigned to smoke cigarette. This would be highly illegal because of the possible harm the study might do to the participants.
So what researchers does is to ask people how much cigarette they smoke in their pregnancy and then assign them to groups.
Quasi-experimental design is often integrated with individual case studies; the figures and results generated often reinforce the findings in a case study, and allow some sort of statistical analysis to take place.
In addition, without extensive pre-screening and randomization needing to be undertaken, they do reduce the time and resources needed for experimentation.
DISADVANTAGES
Without proper randomization, statistical tests can be meaningless. For example, these experimental designs do not take into account any pre-existing factors (as for the mothers: what made them smoke or not smoke a cigarette), or recognize that influences outside the experiment may have affected the results. A quasi experiment constructed to analyze the effects of different educational programs on two groups of children, for example, might generate results that show that one program is more effective than the other.
These results will not stand up to rigorous statistical scrutiny because the researcher also need to control other factors that may have affected the results. This is really hard to do properly.
3. The double blind experiment takes this precaution against bias one-step further, by ensuring that the researcher does not know in which group a patient falls.
Whilst the vast majority of researchers are professionals, there is always a chance that the researcher might subconsciously tip off a patient about the pill they were receiving. They may even favor giving the pill to patients that they thought had the best chance of recovery, skewing the results.
Whilst nobody likes to think of scientists as dishonest, there is often pressure, from billion dollar drug companies and the fight for research grants, to generate positive results.
This always gives a chance that a scientist might manipulate results, and try to show the research in a better light. Proving that the researcher carried out a double blind experiment reduces the chance of criticism.
4. Descriptive research design is a method which involves observing and describing the behavior of a subject without influencing it in any way. This cannot be manipulated. This research also uses survey as a tool for the collection of data.
Many scientific disciplines, especially social science and psychology, use this method to obtain a general overview of the subject. Some subjects cannot be observed in any other way; for example, a social case study of an individual subject is a descriptive research design and allows observation without affecting normal behavior.
It is also useful where it is not possible to test and measure the large number of samples needed for more quantitative types of research .
These types of experiments are often used by anthropologists, psychologists and social scientists to observe natural behaviors without affecting them in any way. It is also used by market researchers to judge the habits of customers, or by companies wishing to judge the morale of staff.
The results from a descriptive research can in no way be used as a definitive answer or to disprove a hypothesis but, if the limitations are understood, they can still be a useful tool in many areas of scientific research.
ADVANTAGES
The subject is being observed in a completely natural and unchanged natural environment. A good example of this would be an anthropologist who wanted to study a tribe without affecting their normal behavior in any way. True experiments, whilst giving analyzable data, often adversely influence the normal behavior of the subject.
Descriptive research is often used as a pre-cursor to more quantitatively research designs, the general overview giving some valuable pointers as to what variables are worth testing quantitatively. Quantitative experiments are often expensive and time-consuming so it is often good sense to get an idea of what hypothesis are worth testing.
DISADVANTAGES
Because there are no variables manipulated, there is no way to statistically analyze the results. Many scientists regard this type of study as very unreliable and ‘unscientific’.
In addition, the results of observational studies are not repeatable , and so there can be no replication of the experiment and reviewing of the results
5. Case study is an in depth study of a particular situation rather than a sweeping statistical survey . It is a method used to narrow down a very broad field of research into one easily researchable topic.
Whilst it will not answer a question completely, it will give some indications and allow further elaboration and hypothesis creation on a subject.
The case study research design is also useful for testing whether scientific theories and models actually work in the real world. You may come out with a great computer model for describing how the ecosystem of a rock pool works but it is only by trying it out on a real life pool that you can see if it is a realistic simulation.
For psychologists, anthropologists and social scientists they have been regarded as a valid method of research for many years. Scientists are sometimes guilty of becoming bogged down in the general picture and it is sometimes important to understand specific cases and ensure a more holistic approach to research.
6. A longitudinal study is observational research performed over a period of years or even decades, and allows social scientists and economists to study long-term effects in a human population.
7. The cross sectional study takes a snapshot of a population at a certain time, allowing conclusions about phenomena across a wide population to be drawn.
8. The survey research design is often used because of the low cost and easy accessible information.
9. Meta analysis is the process of drawing from a larger body of research, and using powerful statistical analyzes on the conglomerated data.
This gives a much larger sample population and is more likely to generate meaningful and usable data.
10. A field study is an experiment performed outside the laboratory, in the 'real' world.
11. A cohort study is a research program investigating a particular group with a certain trait, and observes over a period of time.
12. A pilot study is a standard scientific tool for 'soft' research, allowing scientists to conduct a preliminary analysis before committing to a full-blown study or experiment.
Reference:
http://www.experiment-resources.com/research-designs.html
http://www.markwebtest.netfirms.com/teachRDE/start/default.html
http://www.sportsci.org/jour/0001/wghdesign.html
Iverseen Gudmund R. and Norpoth Helmut (1976) "Analysis of variance" Sage University Paper series on quantitative applications in social sciences. 07- 001 Beverly Hills and London. Sage Publications
Paul E. Spector (1981) Research Designs, Series: Quantitative Applications in Social Sciences. Sage Publications
Let us now learn about the different types of research designs. Choosing the right design for your research is important to avoid problems on writing down a research work.
Research Designs:
1. True experimental design is regarded as the most accurate and used form of experimental research, it tries to prove or disprove a hypothesis mathematically , with statistical analysis.
For some of the physical sciences, such as physics, chemistry and geology, they are standard and commonly used. For social sciences, psychology and biology, they can be a little more difficult to set up.
For an experiment to be classed as a true experimental design, it must fit all of the following criteria.
Groups must be assigned via random sampling.
There must be a control group.
Only one variable can be manipulated and tested. It is possible to test more than one, but such experiments and their statistical analysis tend to be cumbersome and difficult.
The tested subjects must be randomly assigned to either control or experimental groups.
ADVANTAGES
The results of a true experimental design can be statistically analyzed and so there can be little argument about the results. It can be manipulated. It is also much easier for other researchers to replicate the experiment and validate the results. For physical sciences working with mainly numerical data, it is much easier to manipulate one variable, so true experimental design usually gives a yes or no answer.
DISADVANTAGES
Whilst perfect in principle, there are a number of problems with this type of design. Firstly, they can be almost too perfect, with the conditions being under Complete and not being representative of real world conditions. For psychologists and behavioral biologists, for example, there can never be any guarantee that a human or living organism will exhibit ‘normal’ behavior under experimental conditions. True experiments can be too accurate and it is very difficult to obtain a complete rejection or acceptance of a hypothesis because the standards of proof required are so difficult to reach. True experiments are also difficult and expensive to set up. They can also be very impractical.
While for some fields, like medicine, there are not as many variables so the design is easy, for social sciences and biological sciences, where variations are not so clearly defined it is much more difficult to exclude other factors that may be affecting the manipulated variable.
2. Quasi-experimental design is a form of experimental research used extensively in the social sciences and courses that focuses on behaviors like psychology.
Quasi - Experimental design involves selecting groups, upon which a variable is tested, without any random pre-selection processes.
For instance to perform an educational experiment, a group might be arbitrarily divided by alphabetical selection. The division is often convenient and, especially in an educational situation, causes as little disruption as possible.
After this selection, the experiment proceeds in a very similar way to any other experiment, with a variable being compared between different groups, or over a period of time.
ADVANTAGES
Especially in social sciences, where pre-selection and randomization of groups is often difficult, they can be very useful in generating results for general trends.
Example if we study the effect of maternal cigarette use when the mother is pregnant, we know that cigarette does harm the baby and the mother. A a strict experimental design would include that mothers were randomly assigned to smoke cigarette. This would be highly illegal because of the possible harm the study might do to the participants.
So what researchers does is to ask people how much cigarette they smoke in their pregnancy and then assign them to groups.
Quasi-experimental design is often integrated with individual case studies; the figures and results generated often reinforce the findings in a case study, and allow some sort of statistical analysis to take place.
In addition, without extensive pre-screening and randomization needing to be undertaken, they do reduce the time and resources needed for experimentation.
DISADVANTAGES
Without proper randomization, statistical tests can be meaningless. For example, these experimental designs do not take into account any pre-existing factors (as for the mothers: what made them smoke or not smoke a cigarette), or recognize that influences outside the experiment may have affected the results. A quasi experiment constructed to analyze the effects of different educational programs on two groups of children, for example, might generate results that show that one program is more effective than the other.
These results will not stand up to rigorous statistical scrutiny because the researcher also need to control other factors that may have affected the results. This is really hard to do properly.
3. The double blind experiment takes this precaution against bias one-step further, by ensuring that the researcher does not know in which group a patient falls.
Whilst the vast majority of researchers are professionals, there is always a chance that the researcher might subconsciously tip off a patient about the pill they were receiving. They may even favor giving the pill to patients that they thought had the best chance of recovery, skewing the results.
Whilst nobody likes to think of scientists as dishonest, there is often pressure, from billion dollar drug companies and the fight for research grants, to generate positive results.
This always gives a chance that a scientist might manipulate results, and try to show the research in a better light. Proving that the researcher carried out a double blind experiment reduces the chance of criticism.
4. Descriptive research design is a method which involves observing and describing the behavior of a subject without influencing it in any way. This cannot be manipulated. This research also uses survey as a tool for the collection of data.
Many scientific disciplines, especially social science and psychology, use this method to obtain a general overview of the subject. Some subjects cannot be observed in any other way; for example, a social case study of an individual subject is a descriptive research design and allows observation without affecting normal behavior.
It is also useful where it is not possible to test and measure the large number of samples needed for more quantitative types of research .
These types of experiments are often used by anthropologists, psychologists and social scientists to observe natural behaviors without affecting them in any way. It is also used by market researchers to judge the habits of customers, or by companies wishing to judge the morale of staff.
The results from a descriptive research can in no way be used as a definitive answer or to disprove a hypothesis but, if the limitations are understood, they can still be a useful tool in many areas of scientific research.
ADVANTAGES
The subject is being observed in a completely natural and unchanged natural environment. A good example of this would be an anthropologist who wanted to study a tribe without affecting their normal behavior in any way. True experiments, whilst giving analyzable data, often adversely influence the normal behavior of the subject.
Descriptive research is often used as a pre-cursor to more quantitatively research designs, the general overview giving some valuable pointers as to what variables are worth testing quantitatively. Quantitative experiments are often expensive and time-consuming so it is often good sense to get an idea of what hypothesis are worth testing.
DISADVANTAGES
Because there are no variables manipulated, there is no way to statistically analyze the results. Many scientists regard this type of study as very unreliable and ‘unscientific’.
In addition, the results of observational studies are not repeatable , and so there can be no replication of the experiment and reviewing of the results
5. Case study is an in depth study of a particular situation rather than a sweeping statistical survey . It is a method used to narrow down a very broad field of research into one easily researchable topic.
Whilst it will not answer a question completely, it will give some indications and allow further elaboration and hypothesis creation on a subject.
The case study research design is also useful for testing whether scientific theories and models actually work in the real world. You may come out with a great computer model for describing how the ecosystem of a rock pool works but it is only by trying it out on a real life pool that you can see if it is a realistic simulation.
For psychologists, anthropologists and social scientists they have been regarded as a valid method of research for many years. Scientists are sometimes guilty of becoming bogged down in the general picture and it is sometimes important to understand specific cases and ensure a more holistic approach to research.
6. A longitudinal study is observational research performed over a period of years or even decades, and allows social scientists and economists to study long-term effects in a human population.
7. The cross sectional study takes a snapshot of a population at a certain time, allowing conclusions about phenomena across a wide population to be drawn.
8. The survey research design is often used because of the low cost and easy accessible information.
9. Meta analysis is the process of drawing from a larger body of research, and using powerful statistical analyzes on the conglomerated data.
This gives a much larger sample population and is more likely to generate meaningful and usable data.
10. A field study is an experiment performed outside the laboratory, in the 'real' world.
11. A cohort study is a research program investigating a particular group with a certain trait, and observes over a period of time.
12. A pilot study is a standard scientific tool for 'soft' research, allowing scientists to conduct a preliminary analysis before committing to a full-blown study or experiment.
Reference:
http://www.experiment-resources.com/research-designs.html
http://www.markwebtest.netfirms.com/teachRDE/start/default.html
http://www.sportsci.org/jour/0001/wghdesign.html
Iverseen Gudmund R. and Norpoth Helmut (1976) "Analysis of variance" Sage University Paper series on quantitative applications in social sciences. 07- 001 Beverly Hills and London. Sage Publications
Paul E. Spector (1981) Research Designs, Series: Quantitative Applications in Social Sciences. Sage Publications
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