RESEARCH DESIGN
INTRODUCTION
Research is a critical, careful, scholarly, scientific, positive, exhaustive investigation or an organized and systematic inquiry of facts or answer to questions and solution to the problems. The term ‘research design’ means drawing a tentative outline, a blue print and a scheme, planning or arranging a strategy of conducting research with a through knowledge about research methodology. It can enable certain guidelines and procedure to pursue authentic and relevant investigation with a professional standard. It is a logical and systematic plan for collecting data, measurement and analysis of data and prepared for a research study. The research proposal is a written plan for a study and it reveals what the researcher intends to do. In this paper the specific emphasis is given to the ‘research design’ keeping in mind the ‘empirical studies’[1], important concepts in research design, classify the major types of designs and an attempt is also made to present a format of a research project. Any scientific investigation must begin with some structure or plan. This structure defines the number and the type of variables to be studied and their relationship to one another. Such a structure is termed a design.
WHAT IS RESEARCH DESIGN
Kerlinger defines ‘a research design as the plan, structure and strategy of investigation purporting to answer research questions and control variance’.[2] Research design provides the ‘glue’ that holds the research project together. A design is used to structure the research, to show how all of the major parts of the research project - the samples or groups, measures, treatments or programs, and methods of assignment- work together to try to address the central research questions. We often describe a design using a concise notation that enables us to summarize a complex design structure efficiently.[3]
A research design is prepared for collecting and analyzing new data for interpreting the already available facts in a new way. Preparation for a research design involves making proper arrangements for systematic research work. The researcher plans the various operations, keeping the theoretical framework and the availability of the required resources in mind.[4] The research design is the outline of a plan for collecting and analyzing data. For this purpose hypothesis are set out, Concepts are refined, operational definitions are formulated, scales are chosen, reliability and validity are taken into account, once decides which tools are to be used and which statistical tests are to be applied. Preparing a research design involves deciding the appropriate means for achieving the targets laid down ahead of time, with a minimum expenditure of time, money and manpower.[5]
There is no agreement on the structure of how to design a qualitative study. A qualitative study generally falls within the process of scientific research, with common phases whether on is writing qualitatively or quantitatively.[6] A research seems to start with an issue of the problem, examines the literature in some way related to the problem, pose questions, gather data and then analyze them, and write up their reports. The qualitative research fits within this structure.[7] The process of designing a qualitative study begins not with the method which is actually the easiest part of the research, I believe but instead with a broad assumption central to qualitative inquiry, a worldview consistent with it, and in many cases, a theoretical lens that shapes the study.[8]
BASIC CONCEPTS IN RESEARCH DESIGN
1. Variable
A variable is a qualitative or quantitative entity that can vary or take on different values according to the nature of the research. Variables represent the concepts under consideration in the study. According to ‘Best’ "variables are the conditions or characteristics that the experimenter manipulates, controls, or observes".[9]
2. Independent and Dependent Variables
The independent variables are the conditions or characteristics that the experimenter manipulates in his/her attempt to ascertain their relationship to an observed phenomenon. The independent variable is a variable that can be used to predict or explain the values of another variable. According to Best (1984) "a variable manipulated by an experimenter who predicts that the manipulation will have an effect on another variable (the dependent variable) is called an independent variable".[10] Some authors use the term independent variable for experimental research only. Instead of independent variable these authors use the term predictor variable. Essentially, dependent variable is the behavioral or attitudinal measurement made by the experimenter. The dependent variable gets its name because it depends on what does with the independent variable. According to Best (1984), the dependent variables are the conditions or characteristics that appear, disappear, or change an experimenter introduces, removes, or changes independent variables.[11] The variable whose values are predicted by the independent variable, whether or not caused by it. In non-experimental research, instead of dependent variable some authors use the term criterion variable or outcome variable. Most commonly, however, dependent variable is used both in experimental and non-experimental research.
3. Extraneous variables
Independent variables that are not related to the purpose of the study, but may affect the dependent variable are termed as extraneous variables.[12] Extraneous variables are those uncontrolled variables that may have a significant influence upon the dependent variable. Many research conclusions are invalidated by the influence of these extraneous variables. Extraneous, in this context, does not mean unimportant. Sometimes it is called as nuisance variables. Researchers usually try to control for extraneous variables by experimental isolation, by randomization, or by statistical technical techniques such as analysis of covariance or partial correlation.
4. Confounding variables
When the dependent variable is not free from the influence of extraneous variables, the relationship between the dependent and independent variables is said to be confounded by an extraneous variable(s). Confounding variable is a variable that obscures the effects of another. If the independent variable is confounded with a secondary variable, the experimenter cannot separate the effects of the two variables on the dependent measure.[13]
5. Experimental group and control group
In an experimental hypothesis- testing research when a group is exposed to usual conditions, it is termed a control group but when the group is exposed to some novel or special treatment condition, it is termed an experimental group. The experimental group is the group which receives some treatment in an experiment. The experimental group is exposed to the influence of the factor under consideration. Data collected about subjects in the experimental group are compared with data about subjects in a control group who received no treatment and/or another experimental group who received a different treatment. In true experimental research, participants are randomly assigned to certain conditions -i. e., they have an equal chance of being assigned to either the experimental or the control group.
6. Quantitative and Qualitative studies
A distinction that is often made in the context of measurement is between quantitative and qualitative methods. Quantification has been defined as a numerical method of describing observations of materials or characteristics. The quantitative approach typically involves the reduction of all verbal/nonverbal data to numerical forms and notations.[14] Qualitative research is generally defined as research built around the collection of analysis of the accounts or stories that people offer regarding their experience. Qualitative studies are those in which the description of observations is not numerically expressed in quantitative terms. The data of qualitative research is, therefore, 'words' rather 'numbers'. However, to describe qualitative research merely in terms of an absence of quantification and statistics is to miss the point. The methods used to collect qualitative data are interviews, case studies, open-ended questionnaires, projective techniques, documentary research, and participant observation and so on. The various approaches to analyzing qualitative data are grounded theory analysis, phenomenological methods, and narrative analysis. The quantitative researchers typically use techniques such as surveys, questionnaires, and structured observations. Using statistics, they analyze the information they have collected to see if their ideas about patterns or relationships are supported by the facts as revealed in their research.[15]
7.Probabilistic Equivalence
When we deal with human beings it is impossible to ever say that any two individuals or groups are equal or equivalent. Clearly, the important term in the phrase is "probabilistic". This means that the type of equivalence we have is based on the notion of probabilities. In more concrete terms, probabilistic equivalence means that we know perfectly the odds that we will find a difference between two groups.8. Random Selection[16] & Assignment
Random selection is how you draw the sample of people for your study from a population. Random assignment is how you assign the sample that you draw to different groups or treatments in your study. It is possible to have both random selection and assignment in a study. It is important to randomly select which participants will be included in each group. This ensures that any difference in the outcome will not be due to the selection effects.[17] Random selection is related to sampling.[18] Therefore it is most related to the external validity (or generalizability) of your results. After all, we would randomly sample so that our research participants better represent the larger group from which they're drawn. Random assignment is most related to design. In fact, when we randomly assign participants to the treatments we have, by definition, an experimental design.[19] Therefore, random assignment is most related to internal validity. After all, we randomly assign in order to help assure that our treatment groups are similar to each other (i.e., equivalent) prior to the treatment.
EMPIRICAL RESEARCH DESIGN IN PASTORAL CARE AND COUNSELING
Broadly speaking, research in pastoral care and counseling, like research in other professional fields, is of two kinds: (1) empirical studies[20], which examine actual events of care and counseling (and the human problems to which they are addressed); and (2) theoretical studies, which analyze or construct the concepts and images (e.g. assumptions, metaphors, meanings, values, and causal hypotheses) which define the problems and guide the practice of pastoral care and counseling. It is important to recognize the close connection in principle between these two even though many research studies give a dominant or even exclusive attention to one over the other.[21]
There are basically three Methods of Empirical Research. In pastoral care and counseling, there are three predominant methods of gathering information: the case study, correlation[22], and experimental. All three involve observations of behavior. These methods differ in terms of the research questions they ask, the types of observations that are made, the circumstances surrounding the observations, and how the data from the observations are handled.
There are basically three Methods of Empirical Research. In pastoral care and counseling, there are three predominant methods of gathering information: the case study, correlation[22], and experimental. All three involve observations of behavior. These methods differ in terms of the research questions they ask, the types of observations that are made, the circumstances surrounding the observations, and how the data from the observations are handled.
1. Case studies. In the case study method, an in-depth analysis of a single individual using qualitative terms and concepts is frequently used. The research question may highlight an unusual problem or demonstrate how to work with a particular individual.[23]
2. Correlation studies. The correlation method examines the relationship between two or more variables, quantitatively looking at the extent one variable changes with another variable. The research question is usually stated in the form: “Do variable A and variable B go in the same or opposite direction?” Usually the closer the correlation coefficient is to + 1 or -1 the more statistically significant the findings. This approach is useful for gathering information about how variables relate to each other but does not lend itself to making cause and effect statements.[24] Another popular form of co-relational research used in pastoral care and counseling is an opinion survey. The question asked here is to what extent certain options correlate, or go together with sex, social class, church affiliation, or political affiliation.
3. Experimental studies. The experimental method looks at the quantitative relationship between one or more conditions which are systematically varied and are expected to cause a change in a person’s behavior. This approach represents the greatest degree of control, which in research refers to systematically varying, randomizing, or holding constant the conditions under which observations are made. The purpose of having control within research is to reduce the number of alternative explanations for why and how behavior is influenced. In experimental research, the condition which is directly varied is called the independent variable. The dependent variable is thought to depend on the conditions varied by the experimenter. [25] An experimental hypothesis is a statement about the effect of the independent variable upon the dependent variable.[26] (For example, check the footnote)
CLASSIFICATION OF RESEARCH DESIGN
1. Exploratory or Formulative design (study)
This type of research designs looks for patterns, ideas, or hypotheses, rather than research that tries to test or confirm hypotheses. In any explorative studies, the purpose is to formulate a problem for further study that is to formulate a hypothesis. An exploratory study has other functions also. It increases the researcher's familiarity with a phenomenon that s/he wants to study, or with the situation in which the study is to be done. It also set up priorities for further research, explains more clearly the concepts, and gathers information about the practical possibility of carrying out further research or provides some idea of the problems that are considered most urgent by the people in that field. The exploratory study may also be considered as the first step in a continuous research process. It helps the researcher to design a structured investigation. The purpose of explorative studies is to achieve new insights into a phenomenon. The reason for aiming new insights or ideas is to formulate a more precise problem or to develop hypotheses for further research.
2. Descriptive design (study)
Descriptive research deals with the relationship between variables, the testing of hypotheses, and the development of generalizations, principles, or theories that have universal validity. The descriptive questions need for a frame of reference is fairly obvious.[27] In contrast to the experimental design, the researcher does not manipulate the variables or arrange for events to happen. The process of research goes beyond mere collection and tabulation of data. It is essentially a fact-finding approach, which is related mainly to the present and draws generalizations from a cross-sectional study of the current situation. The description is combined with comparison or contrast, which involves measurement, classification, interpretation, and evaluation to show the significance of what is described. Unlike formulations studies, the descriptive studies presuppose much prior knowledge of the problem to be studied. The descriptive studies deal with the relationship between non-manipulated variables in a natural rather artificial setting. Since the events or conditions have already occurred or exist, the researcher selects the relevant variables for analysis of their relationships. They involve hypothesis formulation and testing and they use logical methods of inductive-deductive reasoning to arrive at generalizations. They often employ methods of randomization.
3. Ex- Post Facto Research Design
The ex-post facto theory developed after data have been analyzed to explain the patterns in the data. Ex-post facto theories are usually consistent with the data but often are simply plausible rather than compelling since more than one ex-post-facto explanation is often consistent with data.[28] Any investigation using existing data rather than new data gathered specifically for the study is known as ex-post facto research design. Causes will be studied after (post) they have had their effect. Therefore, any non- experimental research design that takes place after the conditions to be studied have occurred or such research in which there is a post-test but not pre-test is considered as an 'ex- post facto research design'
4. Experimental Design
Experimental designs are often touted as the most "rigorous" of all research designs or, as the "gold standard" against which all other designs are judged.[29] Experimental design is the blueprint of the procedures that enable the researcher to test hypotheses by reaching valid conclusions about relationships between independent and dependent variables.[30] The experimental design occurs when the investigator manipulates the subjects and conditions (events or situations) to be studied. The key to experimental design is that the investigator assigns subjects to conditions rather than observing in natural occurring. Experimental studies are more powerful than non-experimental studies if one has to study and discover the causal relationship among the variables. Through control and randomization, the potential confounding effects can be removed. Experimenters manipulate certain environmental condition, stimuli, and treatment, and observe how the condition or the behavior of the subject is affected or changed. Selection of the design is based on the purposes of the experiment, the type of variables to be manipulated, and the conditions or the limiting factors under which it is conducted. The design deals with practical problems such as how subjects are to be selected for experimental and control groups, the way the variables are to be manipulated and controlled, the way the extraneous variables are to be controlled, how observations are to be made, and the type of statistical analysis to be employed in interpreting data relationships. The adequacy of experimental designs is judged by the degree to which they eliminate or minimize threats to experimental validity. So also experimental studies become conclusive only when there is direct manipulation and also when the principles of control, randomization, and comparison are used. There are various types of experimental designs such as pre-test- post-test control group design, post-test control group design, single factor multiple group design and so on. A discussion on these is beyond the scope of this paper.
5. Quasi-Experimental Designs
Most experiments in pastoral care and counseling are really what is called quasi-experimental designs. The quasi-quality comes from the inability of the researcher to control fully the scheduling of treatment or exactly who gets treated. The researcher attempts to control other possible influences on the experiment as well as possible and to interpret results in the same manner a true experiment is interpreted.[31] Any experimental situations in which experimenter does not have full control over the assignment of experimental units randomly to the treatment conditions or the treatment cannot be manipulated are called 'quasi-experimental designs. A quasi-experimental design is one that looks a bit like an experimental design but lacks the key ingredient - random assignment.[32]
6. Factorial Design
Most experimental designs encountered in practice have several independent variables and are meant to determine their combined effects on the dependent variable in question. For this, the independent variables are placed into factorial for structure for ease of analysis. [33] These structures can be simple or complex, depending upon the nature and number of variables chosen. Research designs with two or more independent variables or factors, each studied at two or more levels. The goal of the factorial design is to determine whether the factors combine to produce interaction effects. In factorial designs, the influence of more than one independent variable upon more than one dependent variable can be observed. In factorial designs, a factor is a major independent variable.[34] The factorial design has several important features. First, it has great flexibility in exploring or enhancing the “signal” (treatment) in our studies. Whenever we are interested in examining treatment variations, factorial designs should be strong candidates as the designs of choice. Second, factorial designs are efficient. Instead of conducting a series of independent studies we are effectively able to combine these studies into one. Finally, factorial designs are the only effective way to examine interaction effects.[35
7. The survey Method design
In the social research, survey involves collecting information from a large number of people. The data may be elicited face to face interviewing or at a distance by postal questionnaires. There are various types of the interview such as structured interview and ethnographic style interviewing (highly unstructured). The questions may be made of open-ended or closed-ended questions.[36]
8. Cross-Sectional or correlation design
The most common design used in survey research is the cross-sectional design. Using this approach we collect measures from at least two groups of people at once point of time and compare the extent to which the two groups differ on the dependent variable (eg. Level of smoking).[37]
Formulation of a Research Problem or the steps in Research Design
1. Selection of a research area, sensing and formulation of a problem
Research begins with the selection of a general area or topic. The general area/topic to be studied may be suggested by some practical concerns or by some scientific or intellectual interest. The selection of a topic is only a half step forward. The researcher needs to formulate a specific problem. The formulation of a topic into research problem is really the first step in a scientific inquiry. When a problem is observed and we are not sure of its cause or how it happens, then our reflective thinking starts working. The inquisitive mind tries to explore the various dimensions of the phenomenon. Once you have found a general topic or area, the next stage is to narrow down and refine the topic. A useful way to narrow down your topic is to develop a research question from your general topic. Every research starts with a research question. A research question might be "what is the relation between A and B?. A research question has three characteristics. First it should be a question: you need to phrase what you would like study in the form of a question.[38] Second, the research question should propose a relationship between variables that need to be examined.[39] Third, the research question should use terminology that allows it to be tested empirically.[40] Clearly stating the research question is critical, since all subsequent decisions flow from the research question.
2. Evaluating, defining or the statement of the problem
Before the proposed problem can be considered appropriate, several searching questions should be raised. Such as is this the type of problem that can be effectively solved through the process of research, Is the problem significant, Is the problem a new one? or Is the answer already available, are valid and reliable data gathering devices and procedures available, Are pertinent data accessible. Once the problem is located, it must be stated in unambiguous terms. If it is to serve as a guide in planning, investigating and interpreting the results, it is essential that the problem be stated in precise specific terms. The problem may be stated preferably in one sentence and in some cases it is a restatement, in a modified form, of the title.[41] The important independent and dependent variables of the research should be identifiable in the statement of the problem.
3. Formulation of Hypotheses
Once you have narrowed your general topic down to a research question, the next step is to formulate one or more hypotheses[42] from your research question. The Characteristics of the hypothesis are observation, reflection, deduction, and verification. A hypothesis is a postulated connection between two or more variables. It can be descriptive or causal.[43] The hypotheses may be based upon past experience, informal observation, or information gained from others. The research hypothesis is a formal affirmative statement predicting a single research outcome, a tentative explanation of the relationship between two or more variables. It limits the focus of the investigation to a definite target and determines what observations are to be made. The research hypothesis is a predictive statement that relates an independent variable to a dependent variable. Usually, a research hypothesis must contain at least, one independent and one dependent variable. Formulation of a hypothesis gives the definite point to the inquiry, aids in establishing the direction in which to proceed.
In a test of hypothesis, two different hypotheses are laid down. These two hypotheses are known as the null hypothesis and alternative hypothesis. The null hypothesis is denoted by Ho and the alternative hypothesis by H1. Null hypotheses are formulated on the basis of theoretical background and our own previous casual observations. Before we start our research, we start with an assumption of a correlation. We are not at this stage sure about the existence or non-existence of a correlation between two factors. e.g., stress and education or study habits and examination results. In its simplest form null hypothesis states that there is no significant difference between the two groups with respect to some characteristics. The null hypothesis is akin to the legal principle that a man is innocent until he is proved guilty. It constitutes a challenge and the function of a research is to give facts a chance to refute this challenge.
The null hypothesis can be defined as a statistical hypothesis, which is stated for the purpose of possible acceptance. A null hypothesis is an original hypothesis. Any hypothesis other than a null hypothesis is called an alternative hypothesis. So when the null hypothesis is rejected we accept the alternative hypothesis. The research hypothesis is another term for the alternative hypothesis. An alternative hypothesis is that one hopes indirectly to substantiate by rejecting the null hypothesis. The alternative hypothesis is the logical opposite of the null hypothesis. Rejecting the null hypothesis shows that the alternative or research hypothesis may be true. Therefore, the null hypothesis is a hypothesis that the investigator hopes to reject, and thereby substantiating its opposite. The alternative hypothesis and null hypothesis together constitute the framework for the statistical testing of the hypothesis. An alternative hypothesis may be stated as males are more adjusted than females (H1) the null hypothesis may be stated as the males and females do not differ in adjustment (Ho).
CONCLUSION
In this paper, I have briefly discussed the important steps in a research design, the steps involved in test construction, a brief description of the terms/concepts in research design and the guidelines for presenting a research report. This will serve as a background for the understanding of the basic principles of empirical research design in social science.
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Webiliography and CDROM
Http://www.socialresearchmethods.net/kb/constval.php.9/8/2007 9:27 PM.
Florell, J. L., “Empirical research in pastoral care and counseling” Dictionary of Pastoral Care and Counseling, p.354 CDROM
Unpublished Material
Jacob Cherian, “Empirical Research Methods”, unpublished materials, Thomas Mar Athanacious Institute of counseling and Research Center, Amalagiri, Kottayam, 2005.
[1] Research in social science is of two kinds: empirical studies and theoretical studies. Empirical research is a systematic investigation aimed at finding new or substantiating facts (or factors) that help further the understanding of a problem or problems and the rules or interactions that govern them. While empirical studies examine the actual events of the human situation, theoretical studies analyze or construct the concepts and images which define the problems.
[4] Jospal Singh, Methodology and techniques of social research, New Delhi: Kanishka Publishers, distributors, 2001, p.183.
[5] Jospal Singh, Methodology and techniques of social research, p.183.
[6] John W. Creswell; Qualitative inquiry and Research design choosing among five approaches (second Edition), New Delhi: Sage Publications, 2007, p41.
[7] John W. Creswell; p42.
[8] John W. Creswell; p42.
[5] Jospal Singh, Methodology and techniques of social research, p.183.
[6] John W. Creswell; Qualitative inquiry and Research design choosing among five approaches (second Edition), New Delhi: Sage Publications, 2007, p41.
[7] John W. Creswell; p42.
[8] John W. Creswell; p42.
[13] The best way to describe confounding variable is with an example. Suppose the investigator is interested in determining the relationship between life satisfaction scores and family income among the clergy. The problem is that life satisfaction scores are probably related to confounding with education level. It would be difficult to determine whether life satisfaction or education was the crucial variable if a relationship was found. Suppose clergy with D.Th tended to get better appointments and also tended to have higher scores. It would follow necessarily that life satisfaction is the crucial factor. Perhaps it is just the D.Th status, independent of achievement that resulted in better employment and more income.
[19] http://www.socialresearchmethods.net/kb/constval.php.9/8/2007 9:27 PM.[20] Empirical research is a systematic investigation aimed at finding new or substantiating facts and relationships between facts (or factors) that help further the understanding of a problem or problems and the rules or interactions that govern them.
[21] J. L. Florell “Empirical research in pastoral care and counseling” Dictionary of Pastoral Care and Counseling, p.354 CDROM
[21] J. L. Florell “Empirical research in pastoral care and counseling” Dictionary of Pastoral Care and Counseling, p.354 CDROM
[22] Co-variation of variables where values of one variable differ systematically by values of another variable, the variables are correlated or associated. Correlation does not prove causation.
[23] J. L. Florell,“Empirical research in pastoral care and counseling”, Dictionary of Pastoral Care and Counseling, p.354 CDROM
[24] J. L. Florell, “Empirical research in pastoral care and counseling “Dictionary of Pastoral Care and Counseling, p.354, CDROM
[25] J. L. Florell, “Empirical research in pastoral care and counseling”, Dictionary of Pastoral Care and Counseling, p.355, CDROM
[23] J. L. Florell,“Empirical research in pastoral care and counseling”, Dictionary of Pastoral Care and Counseling, p.354 CDROM
[24] J. L. Florell, “Empirical research in pastoral care and counseling “Dictionary of Pastoral Care and Counseling, p.354, CDROM
[25] J. L. Florell, “Empirical research in pastoral care and counseling”, Dictionary of Pastoral Care and Counseling, p.355, CDROM
[32] Reprinted from Trochim, W. (Ed.), (1986). Editor's Notes. Advances in quasi-experimental design and analysis. New Directions for Program Evaluation Series, Number 31, San Francisco, CA: Jossey-Bass. Cited in. http://www.socialresearch methods. net/kb/constval.php.9/8/2007 9:27 PM.
[36] An open ended question is one which does not limit the answer to a yes, a no or a range of set alternatives. The closed-ended question have the opposite advantages and disadvantages of having a binary choice or multiple choice. Eg. Strongly approve, Approve, Neutral disapprove< strongly disapprove!
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