Government declares hike in Research scholar stipend. Scholars disappointed


After continuous protests claiming modification of stipends for research scholars, the government finally announced a hike in the monthly payments of the research fellows. Junior research fellows will now get Rs 31,000 p.m. and Senior research fellows will get 35,000 p.m., a hike of roughly 20%. Stipends for Research Assistants would now range from Rs 47,000 to Rs 54,000 p.m. This is the lowest increase in stipends since 2010. The research scholars are apparently disappointed with the sanctioned hike and have said that they would continue their ongoing protest against the insignificant increase in stipends.

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Measurement in Research

The core of any research is measurement. It can be defined as the method of assigning numbers to things. It is essential in research as everything has to be reduced to numbers.

Assigning numbers to properties of things is easy. However, it is quite difficult in other cases. Measuring social conformity or intelligence is much complex than measuring weight, age or financial assets, which can be directly measured directly with some standard unit of measurement. Measurement tools of abstract/qualitative concepts are not standardized, and the results are not very accurate.

A clear understanding of the level of measurement of variables is important in research because it is the level, which determines what type of statistical analysis has to be conducted. The collected data can be classified into distinct categories. If there are limited categories, then they are known as discrete variables. If there are unlimited categories, they are known as continuous variables. The nominal level of measurement describes these categorical variables. Nominal variables include demographic properties like sex, race, religion, etc. This is considered as the most basic level of measurement. No ranking or hierarchy is present in this level.

The variables that can be sequenced in some order of importance can be described by the ordinal level. Opinions and attitude scales or indexes in the social sciences are ordinal in nature. Ex.: Upper, middle, and lower class. In this case, the order is known; however, the interval between the values is not meaningful.

Variables that have more or less equal intervals are described by the interval level of measurement. Crime rates come under this measurement level. Temperature is also an interval variable. Here, the interval between variables can be interpreted; but, ratios are not meaningful.

Ratio level describes variables that have equal intervals and a reference point. Measurement of physical dimension such as weight, height, distance, etc. falls under this level.


Techniques Involved in Defining a Problem

As a researcher, you must have often read that defining a problem is the first step in a research process. But, have you ever wondered what is meant by defining a problem. Well, it simply means that the researcher has to lay down certain boundaries within which he/she has to study the problem with a pre-defined objective in mind.

Defining a problem is a herculean task, and this must be done intelligently to avoid confusions that arise in the research operation. Try to follow the below steps systematically to best define a problem:

 i.  State the problem in a general way:

First state the problem in general terms with respect to some practical, scientific or intellectual interest. For this, the researcher may himself read the concerned subject matter thoroughly or take the help of the subject expert. Often, the guide states the problem in general terms; it depends on the researcher if he/she wants to narrow it down to operational terms. The problem stated should also be checked for ambiguity and feasibility.

ii.  Understand the nature of the problem:

The next step is to understand the nature and origin of the problem. The researcher needs to discuss the problem with those related to the subject matter in order to clearly understand the origin of the problem, its nature, objectives, and the environment in which the problem is to be studied.

iii. Survey the available literature:

All available literature including relevant theories, reports, records, and other relevant literature on the problem needs to be reviewed and examined. This would help the researcher to identify the data available, the techniques that might be used, types of difficulties that may be encountered during the study, possible analytical shortcomings, and even new methods of approach to the present problem.

iv.  Go for discussions for developing ideas:

The researcher may discuss the problem with his/her colleagues and others related to the concerned subject. This helps the researcher to generate new ideas, identify different aspects on the problem, gain suggestions and advices from others, and sharpen his focus on certain aspects within the field. However, discussions should not be limited to the problem only, but should also be related to the general approach to the problem, techniques that might be used, possible solutions, etc.

v.  Rephrase the research problem into a working proposition:

Finally, the researcher must rephrase the problem into a working proposition. Rephrasing the problem means putting the problem in specific terms that is feasible and may help in the development of working hypotheses. Once the researcher has gone through the above steps systematically, it is easy to rephrase the problem into analytical and operational terms.


Selecting the Problem/Subject of Research

The undertaken research problem must be thoroughly selected. For this purpose, the help of a research guide can also be taken. However, since research problems cannot be usually borrowed, each and every researcher must therefore strive to find out his research problem for the study. While buying a new pair of spectacles, we need to cooperate with the optician along with our own preferences in deciding the power of lens. Similarly, a research guide can, at the most, only help the researcher to choose a subject. However, the following points can be observed by the researcher while selecting a research problem/subject:

i.  Generally, the subject, which is overdone, is avoided, as it will be a hard and complex task to throw any new light on such a case that has already been done. Controversial subject should not become the choice of an average researcher. Moreover, too narrow or too vague problems should be avoided.

ii.   The selected research subject should be practical and realistic, so that the related research material/sources are easily available within one’s reach. However, sometimes, even after this it remains still quite difficult to supply absolute ideas regarding how a researcher should acquire the necessary ideas for his research. Thus, for this purpose the researcher should definitely contact an expert or a professor, in the University, who is already occupied in a research. Besides, he may read articles on the subject published in literature and may also get the notions about how the techniques/ideas discussed therein might be functional in obtaining the solutions of other problems. Moreover, he may discuss what he has in his mind, concerning a problem, with others as well. By this way, he should be absolutely successful in selecting a problem by putting his best efforts.

iii.   Some of the other criteria, which must also be considered while selecting a problem, are: importance of the subject, qualifications and training of the researcher, costs involved, and the time factor. In other words, before selecting a problem, the researcher must ask himself the following questions:

  1. Is he well equipped, concerning his background, to conduct the research?
  2. Does the research/study come within the budget he can afford?
  3. Can the necessary cooperation be obtained from those who must participate in the research as subjects?

In case, the answers to all of the above mentioned questions are positive, one may become confident concerning the practicability of the study.

iv.  A preliminary study should most certainly precede the selection of a problem. However, this won’t be necessary regarding the problem needs the conduct of a research closely similar to the one, which has already been conducted. But, usually a brief feasibility study must be undertaken, when the field of inquiry is reasonably new and lacks the availability of a set of well developed techniques.

In conclusion, when the research subject is selected appropriately, by conforming to the above mentioned points, the research will, most probably, not be a boring drudgery. Rather, it will be exciting and educating. The selected subject/problem must involve the researcher and be the prime priority in his mind, so that he may give his best shot required for the study.


Problems Encountered by Researchers in India

Lack of Scientific Training: The research methodology is not systematic. Many researchers undertake research work without having actual knowledge of the research methods. They just look for similar studies and copy the methodologies listed in it. Even the research guides do not have a thorough knowledge of the various methodologies. This scenario warrants the need for some sort of short-term training to be imparted to researchers prior to undertaking research activities.

Insufficient Interaction: There is no proper interaction between researchers and the business establishments, government institutions, etc. This leads to a great deal of data going untapped. Interaction programs should be organized between researchers and other institutions on a regular basis. This will highlight what issues need to be researched, what data is required for conducting research, and how the study will be useful.

Lack of Confidence: Most of the business establishments are of the opinion that, researchers can misuse the data provided by them. As such, they are reluctant to divulge details of their company. This affects the research studies for which that particular data may be of utmost importance. Thus, confidence-building measures should be adopted, which will convince the business units that their data will be put to productive purposes, and will not be misused in any manner by the researcher.

Lack of Code of Conduct: No specific code of conduct exists for the researchers, which leads to inter-departmental and inter-university rivalries.

Inadequate Assistance: Researchers in India have to cope with the non-availability of adequate and timely secretarial assistance, which affects the schedule of their research study.

Improper Library Management: The libraries are not managed systematically. Much of the precious time of the researchers is spent in looking for books, reports, newspapers, etc. rather than searching relevant information from them.

High Cost of Publishing: Once their research is completed, the researchers have to look for a means to publish it. Publishing in international journals is highly expensive. This discourages most of the researchers from taking up research work.


Criteria of Good Research

Although the research works and studies differ in their form and kind, they all still meet on the common ground of scientific methods employed by them. Hence, scientific research is expected to satisfy the following criteria:

i.  The aim of the research should be clearly mentioned, along with the use of common concepts.

ii.  The procedures used in the research should be adequately described, in order to permit another researcher to repeat the research for further advancement, while maintaining the continuity of what has already been done.

iii.  The researchs procedural design should be carefully planned to obtain results that are as objective as possible.

iv.  The flaws in the procedural design should be sincerely reported by the researcher to correctly estimate their effects upon the findings.

v.  The data analysis should be adequate to reveal its significance.

vi.  The methods used during the analysis should be appropriate.

vii.  The reliability and validity of the concerned data should be checked carefully.

viii. The conclusions are needed to be confined and limited to only those data, which are justified and adequately provided by the research.

ix.  In case, the researcher is experienced and has a good reputation in the field of research, greater confidence in research is warranted.


In other words, we can state the qualities of a good research” as following:

1)  Systematic - This states that the research is structured with some specified steps, which are to be followed in a specified sequence, according to the well defined set of rules. Systematic characteristic of the research does not actually rule out creative thinking, but it does discourage the use of guessing and intuition in order to arrive at conclusions.

2)  Logical - This states that the research is guided by the rules of logical reasoning, and that the logical process of induction and deduction are essential while conducting a research. Induction is the process of reasoning from a part to the whole; while, deduction is the process of reasoning from some premise to a conclusion that follows from that very premise. Besides, logical reasoning enables the research to be more meaningful in the context of decision making.

3)  Empirical - This states that the research is basically related to one or more aspects of a real situation. Moreover, it deals with the concrete data, which provides a base for the external validity of research results.

4) Replicable - This states that the research results should be allowed verification by replicating their study, to thus build a sound basis for decisions.



Among all the previously discussed sampling techniques, the most widely and effectively used techniques include Deliberate Sampling and Simple Random Sampling.

1. Deliberate Sampling

It is a kind of non-probability sampling that involves the selection of components based on factors excluding random chance. This type of sampling involves the chance of unequal selection of members of the population. Hence, it is not reliable to assume that the sample represents the target population completely, as it might be possible that the researcher intentionally chose the individuals to participate in the study.

Deliberate sampling method is useful for case studies, pilot studies, qualitative research, and hypothesis development. This sampling technique is generally applied in studies, which are not interested in the parameters of the total population. For example, if you are interested to find out the particular reaction of some students on the devaluation of the rupee, then instead of asking the opinions of all students in various college/universities of Delhi, you may deliberately ask only the student leaders of a particular college/university.

Deliberate sampling method is more preferred as it is easy, quick, and cost-effective. However, the findings of the sample survey cannot be universal to the entire population as the sample is not representative. Since there is no set criterion for sample selection, there is a scope for research being persuaded by the preference of the researcher.

2.  Simple Random Sampling

It is a kind of probability sampling, which provides each member of the population with a calculable and non-zero probability of selection in the sample. Since every member is given an equal chance of being selected, this type of sampling is thus considered as a reliable way of selecting a sample from a given population.

The benefits of simple random sampling can be obtained when the target population size is small, homogeneous, and not much information is available regarding the population. For example, if we have a list of 70 heads of households, each having a unique number. We want to select 30 random households from this list. By the help of a random number table, we select consecutive 2-digit numbers from the table. If a random number matches a household’s number, then that household will be added to the list of selected households. Similarly, if a random number does not match a household’s number (e.g., if it is greater than 70), then it is not added to the list of selected households. Each random number that is used is crossed out to avoid repetition. In this way, we continue to select households until we have 30.

Simple random sampling is quite advantageous as it is free of classification error and needs minimum innovative knowledge of the population. However, this sampling method is usually not preferred as it becomes crucial to list every item in the population prior to the sampling and requires a huge sampling frame, which can result in massive sampling calculations and extreme costs.


Types of Sampling

Sampling can be basically categorized into probability and non-probability sampling. In probability sampling, each and every element of the population has a probability of being selected in the sample, i.e., the probability can be accurately measured. Whereas, in non-probability sampling, not all elements have a chance of being selected in the sample, i.e., their probability cannot be accurately measured.

The commonly used sampling methods are given below:

»  Deliberate sampling: It is a non-probability sample design in which the researcher purposively or deliberately selects certain units of the universe to form a sample that would represent the universe. In other words, it is a sampling with a purpose. It is also known as purposive sampling.


»  Simple random sampling: It is a probability sample design where each and every element has an equal probability of being selected in the sample. It is also known as chance sampling.


»  Systematic sampling: In this method, elements from a large population are selected at periodic intervals according to a random starting point, i.e., every nth element is selected for the sample, where n can be any random position of an element.


»  Stratified sampling: In this method, the researcher divides the entire population into different subgroups or strata, and then randomly selects elements proportionally from the strata to include in the sample.


»  Quota sampling: It is a non-probability sample in which the researcher selects random units for a sample according to certain given criteria or quota. In other words, elements are selected according to pre-specified criteria in such a way that the sample represents the same characteristics of the population under study.


Preparing the Research Design

Once the research problem has been identified, the next task for the researcher is preparing the research design. According to Russell Ackoff, “research design is the process of making decisions before a situation arises in which the decision has to be carried out.” It is the conceptual framework within which the research would be carried out. It is a key aspect as it binds the research project together. Its aim is to provide for the collection of relevant information with minimal expenditure of effort, time and money.

But, whether this can be achieved depends upon a large extent on the research purpose, which is classified into four categories: (i) Exploratory; (ii) Description; (iii) Diagnosis; and (iv) Experimentation. For an exploratory research study, a flexible research design is more appropriate as it provides ample scope for researching various aspects of a problem (E.g.Types of vehicles suitable for the Indian market. This topic provides extensive scope for writing). For a research paper, which requires an accurate description, the research design should be formulated in such a way that, it is unbiased and vouches for the reliability of the collected data and analyzed (E.g.: Percentage of small car segment in Indian market. This topic needs accurate facts and figures).

There are various kinds of research designs, such as, experimental (independent variable is manipulated) and non-experimental (independent variable is not manipulated) hypothesis-testing. Experimental designs can be further grouped into informal and formal. Informal experimental design normally uses a less sophisticated form of analysis. It includes: before and after without control design; after only with control design; before and after with control design. Formal experimental design offers relatively more control and uses precise statistical procedures for analysis. It includes: completely randomized design; randomized block design; Latin square design; and factorial designs.

Important factors to remember while preparing the research design:

  • Objectives of the research study;
  • Means of obtaining the information;
  • Tools for data collection;
  • Data analysis (qualitative and quantitative);
  • Time available for each stage of the research; and
  • Cost involved for the research.

A well-planned research design serves as a blueprint for the researcher even before he actually starts working on his research. This helps him to decide his course of action during various stages of the research, thus saving his time and resources.


Development of working hypothesis

After an extensive literature survey, a researcher should state in clear terms the working hypothesis or hypotheses. Working hypothesis is tentative assumption made in order to draw out and test its logical or empirical consequences. As such the manner in which research hypotheses are developed is particularly important since they provide the focal point for research. They also affect the manner in which tests must be conducted in the analysis of data and indirectly the quality of data which is required for the analysis. In most types of research, the development of working hypothesis plays an important role. Hypothesis should be very specific and limited to the piece of research in hand because it has to be tested. The role of the hypothesis is to guide the researcher by delimiting the area of research and to keep him on the right track. It sharpens his thinking and focuses attention on the more important facets of the problem. It also indicates the type of data required and the type of methods of data analysis to be used.