QUESTION : 1. Describe 'sampling techniques' and explain various kinds of sampling techniques. What are the advantages and disadvantages of using sampling method while conducting research?
QUESTION : 2. What are the conditions required to formulate a Research Design?
QUESTION : 3. What is the questionnaire method? What are the requirements of a good questionnaire? Examin
e the merits and demerits of the questionnaire method.
QUESTION : 4. Explain Doctrinal and Non-Doctrinal Research?
QUESTION : 5. Explain various methods of teaching.
LEGAL EDUCATION AND RESEARCH METHODOLOGY
QUESTION : 1. Describe 'Sampling techniques' and explain various kinds of sampling techniques. What are the advantages and disadvantages of using sampling method while conducting a research?
Sampling Methods | Types, Techniques & Examples
When you conduct research about a group of people, it’s rarely possible to collect data from every person in that group. Instead, you select a sample. The sample is the group of individuals who will actually participate in the research.
To draw valid conclusions from your results, you have to carefully decide how you will select a sample that is representative of the group as a whole. This is called a sampling method. There are two primary types of sampling methods that you can use in your research:
Probability sampling involves random selection, allowing you to make strong statistical inferences about the whole group.
Non-probability sampling involves non-random selection based on convenience or other criteria, allowing you to easily collect data.
You should clearly explain how you selected your sample in the methodology section of your paper or thesis, as well as how you approached minimizing research bias in your work.
Population vs. sample
First, you need to understand the difference between a population and a sample, and identify the target population of your research.
The population is the entire group that you want to draw conclusions about.
The sample is the specific group of individuals that you will collect data from.
The population can be defined in terms of geographical location, age, income, or many other characteristics.
Population vs sampleIt can be very broad or quite narrow: maybe you want to make inferences about the whole adult population of your country; maybe your research focuses on customers of a certain company, patients with a specific health condition, or students in a single school.
It is important to carefully define your target population according to the purpose and practicalities of your project. If the population is very large, demographically mixed, and geographically dispersed, it might be difficult to gain access to a representative sample. A lack of a representative sample affects the validity of your results, and can lead to several research biases, particularly sampling bias.
Sampling frame
The sampling frame is the actual list of individuals that the sample will be drawn from. Ideally, it should include the entire target population (and nobody who is not part of that population).
Probability sampling methods
Probability sampling means that every member of the population has a chance of being selected. It is mainly used in quantitative research. If you want to produce results that are representative of the whole population, probability sampling techn iques are the most valid choice.
1. Simple random sampling
In a simple random sample, every member of the population has an equal chance of being selected. Your sampling frame should include the whole population. To conduct this type of sampling, you can use tools like random number generators or other techniques that are based entirely on chance.
2. Systematic sampling
Systematic sampling is similar to simple random sampling, but it is usually slightly easier to conduct. Every member of the population is listed with a number, but instead of randomly generating numbers, individuals are chosen at regular intervals.
3. Stratified sampling
Stratified sampling involves dividing the population into subpopulations that may differ in important ways. It allows you draw more precise conclusions by ensuring that every subgroup is properly represented in the sample.
To use this sampling method, you divide the population into subgroups (called strata) based on the relevant characteristic (e.g., gender identity, age range, income bracket, job role).
Based on the overall proportions of the population, you calculate how many people should be sampled from each subgroup. Then you use random or systematic sampling to select a sample from each subgroup.
4. Cluster sampling
Cluster sampling also involves dividing the population into subgroups, but each subgroup should have similar characteristics to the whole sample. Instead of sampling individuals from each subgroup, you randomly select entire subgroups.
If it is practically possible, you might include every individual from each sampled cluster. If the clusters themselves are large, you can also sample individuals from within each cluster using one of the techniques above. This is called multistage sampling.
This method is good for dealing with large and dispersed populations, but there is more risk of error in the sample, as there could be substantial differences between clusters. It’s difficult to guarantee that the sampled clusters are really representative of the whole population.
Non-probability sampling methods
In a non-probability sample, individuals are selected based on non-random criteria, and not every individual has a chance of being included.
This type of sample is easier and cheaper to access, but it has a higher risk of sampling bias. That means the inferences you can make about the population are weaker than with probability samples, and your conclusions may be more limited. If you use a non-probability sample, you should still aim to make it as representative of the population as possible.
Non-probability sampling techniques are often used in exploratory and qualitative research. In these types of research, the aim is not to test a hypothesis about a broad population, but to develop an initial understanding of a small or under- researched population.
Non probability sampling
1. Convenience sampling
A convenience sample simply includes the individuals who happen to be most accessible to the researcher.
This is an easy and inexpensive way to gather initial data, but there is no way to tell if the sample is representative of the population, so it can’t produce generalizable results. Convenience samples are at risk for both sampling bias and selection bias.
Example: Convenience sampling
You are researching opinions about student support services in your university, so
after each of your classes, you ask your fellow students to complete a survey on the topic. This is a convenient way to gather data, but as you only surveyed students taking the same classes as you at the same level, the sample is not representative of all the students at your university.
2. Voluntary response sampling
Similar to a convenience sample, a voluntary response sample is mainly based on ease of access. Instead of the researcher choosing participants and directly contacting them, people volunteer themselves (e.g. by responding to a public online survey).
Voluntary response samples are always at least somewhat biased, as some people will inherently be more likely to volunteer than others, leading to self-selection bias.
Example: Voluntary response sampling
You send out the survey to all students at your university and a lot of students decide to complete it. This can certainly give you some insight into the topic, but the people who responded are more likely to be those who have strong opinions about the student support services, so you can’t be sure that their opinions are representative of all students.
3. Purposive sampling
This type of sampling, also known as judgement sampling, involves the researcher using their expertise to select a sample that is most useful to the purposes of the research.
It is often used in qualitative research, where the researcher wants to gain detailed knowledge about a specific phenomenon rather than make statistical inferences, or where the population is very small and specific. An effective purposive sample must have clear criteria and rationale for inclusion. Always make sure to describe your inclusion and exclusion criteria and beware of observer bias affecting your arguments.
4. Snowball sampling
If the population is hard to access, snowball sampling can be used to recruit participants via other participants. The number of people you have access to “snowballs” as you get in contact with more people. The downside here is also representativeness, as you have no way of knowing how representative your sample is due to the reliance on participants recruiting others. This can lead to sampling bias.
5. Quota sampling
Quota sampling relies on the non-random selection of a predetermined number or proportion of units. This is called a quota.
You first divide the population into mutually exclusive subgroups (called strata) and then recruit sample units until you reach your quota. These units share specific characteristics, determined by you prior to forming your strata. The aim of quota sampling is to control what or who makes up your sample.
Advantages of sampling
Sampling ensures convenience, collection of intensive and exhaustive data, suitability in limited resources and better rapport. In addition to this, sampling has the following advantages also.
1. Low cost of sampling
If data were to be collected for the entire population, the cost will be quite high. A sample is a small proportion of a population. So, the cost will be lower if data is collected for a sample of population which is a big advantage.
2. Less time consuming in sampling
Use of sampling takes less time also. It consumes less time than census technique. Tabulation, analysis etc., take much less time in the case of a sample than in the case of a population.
3. Scope of sampling is high
The investigator is concerned with the generalization of data. To study a whole population in order to arrive at generalizations would be impractical.
Some populations are so large that their characteristics could not be measured. Before the measurement has been completed, the population would have changed. But the process of sampling makes it possible to arrive at generalizations by studying the variables within a relatively small proportion of the population.
4. Accuracy of data is high
Having drawn a sample and computed the desired descriptive statistics, it is possible to determine the stability of the obtained sample value. A sample represents the population from which its is drawn. It permits a high degree of accuracy due to a limited area of operations. Moreover, careful execution of field work is possible. Ultimately, the results of sampling studies turn out to be sufficiently accurate.
5. Organization of convenience
Organizational problems involved in sampling are very few. Since sample is of a small size, vast facilities are not required. Sampling is therefore economical in respect of resources. Study of samples involves less space and equipment.
6. Intensive and exhaustive data
In sample studies, measurements or observations are made of a limited number. So, intensive and exhaustive data are collected.
7. Suitable in limited resources
The resources available within an organization may be limited. Studying the entire universe is not viable. The population can be satisfactorily covered through sampling. Where limited resources exist, use of sampling is an appropriate strategy while conducting marketing research.
8. Better rapport
An effective research study requires a good rapport between the researcher and the respondents. When the population of the study is large, the problem of rapport arises. But manageable samples permit the researcher to establish an adequate rapport with the respondents.
Disadvantages of sampling
The reliability of the sample depends upon the appropriateness of the sampling method used. The purpose of sampling theory is to make sampling more efficient. But the real difficulties lie in selection, estimation and administration of samples.
Disadvantages of sampling may be discussed under the heads:
Chances of bias
Difficulties in selecting truly a representative sample
Need for subject specific knowledge
changeability of sampling units
Impossibility of sampling.
1. Chances of bias
The serious limitation of the sampling method is that it involves biased selection and thereby leads us to draw erroneous conclusions. Bias arises when the method of selection of sample employed is faulty. Relative small samples properly selected may be much more reliable than large samples poorly selected.
2. Difficulties in selecting a truly representative sample
Difficulties in selecting a truly representative sample produces reliable and accurate results only when they are representative of the whole group. Selection of a truly representative sample is difficult when the phenomena under study are of a complex nature. Selecting good samples is difficult.
3. In adequate knowledge in the subject
Use of the sampling method requires adequate subject-specific knowledge in sampling technique. Sampling involves statistical analysis and calculation of probable error. When the researcher lacks specialized knowledge in sampling, he may commit serious mistakes. Consequently, the results of the study will be misleading.
4. Changeability of units
When the units of the population are not in homogeneous, the sampling technique will be unscientific. In sampling, though the number of cases is small, it is not always easy to stick to the, selected cases. The units of sample may be widely dispersed.
In some cases of sample may not cooperate with the researcher and some others may be inaccessible. Because of these problems, all the cases may not be taken up. The selected cases may have to be replaced by other cases.
Changeability of units stands in the way of results of the study.
5. Impossibility of sampling
Deriving a representative sample is difficult when the universe is too small or too heterogeneous. In this case, census study is the only alternative. Moreover, in studies requiring a very high standard of accuracy, the sampling method may be unsuitable. There will be chances of errors even if samples are drawn most carefully.
QUESTION : 2. What are the conditions required to formulate a Research Design.
Step 1: Consider your aims and approach
Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.
There are many different ways you could go about answering this question. Your
research design choices should be driven by your aims and priorities—start by thinking carefully about what you want to achieve.
The first choice you need to make is whether you’ll take a qualitative or quantitative approach.
Understanding subjective experiences, beliefs, and concepts
Gain in-depth knowledge of a specific context or culture
Explore under-researched problems and generate new ideas
Measure different types of variables and describe frequencies, averages, and correlations
Test hypotheses about relationships between variables
Test the effectiveness of a new treatment, program or product
The first choice you need to make is whether you’ll take a qualitative or quantitative approach.
Qualitative research designs tend to be more flexible and inductive, allowing you to adjust your approach based on what you find throughout the research process
Quantitative research designs tend to be more fixed and deductive, with variables and hypotheses clearly defined in advance of data collection.
It’s also possible to use a mixed-methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.
Practical and ethical considerations when designing research
As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics.
How much time do you have to collect data and write up the research?
Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
Will you need ethical approval?
At each stage of the research design process, make sure that your choices are practically feasible.
Step 2: Choose a type of research design
Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.
Types of quantitative research designs Quantitative designs can be split into four main types.
Experimental and quasi-experimental designs allow you to test cause-and-effect relationships
Descriptive and correlational designs allow you to measure variables and describe relationships between them.
Type of design Purpose and characteristics
Experimental • Used to test causal relationships
Involves manipulating an independent variable and measuring its effect on a dependent variable
Subjects are randomly assigned to groups
Usually conducted in a controlled environment (e.g., a lab) Quasi- experimental • Used to test causal relationships
Similar to experimental design, but without random assignment
Often involves comparing the outcomes of pre- existing groups
Often conducted in a natural environment (higher ecological validity) Correlational • Used to test whether (and how strongly) variables are related
Variables are measured without influencing them
Type of design Purpose and characteristics With descriptive and correlational designs, you can get a clear picture of characteristics, trends and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation).
Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled
Case study
Type of design, purpose and characteristics
Grounded theory
Aims to develop a theory inductively by systematically analyzing qualitative data.
Phenomenology
Aims to understand a phenomenon or event by describing participants’ lived experiences.
Step 3: Identify your population and sampling method Your research design should clearly define who or what your research will focus
on, and how you’ll go about choosing your participants or subjects.
In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.
Defining the population
A population can be made up of anything you want to study—plants, animals, organizations, texts, countries, etc. In the social sciences, it most often refers to a group of people.
For example, will you focus on people from a specific demographic, region or background? Are you interested in people with a certain job or medical condition, or users of a particular product?
The more precisely you define your population, the easier it will be to gather a representative sample.
Sampling methods
Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.
To select a sample, there are two main approaches: probability sampling and non- probability sampling. The sampling method you use affects how confidently you can generalize your results to the population as a whole.
Sample is selected using random methods
Mainly used in quantitative research
Allows you to make strong statistical inferences about the population
Sample selected in a non-random way
Used in both qualitative and quantitative research
Easier to achieve, but more risk of research bias
Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.
For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.
Case selection in qualitative research
In some types of qualitative designs, sampling may not be relevant.
For example, in an ethnography or a case study, your aim is to deeply understand a specific context, not to generalize to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.
In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question.
For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.
Step 4: Choose your data collection methods
Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.
You can choose just one data collection method, or use several methods in the same study.
Survey methods
Surveys allow you to collect data about opinions, behaviors, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews.
More common in quantitative research
May be distributed online, by phone, by mail or in person
Usually offer closed questions with limited options
Consistent data can be collected from many people
More common in qualitative research
Conducted by researchers in person, by phone or online
Usually, allow participants to answer in their own words
Ideas can be explored in- depth with a smaller group (e.g., focus group)
Observation methods
Observational studies allow you to collect data unobtrusively, observing characteristics, behaviors or social interactions without relying on self-reporting.
Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.
Systematically counting or measuring
Categories and criteria determined in advance
Taking detailed notes and writing rich descriptions
All relevant observations can be recorded.
Other methods of data collection
There are many other ways you can collect data depending on your field and topic.
Field Examples of data collection methods
Media & communication Collecting a sample of texts (e.g., speeches, articles, or social media posts) for data on cultural norms and narratives
Psychology Using technologies like neuroimaging, eye-tracking, or computer-based tasks to collect data on things like attention, emotional response, or reaction time
Education Using tests or assignments to collect data on knowledge and skills
Physical sciences Using scientific instruments to collect data on things like weight, blood pressure, or chemical composition
If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what kinds of data collection methods they used.
Secondary data
If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers have already collected—for example, datasets from government surveys or previous studies on your topic.
With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.
Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.
However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.
Step 5: Plan your data collection procedures
As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.
Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are high in reliability and validity.
Operationalization
Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalization means turning these fuzzy ideas into measurable indicators.
If you’re using observations, which events or actions will you count?
If you’re using surveys, which questions will you ask and what range of responses will be offered?
You may also choose to use or adapt existing materials designed to measure the
concept you’re interested in—for example, questionnaires or inventories whose reliability and validity has already been established.
Reliability and validity
Reliability means your results can be consistently reproduced, while validity means that you’re actually measuring the concept you’re interested in.
Does your measure capture the same concept consistently over time?
Does it produce the same results in different contexts?
Do all questions measure the exact same concept?
Do your measurement materials test all aspects of the concept? (content validity)
Does it correlate with different measures of the same concept? (criterion validity)
For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.
If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.
Sampling procedures
As well as choosing an appropriate sampling method, you need a concrete plan
for how you’ll actually contact and recruit your selected sample.
That means making decisions about things like:
How many participants do you need for an adequate sample size?
What inclusion and exclusion criteria will you use to identify eligible participants?
How will you contact your sample—by mail, online, by phone, or in person?
If you’re using a probability sampling method, it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?
If you’re using a non-probability method, how will you avoid research bias and ensure a representative sample?
Data management
It’s also important to create a data management plan for organizing and storing your data.
Will you need to transcribe interviews or perform data entries for observations? You should anonymize and safeguard any sensitive data, and make sure it’s backed up regularly.
Keeping your data well-organized will save time when it comes to analyzing it. It can also help other researchers validate and add to your findings (high replicability).
Step 6: Decide on your data analysis strategies
On its own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyze the data.
Quantitative data analysis
In quantitative research, you’ll most likely use some form of statistical analysis. With statistics, you can summarize your sample data, make estimates, and test hypotheses.
Using descriptive statistics, you can summarize your sample data in terms of:
The distribution of the data (e.g., the frequency of each score on a test)
The central tendency of the data (e.g., the mean to describe the average score)
The variability of the data (e.g., the standard deviation to describe how spread out the scores are)
The specific calculations you can do depend on the level of measurement of your variables.
Using inferential statistics, you can:
Make estimates about the population based on your sample data.
Test hypotheses about a relationship between variables.
Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs) look for differences in the outcomes of different groups.
Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.
Qualitative data analysis
In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.
Two of the most common approaches to doing this are thematic analysis and discourse analysis.
Approach Characteristics
There are many other ways of analyzing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.
QUESTION : 3. What is the questionnaire method? What are the requirements of a good questionnaire? Examine the merits and demerits of the questionnaire method.
What Is a Questionnaire?
A questionnaire is a research tool featuring a series of questions used to collect useful information from respondents. These instruments include either written or oral questions and comprise an interview-style format. Questionnaires may be qualitative or quantitative and can be conducted online, by phone, on paper or face-to-face, and questions don’t necessarily have to be administered with a
answers from respondents.
Why Are Questionnaires Effective in Research?
Questionnaires are popular research methods because they offer a fast, efficient and inexpensive means of gathering large amounts of information from sizeable sample volumes. These tools are particularly effective for measuring subject behavior, preferences, intentions, attitudes and opinions. Their use of open and closed research questions enables researchers to obtain both qualitative and quantitative data, resulting in more comprehensive results.
Pros and Cons of Using Questionnaires in Research
Though the importance of questionnaires in research is clear, there are both pros and cons to using these instruments to gather information. Learn more about
questionnaire advantages and disadvantages to determine if they’re suitable for your study.
Advantages of Questionnaires
Some of the many benefits of using questionnaires as a research tool include:
Practicality: Questionnaires enable researchers to strategically manage their target audience, questions and format while gathering large data quantities on any subject.
Cost-efficiency: You don’t need to hire surveyors to deliver your survey questions — instead, you can place them on your website or email them to respondents at little to no cost.
Speed: You can gather survey results quickly and effortlessly using mobile tools, obtaining responses and insights in 24 hours or less.
Comparability: Researchers can use the same questionnaire yearly and compare and contrast research results to gain valuable insights and minimize translation errors.
Scalability: Questionnaires are highly scalable, allowing researchers to distribute them to demographics anywhere across the globe.
Standardization: You can standardize your questionnaire with as many questions as you want about any topic.
Respondent comfort: When taking a questionnaire, respondents are completely anonymous and not subject to stressful time constraints,
helping them feel relaxed and encouraging them to provide truthful responses.
Easy analysis: Questionnaires often have built-in tools that automate analyses, making it fast and easy to interpret your results.
Disadvantages of Questionnaires
Questionnaires also have their disadvantages, such as:
Answer dishonesty: Respondents may not always be completely truthful with their answers — some may have hidden agendas, while others may answer how they think society would deem most acceptable.
Question skipping: Make sure to require answers for all your survey questions. Otherwise, you may run the risk of respondents leaving questions unanswered.
Interpretation difficulties: If a question isn’t straightforward enough, respondents may struggle to interpret it accurately. That’s why it’s important to state questions clearly and concisely, with explanations when necessary.
Survey fatigue: Respondents may experience survey fatigue if they receive too many surveys or a questionnaire is too long.
Analysis challenges: Though closed questions are easy to analyze, open questions require a human to review and interpret them. Try limiting open- ended questions in your survey to gain more quantifiable data you can evaluate and utilize more quickly.
Unconscientious responses: If respondents don’t read your questions thoroughly or completely, they may offer inaccurate answers that can impact data validity. You can minimize this risk by making questions as short and simple as possible.
Types of Questionnaires in Research
There are various types of questionnaires in survey research, including:
Postal: Postal questionnaires are paper surveys that participants receive through the mail. Once respondents complete the survey, they mail them back to the organization that sent them.
In-house: In this type of questionnaire, researchers visit respondents in their homes or workplaces and administer the survey in person.
Telephone: With telephone surveys, researchers call respondents and conduct the questionnaire over the phone.
Electronic: Perhaps the most common type of questionnaire, electronic surveys are presented via email or through a different online medium.
QUESTION : 4. Explain Doctrinal and Non Doctrinal Research?
The research basically means searching for something again and again until we reach an unequivocal conclusion. It is a systematic investigation that entails the collection of data, critical information, arranging it all and then analyzing it to deduce something meaningful. The word “research” is derived from the French word “recherché” which means to investigate thoroughly. So whenever research is being conducted, be it in any field, it involves going into the depth of the topic and making sense of it.
Legal research in particular dives deeper into the legal ocean. It is all about searching and researching laws, their origin, their application and everything else that can have the slightest nexus with the legal sphere. We try to search and analyze the effect of all the legal and non-legal variables on the process of legal decision-making. Black’s law dictionary defines legal research as “the finding and assembling of authorities that bear on a question of law”.(How to do legal research in 3 steps n.d.) Legal research is a constant companion of people involved in the legal world, be it the attorneys, judges, jurists, law researchers, law students and academicians. To possess the legal prowess and accumulate
knowledge to effectively contribute in this arena, research is important for all of them.
Now, to conduct research different pathways can be adopted. These pathways are known as “research methodologies”. Methodology in research is defined as the systematic method to resolve a research problem through data gathering using various techniques, providing an interpretation of data gathered and drawing conclusions about the research data.(Bouchrika 2021) The two words method and methodology should not be used interchangeably. Method signifies the process of collecting the required information and the technique that is employed to achieve this objective.
Whereas, on the other hand, methodology implies not only the procedures involved to collect data but also how to analyze and interpret it. The methodology is a comprehensive term and is wider than the method. It is a compass that determines the direction of the research.
Two prominent methodologies that are employed in legal research are doctrinal and non-doctrinal. The former one is more inclined towards theoretical aspects and academics, hence also known as “library” or “arm-chair” research. While the latter is more practical and takes an interdisciplinary approach to observation.
Hence it is also called “empirical” research.
Doctrinal research
Meaning and definition
Dr S.R. Myneni has defined, “A doctrinal research means a research that has been carried out on a legal proposition or propositions by way of analyzing the existing statutory provisions and cases by applying the reasoning power.” (Tiwary 2020)
Doctrinal research has the root word “doctrine” which means a principle or a basic governing tenet. That means, the legal doctrine would include legal principles and tenets that would govern the legal world. Therefore, it implies that
doctrinal legal research would involve digging deeper into the legal principles and concepts from various sources like cases, precedents, statutes and others; to analyze them and reach valid conclusions.
The focal point of doctrinal research is answering the question “What is law?”. It is library-based research, i.e. we try to find out definite answers to legal questions
through a thorough investigation from the law books, statutes, legislation, commentaries and other legal documents. All of these sources fall under the category of “Secondary Sources”. As stated earlier, it is theoretical research that does not involve any kind of experimentation or fieldwork.
Here, we are basically checking the validity of existing laws in light of a changing society. It begins with one or more legal propositions taken as a starting point and the entire research is directed in finding the validity of that hypothesis. It simply means reviewing and studying different legal documents and other sources and then deducing a complete answer to the question asked at the beginning by the means of rational interpretation and logical reasoning. Most often, the starting point in any research is doctrinal, i.e. library-based and then we move forward to other methodologies once our base is set by doctrinal research. This is the reason that doctrinal research is very famous among students and academicians.
History
The roots of doctrinal research can be traced to the positivist or the analytical school of law which was objective and value-free. It is more epistemologically oriented and does not concern itself with people or society. Though the law itself is normative, doctrinal research does not study it in a normative sense. It does not take into consideration the human aspects of law and how it affects people in society. In this type of research, we just concern ourselves with existing laws in the present state as they are. Its emergence can be traced parallel to the rise of common law in the nineteenth and twentieth century. Common law has been developed by the efforts of jurists and the Court’s decisions. The doctrine of precedents also developed around the same time. All of these developments are linked to doctrinal research as without it the other parallel developments would have been incomplete. It is when judges and attorneys investigated laws from various above-mentioned sources, that they could set the stage for the progress of common law.
And we all know, common law is the basis of legal development in several other countries. At a similar time, the law had entered the academic field in Europe and doctrinal research picked up pace as it became a popular tool of academic legal research. (Tiwary 2020) This is the reason why doctrinal research is also known as traditional research.
Purpose
One of the main purposes of conducting doctrinal research is solving the legal problems of bringing laws. For example, if the government decides to bring umbrella legislation for all the crimes committed against women, it may initiate doctrinal research by some jurists and experts in the field.
They may have to go through all the existing laws in this field, previous case laws, precedents, international trends, legal commentaries, articles by scholars, dictionaries, encyclopedias, journals, treatises, textbooks and other sources of legal information. Going through this sea of information, they would be able to answer all the questions related to this legislation and will be successful in bringing out comprehensive legislation.
It can be utilized for several other purposes as well like to help lawmakers develop meaningful and effective laws, develop fresh legal doctrines, aid courts in reaching effective and legally accurate judgments, help lawyers to interpret statutes and prepare their suits, help students in academia to set a base and many others.
Methodology
The methodology in doctrinal research starts with setting a proposition as the starting point. A legal provision in question or an existing law could be chosen for the purpose. The next step could be to analyze the purpose behind bringing that particular law. For example, for a provision of the constitution, Constituent Assembly Debates could give great insight.
The law then can be studied in greater detail. A course of action must be selected. Alternative courses can be explored. Different models need to be studied and finally, the consequences and approximated effects have to be weighed in order to accurately make predictions about the proposition set at the beginning. In all these stages, secondary sources talked about in the above paragraphs are utilized.
But one must be very careful in the selection of these sources. Searching for reliable and accurate sources demands time and effort. Useful information must be separated from the chaff as the presence of unreliable information could lead to misleading and inaccurately skewed results. The efficiency of this method also depends on the question that is asked in the beginning. Asking the right question is the first step towards concrete research. Setting the right proposition and then relying on the right sources is the key to successful doctrinal research.
Advantages and disadvantages
To begin with the advantages, doctrinal research forms the base of legal research in the academic field of law. Law students at the graduate and post-graduate levels usually venture into the world of legal research with the help of doctrinal methodology. This is the starting point for them where they can analyze sources available in the library and logically deduce their findings. The students are not well equipped at this particular stage to get involved with empirical research and to consider the law in the context of society. It is easier for them to study law “as it is” from secondary sources and it acts as a good starting point.
In addition, it gives the judges and lawyers the flexibility to approach law from different aspects and make its interpretation. It may not be wrong to say that the amorphous mass of the present-day statutory provisions takes concrete shape and form in the great laboratories of the law courts. (Jain 1982) Judges have over time developed law from their deep knowledge and investigation into the field. Law of torts is one great example as it is a “judge-made law”. Therefore, doctrinal research being the traditional methodology has helped in the development of legal research by giving it a base. It has been a close companion of law academicians, students, judges, advocates and jurists.
However, doctrinal research has its own shortcomings as well. Availability and choice of right and reliable sources is the bottleneck in doctrinal research. Logical deduction is also an uphill task. Furthermore, it is highly theoretical and restricted. Without the right direction, it may become highly objective and too mechanical. Moreover, it can be further highlighted that it studies law individually and does not consider it in the backdrop of society which is the playground of law. Without studying its normative and practical aspects, it’s like studying law in darkness and seems incomplete.
Non-doctrinal research
Meaning and definition
Non-doctrinal research, also known as social-legal research, is research that employs methods taken from other disciplines to generate empirical data that answers research questions. (Salim Ibrahim Ali 2017)
Non-doctrinal research takes a multi-disciplinary approach towards legal research. It employs methods and information available from other disciplines to
make a comprehensive approach towards law. It employs primary sources of legal information to reach a conclusion. Primary sources may include observations, experiments, questionnaires, surveys, etc. With the help of these sources, we analyze the practical aspects of law like the effect of its implementation in non- legal fields and society as a whole. Basically, we take a legal variable which could be a law along with a non-legal variable like economic, social, political, etc. and study their relationship by data collected, which could be qualitative or quantitative. Its area of focus is how the law works in the real world.
History
After World War II, there was a growing emphasis on empiricism. Hence, the realist school of thought developed. The realist school of thought brings to the forefront, the concern that laws are made for the benefit and regulation of society. Laws are there to fulfil society’s needs. Therefore, they cannot be studied in isolation and must be developed as per society’s requirements. Society is dynamic and so should be the law. Law should be suited to the needs of the real world.
Non-doctrinal research developed out of the growing need of bringing the law into the realm of realism. It was felt that legal research should deal more with its practical application and how it functions and affects the life of people in real- world; and less with the theoretical aspect of studying written law.
Moreover, we have also seen that towards the same time, there was a growing emphasis on the welfare state model. It was believed that the state was meant to serve the society and all the laws that it brings must cater to this need of welfare of the citizens. In this background, there was a huge lift received by non-doctrinal research that helped in this direction. Governments have also encouraged this field of research to bring out legislation that truly help people and also to judge how well they have performed.
Purpose and methodology
The purpose of non-doctrinal research is to check the utility of a law that has been brought or how it impacts the non-legal aspects of society. Also, non-legal factors affect the implementation of the law. Sometimes, a very comprehensive law is brought but sometimes the environment is such that its effectiveness is shielded by those circumstances. For example, a law brought to open the market for foreign players to liberalize the economy may be considered very destructive at a time like that of a pandemic when the domestic market is hard hit by lockdown and would be considered devastating.
While in normal circumstances the same law might have been proved very useful for the economy. Now research may be sponsored by the government to check whether circumstances are conducive to bringing such a law. The research may include collecting data about the condition of the domestic market and how it will affect it if the law becomes a reality. Research after implementing the law can also be conducted to check its consequences and effects that it had actually brought. For this purpose, the help of other behavioral sciences can be taken. It relies on observation more than theory because under different circumstances theory remains the same but its practical application changes and it is important to keep a track of these changes to keep the law updated and effective.
The methodology adopted is that of empirical research, i.e. different modes of experimentation and observation like collecting data by means of case studies, questionnaires, surveys, etc. These are the primary sources that give us first-hand information that can be then analyzed. This data collected can then be arranged in pie charts, bar graphs or other forms to reach a conclusion.
Advantages and disadvantages
The advantages of non-doctrinal research are many but the prime one remains its utility in practical purposes. It helps in gauging the practical effectiveness of laws in various non-legal fields. It is an effective tool to judge the performance of law in society. Legal issues are better analyzed when studied in a comprehensive manner by taking into consideration all the factors that might affect it. Moreover, when the data is quantified, it becomes rationally more appealing and authentic.
Also, since it relies on primary sources of information, it is more reliable.
Developing welfare policies for people has become the major function of the state. But it is not possible without any data that reveals the actual circumstances of society. Non-doctrinal research tells us what actually the society needs, where the laws are lacking and what are the responses of people on whom those laws are imposed. All of this information which can be obtained by non-doctrinal research makes policymaking a better and easier task.
Moreover, there is a gap between the law in books and law in action. Law transforms to a certain extent when it comes to implementation. Many variables exert their influence to cause this transformation. Knowledge of these factors that can be obtained by non-doctrinal research can help us in understanding this gap and in working towards eliminating it.
However, it also has its fair share of pitfalls. Non-doctrinal research is very time- consuming. It requires a lot of time and resources. Availability of funds poses another challenge. The collection of data can be a daunting task. And more than that, collecting the right pool of information from society can be full of errors.
People have different understanding and amounts of information. They have their own biases. That means the information collected, like from questionnaires and surveys can be skewed and misleading. Also, collecting primary data about some sensitive issues can be a dangerous task for the researcher. The research may also be blurred by the researcher’s personal prejudices and biases.
Comparison between doctrinal and non-doctrinal research
Doctrinal research is theoretical research, while on the other hand, non- doctrinal research is more practical.
Doctrinal research has its roots in the analytical or positivist school of thought. But non-doctrinal research comes from the realist school of thought.
Doctrinal research is based on secondary sources of information, like articles, commentaries, textbooks, etc. But non-doctrinal research is based on primary sources like surveys and case studies.
Non-doctrinal research includes fieldwork but doctrinal research is library-based arm-chair research that does not involve going to the field.
Doctrinal research is more concerned with the question “What is law” and studying law exclusively. But non-doctrinal research studies law in connection with society and various non-legal aspects that affect the law. It is socio-legal research.
The scope of doctrinal research is narrower concerning the law in isolation. But non-doctrinal research has a wider scope and studies law in comprehensive terms.
QUESTION : 5. Explain various methods of teaching.
1. Introduction:
The Law is a tool for social engineering and social control which should be studied along with the social content. Education is refulgence that shows the mankind the proper path to excel. Person pursuing Law should be exposed to proper Legal Education to become an expert in that field.
The main purpose of education is to develop rationale thinking, enhance of knowledge and self-sufficiency. Legal education has an important role in directing and moderating the social change forming an inexorable part of the society. Such education must be imparted with proper teaching methods so that the real essence of the subject is known. Teachers are the one who shapes the character, caliber, and future of an individual. Thus, teachers of legal education should have the skills of interpretation, communication, research, problem solving, drafting and analysis for the purpose of incorporating them in the minds of the future legal professionals. In India, there are several law schools offering quality legal education. However, the most immediate challenge is to improve the quality of legal education by introducing various reformative techniques of teaching, leading to the development of young lawyers who are skilled in dealing with the differing legal systems that make up our global community. Thus, the teaching in legal education ‘should prepare the students to meet the challenges and dimensions of internationalization, where the nature and organization of law and legal practice are undergoing a paradigm shift.
2. Basic concept of Legal Education:
The changes in Legal Education and Legal Profession have been long overdue. There have been voices sometimes sharp and sometimes subdued for such change. An unfortunately, no serious attempt could be made. In fact, so far, we have miserably failed to look into the problems of Legal Education and Legal Profession, which have been squarely facing us at our face. It is no use now putting the dust under the carpet as the atmosphere above the carpet is fairly polluted, it is high time we seriously look into these problems. To quote U.S. Chief Justice Warren E. Burgers, “My mother taught us that the time to fix the cracks in the plaster is when you first move into a house. Later on, you do not pay attention to them”. Chief Justice A.M. Ahmadi sounded almost the same note of Caution when he said in a Lecture: “I think we have waited long enough to repair the cracks in the Legal Education system of this country and it is high time that we rise from our arm Charis and start the repair work in right earnest”. The present Law has to meet the requirements of the society, which is entering into 21st century. Law has to deal with problems of diverse magnitudes and a student of law and an Advocate has to be trained in Professional skills to meet the challenges of globalization and universalization of law. With the advent of multi- nationals in India as anywhere else, the task of lawyers would be highly technical and an imperative need would arise to have competent Lawyers who would be trained in the right culture of Legal Education. This makes a sound case for improving Legal Education and Legal Profession at the earliest.
3. Meaning of Legal Education:
The term “Legal Education” is very difficult to define. It gives different meanings, at different times and places in the light of existing circumstances of the society. It is an admitted fact that legal education is a human science which furnishes beyond techniques, skills and competences the basic philosophies, ideologies, critiques, and instrumentalities all addressed to the creation and maintenance of a just society. It provides occasions for articulation of theories of a just society; and teaches us that articulation must be grounded in historical realities so that the truth of the working of the legal order is brought to the forefront.
To be true, it is a subject of great importance in view of its dynamic role in molding and envisioning the legal system of the cherished objectives of justice, liberty, equality and fraternity of a sovereign, socialist, secular, democratic republic. It may be called a branch of logical science through which the struggle for a just must be waged. Freud rightly opines that legal education is the combination of both the law and its context, social, political and theoretical.
Legal education is a broad and comprehensive concept. It includes not merely the profession which is practiced in courts, but also covers law teaching, law research, administration different branches where law plays a role and, in fact commercial and industrial employments and all other activities which postulate and require the use of legal knowledge and skill.
4. Aims of the Legal Education:
The prime object of legal education is to produce professional lawyers. The
term “Professional Lawyer” does not only cover the Litigating, Lawyer, viz.,
“The Lawyer who argues before the ordinary courts but all persons trained in law, whose employment is mainly dependent on their degrees in law. A Lawyer is not merely craftsman or even an artist. He has a special role in our society. He is the principal laboratory in the mixing of the governmental prescriptions. He is an important hand at the wheel of our economy because as a lawyer he has a profound important voice in business transactions.
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