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Preface This foundation manual was developed for the use of graduate and post graduate research scholars of the Agricultural Extension/ Extension Education/ Rural Development. In this book we have made an attempt to clearly illustrate the fundamental concepts related to the aspect of social research in the context of Extension Education. In order to ease the understanding of basic concepts, widely used simplest research methods and tools and techniques of data collection, we have divided the book into four parts, Foundations of social research, Research methods, Tools and techniques of data collection and Data processing and report writing.  Foundations of social research deals with universal and basic units of social research like scientific approach, meaning, process and development of scientific research problem. It also deals with defining and measurement of variables and testing of reliability and validity of measuring instruments. In this manual attempts are made to illustrate these concepts with the relevant examples. Research Methods section deals with the three major research methods used in extension education/ Agricultural extension, namely Survey research, Action research and case study. This section discusses in detail the process, relative advantages and limitations of each of these three methods. There are numerous research methods used in social research. Rather than discussing all these research methods in brief, we made an attempt to discuss in detail the most widely used research methods in the field of agricultural extension.

Term ‘Scientific research’ is too broad to be explained by using one or two definitions. One should go through the different expert views about scientific research in order to internalize the concept of scientific research. In essence a scientific research is characterized by its rigor, testability, replicability, precision, confidence, objectivity, generalizability and parsimony. Research: Uma Sekaran (2006) defined research as an organized, systematic, data-based, critical, objective, scientific inquiry or investigation into a specific problem, undertaken with the purpose of finding answers or solutions to it.

Rationally selected and contextually defined research problem is the foundation to the successful research project. If the selected research problem is not in line with the interests of the researcher, available time, resources, infrastructure & knowledge base then achieving success in research process remains highly uncertain. Consequently, in addition to hindering of professional growth of the researcher, it also results in wastage of time, money and human effort. Most importantly, it may sometimes add up incorrect knowledge into scientific base, hindering the process of scientific progress. Hence the identification of the research problem and designing the problem statement is the most important step in the research process.

Whenever we design a scientific study it is designed in a specific contextual background to solve one or another scientific problem. Subsequently it also involves a set of variables/phenomenon operating in a particular context, set of relationships among these variables and the conditions under which they operate. Certainly, to address an unsolved scientific problem we need to carry out research by employing well defined research methodology and have an idea about possible outcomes.  For example when a extension scientist is asked to study the impact of a novel programme, he needs to understand the background and the context under which the programme was introduced, what are the developmental inputs given under the programme, to whom, when (variables), with what purpose (context), what kind of impact he/she is supposed to investigate (presumed relationship), what methods he is going to use to investigate the impact of developmental programme (research methodology) and what are the possible outcomes of the investigation and how programme interventions are related to the outcome (relationship).

Most of the scientific research studies –except few descriptive survey research studies–will have one or more hypotheses to be tested as a part of study. Hypothesis is a prediction intended to be tested in a research study (Aron, Coups, and Aron, 2012). Hypothesis is the guide which directs the purpose and process of research by indicating the dependent and independent variables to be observed, extraneous variables to be controlled and the active variables to be manipulated.

Variable is any character or attribute of the given object/set of objects which varies from object to object or from one point of time to another point of time. For example height of individuals is a variable; it varies from person to person.  Kerlinger (1973) defined variable as a symbol to which numerals or values are assigned. Importance of variables: In previous sections, we discussed about formulating the research problem and development of research hypothesis. Variables are the building blocks of any scientific research problem and research hypothesis. When we consider a hypothesis to be relational hypothesis, we mean that it make claims about relationship between two or more variables. When we test hypothesis, as such we do not test the hypothesis, rather we test the significance of hypothesised relationship between two or more variables. Since variables play central role in observation, measurement and testing of relationship, it is of prime importance to understand the meaning of variables, different types and the way we define these variables.

There can be no scientific studies which do not involve the process of measuring. Measurement process is the integral part of research activity. Measurement can be defined as the assignment of numerals to the objects or events according to set of rules.  The emphasis in this definition is on phrase ‘set of rules’. If the rules can be set up based on some rational or empirical basis, then theoretically anything can be measured. It is very much easy to understand the concept of measurement in case of physical sciences (Example weight, length, mass etc.) but it is harder understand the concept of measurement in case of psychological objects/phenomenon (intelligence, aggressiveness, attitude etc.) without understanding the predetermined rules of measurement. A rule is a guide, command that tells you what to do/how to do.

Reliability deals with the dependency, consistency, stability, predictability and accuracy of the research data. In our day to day life, when we say that a person is reliable then it means his behaviour is predictable, his behaviour (the way he behaved in past, he is behaving now and the way he will behave in future) will be consistent and he is dependable. On other hand an unreliable person’s behaviour is unpredictably variable and he cannot be depended upon.

In previous section, we discussed about the concept of the reliability and its importance. In this section, we will discuss about different types of reliability and procedures for estimation of the reliability. We already discussed that one cannot measure the reliability but of course it can be estimated.

Reliability aims at assessing the accuracy and consistency of whatsoever the measuring instrument measures irrespective of whether we are measuring what we are supposed to measure or not. Whereas the validity emphasises on the question “are we measuring what we were supposed to measure?” To clarify the difference between reliability and validity, let us take an example of instruments that measure colour intensity. Assume, an expert develops two separate instruments X and Y to measure the intensity of green and red colour, respectively. But, the commercial manufacturer wrongly tags the red colour measuring instrument as X. When someone uses this wrongly tagged instrument for measuring the green colour intensity, whatever intensity values the instrument yields are reliable but not valid. It is so because the instrument is measuring red colour intensity accurately (hence data is reliable) but it is not measuring what it was supposed to measure –the green colour intensity (hence data is not valid).

In previous sections we discussed about the validity and estimation of validity. Now the question is whether the reliable and valid measuring instrument is sufficient condition to ensure the reliable and valid results in actual experiments? What if the measuring instruments are perfectly reliable and valid but the experiment is conducted in less controlled conditions? Can we expect accurate predictions under such conditions? The answer is No.

In previous section we discussed about the ability of the research design to precisely detect the relationship between cause and effect under controlled conditions. But in social research it becomes difficult to conduct the research under highly controlled conditions and moreover many of the researches in social science aim at prediction rather than understanding. As we discussed earlier, aim of science is development theory, understanding, prediction and explanation of natural phenomenon. In many of the cases we are more interested in predicting the occurrence of social phenomenon rather than explaining it or understanding its relationship with other phenomenon. Under such conditions internal validity is of less use because a relationship that is established in artificially controlled conditions (with high internal validity) may fail to express itself in natural setup due to effect of extraneous variables. When the relationship between cause and effect is weak enough to be expressed in natural setup then it is of less use in predicting the phenomenon. Under such conditions we require experiments that are conducted in nearly natural setup, so that we can generalize the findings of the research to the wider domain.

Sampling is the process of drawing a part of population supposed to be the representative of that population. Types: Sampling process can be either random or non-random. Most frequently we use random sampling method in our studies. But sometimes the purpose of the study demands for non-random sampling in one or other phase of sampling (Example: When we want to study the impact of life skills development programme on the disabled female beneficiaries)

Not all the scientific problems demand the detection and establishment of causal relationship among natural phenomenon. Many of the social research problems seek to study the status quo rather than the relation between two or more natural phenomenon. Few of the impact assessment studies (which are kind of causal relationship studies to an extent) also demand for knowing the status quo before and after implementation of interventions. Many other studies demand for benchmark assessment to make policy decisions. Under such circumstances, survey research is a useful research method.

Every practical problem need not have a documented solution. Most of the times to solve a practical problem, we need to apply our experience, creativity and experiment with the novel solutions in order to address the problem which have no readymade solution. Under such circumstance, we will apply our knowledge and experience in selecting, planning, experimenting and evaluation of the possible solutions. This type of problem solving approach involves action research.  Action research is a type of social research that aims at gaining an insight into the problem by learning from experiences gained in an effort to solve the problem. Here, action itself is a source of knowledge.

Quantitative studies are preferred over qualitative studies for their relatively higher objectivity. But many of the times, complexities involved in the occurrence of phenomenon, its causes, and consequences demand for in-depth analysis of a single unit of study. Whenever we want to study a single unit in depth both qualitatively and quantitatively then case study is the best method of research. Case study is a best tool to use, when we are interested in exploring a new phenomenon on which there is very less scientific information available and also when we are interested in formulating new hypothesis for causal study.

Scientific research is always based on observable and measurable facts. This applies to physical as well as humanitarian fields of science. In order to investigate social or psychological phenomenon, most of the times we need quantified information related to the phenomenon under investigation. In order to secure this data, we need one or more method/ means of collecting observable/measurable data.

Interview method: It is a two way interactive (either face-to-face or through multimedia technology), method of data collection wherein the researchers elicit required response from the respondent by presenting stimulus in the form of series of questions pertinent to it. Interview schedule: It is a data collection tool consisting of properly worded, sequentially arranged questions, tests relevant to objective of research.

t is the method of gathering the data by seeing, hearing and then recording the observation on the phenomenon/behavior of the respondent rather than the subjects’ self-reporting of the response.

Communication material is the joint product of knowledge, skill and attitude base of the communicator. Further, most of the communication done on behalf of certain organization also reflects the objective, work culture, strategy and contribution of the organization. Hence analysis of communication material is of greater relevance in exploring the trends, vision, behavior and future course of action. In this chapter, we are going to discuss the content analysis; it’s meaning and practical application.

Existing positive as well as negative interactions among the members of the society determine the communication structure, leadership and technology diffusion pattern within the given social system. Sociometry is a method for gathering and analyzing data on communication choice and interaction pattern of individuals, within a group in order to identify communication structure and pattern.

It is not possible that every respondent is willing to and capable of giving honest and true response. Sometimes, it is practically not possible to make the respondent reveal about personal information, but true research requires true response. When direct stimuli fail to elicit true response, then we must use indirect and extractive methods to elicit the required response indirectly from the respondents, which further can be interpreted in the relevant format. This indirect and ambiguous stimulus based methods are known as projective methods. Projective methods are technique of data collection on the person, value, attitude, emotions and motives etc. by using a highly unstructured and ambiguous stimulus (Wilkening, Wilkening & Wilkening, 1973).

Data collected by using different data collection methods remain meaningless until it is screened, cleaned, coded, analyzed and summarized. Data cleaning and screening mostly come under the purview of statistical logics and techniques hence not dealt with in this practical guide. Since these aspects will be dealt by the statistical experts from the allied statistical wings. Presuming that students are aware about data cleaning and screening, we will proceed further with data coding.

Hypothesis testing is the statistical procedure used in order to accept or reject statistical null hypotheses. One of the major purpose for which we formulate the hypothesis is, to test the statistical significance of the relation, difference or variation etc. among given sample/s at a given point of time or at different time points.

Based on the nature and purpose of the content, there are numerous classes of scientific communications. Theses represent the class of research communications that are of great importance to the students. Thesis is part and parcel of the master’s and doctoral programme in almost every academic institution. In some institutions, even the bachelor students are expected to submit their brief report on project.