If you are looking for MGS-005 IGNOU Solved Assignment solution for the subject Research Methodologies in Gender and Development Studies, you have come to the right place. MGS-005 solution on this page applies to 2022-23 session students studying in MAGD courses of IGNOU.
MGS-005 Solved Assignment Solution by Gyaniversity
Assignment Code: MGS-005 / AST-01 / TMA / 2022-23
Course Code: MGS-005
Assignment Name: Research Methodology In Gender And Development
Year: 2022 - 2023
Verification Status: Verified by Professor
Answer the following in 200 words each: (10marks)
Q 1. Explain the meaning of research.
Ans) Research can be defined as a systematic process of gathering and analysing data and information to answer a question or solve a problem. It involves the use of various methods, tools, and techniques to collect and interpret data, with the aim of generating new knowledge and insights. Research is a critical component of various fields, including science, social science, engineering, and humanities. It allows researchers to investigate complex issues, test hypotheses, and develop new theories and models that can inform decision-making and policy development. The research process typically involves several key steps, including defining the research question, developing a research design, collecting and analysing data, and interpreting and reporting findings. These steps may vary depending on the research area and methodology used.
There are several types of research, including qualitative research, which involves collecting non-numerical data such as interviews, observations, and surveys; and quantitative research, which involves collecting numerical data and using statistical analysis to draw conclusions. Other types of research include mixed-methods research, action research, and exploratory research, among others. Research is an essential tool for advancing knowledge and understanding in various fields. It helps to identify gaps in current knowledge, test hypotheses, and generate new insights and discoveries. Additionally, research is a critical component of evidence-based decision-making, providing policymakers and practitioners with the information they need to make informed choices and develop effective policies and programs.
Q 2. Why do we need theory in social science research? Explain.
Ans) Social science research seeks to understand human behavior and social phenomena, and to generate knowledge that can be used to improve the human condition. There are several reasons why theory is essential in social science research.
Firstly, theory helps to provide a basis for research by identifying key concepts and variables that need to be studied. Without theory, research can become unfocused and aimless, making it difficult to draw meaningful conclusions.
Secondly, theory helps to guide the research process by providing a framework for understanding the relationships between variables. This enables researchers to develop research questions, hypotheses, and study designs that are relevant to the research question at hand. Theory also helps to determine the methods of data collection and analysis that will be most appropriate for the study.
Thirdly, theory helps to explain and interpret research findings. Without a theoretical framework, it can be challenging to understand the significance of research results and their broader implications for social phenomena. Theory helps to provide context for research findings, and to identify areas where further research is needed.
Finally, theory is essential for advancing knowledge and understanding in social science research. By testing and refining theories, researchers can generate new insights and discoveries, contributing to the ongoing development of social science knowledge.
Q 3. Explain features of the feminist method.
Ans) The feminist method has several key features, including:
Feminist sociology argues that research designs were based on men’s experiences: Rural India has a high rate of female-headed households. However, urban middle class males believed women were "housewives." However, household production units, where most women work, are becoming more apparent. Delhi's slum women, domestic workers, and destitute women make bangles, toys, zardozi, and electronic parts.
Feminist sociology is against a separation and reification of a division between the public and private: When gender was considered as an organising factor of the family in sociology, the rest of social activity was wrongly characterised as "ungendered". A gendered "private" world and an ungendered "public" sphere are ideological and deceptive. In the corporate world, men are preferred since they work harder than women, who get married and have children. Men marry and have children, but the presumption is that women do the housework, cooking, shopping, child care, parent-teacher meetings, and sick care.
Feminist sociology recognizes the diversity of gender statuses in the social order: Feminist method emphasises settings rather than operationalized hypotheses, which is a plus. Feminist sociology examines statuses related to social class, caste, race, ethnicity, and international division of labour. Thus, economic, and political influence vary greatly by gender. Feminist study emphasises women's diverse race, age, ethnic, and historical experiences, and behaviours. It deliberately includes more than excludes. Class, status, and honour help analyse women's social position.
Q 4. Discuss the importance of research methods in social science research.
Ans) Research methods are crucial for conducting social science research as they provide a systematic approach for collecting, analysing, and interpreting data. Social science research is concerned with the study of human behavior, social interactions, and social institutions. Therefore, research methods in social science are essential for understanding complex phenomena, explaining patterns, and making evidence-based decisions.
One of the primary importance of research methods is that they ensure the validity and reliability of data. Research methods provide a systematic approach to collecting data, and they help to minimize bias and errors in data collection. Valid and reliable data is important for drawing accurate conclusions and making informed decisions.
Research methods are also important for ensuring ethical research practices. Social science research involves the study of human subjects, and it is essential to protect their rights, privacy, and confidentiality. Research methods provide ethical guidelines for conducting research, and they help to ensure that research is conducted in a manner that is respectful and beneficial to the participants.
Moreover, research methods provide a framework for data analysis, which helps to identify patterns and trends in the data. Data analysis is crucial for drawing conclusions and making generalizations about the population being studied. The use of appropriate research methods also enables researchers to test hypotheses, make predictions, and develop theories.
Answer any two of the questions given below in 1000 words each. (30 marks)
Q 1. What is research design? Explain the structure and function of the research design
Ans) Research design is the plan or strategy that a researcher uses to conduct a research study. It is a framework that outlines the steps or procedures that will be followed to collect, analyze and interpret data in order to answer a research question or test a hypothesis. Research design is an essential component of research, as it helps to ensure that the research study is well-structured, and the results are valid and reliable.
Research design includes various elements such as the type of research study (experimental, observational, descriptive, or correlational), the research population, sample size, sampling techniques, data collection methods, data analysis techniques, and ethical considerations. Each of these elements is crucial in shaping the research design and ensuring that the research is conducted in a scientifically rigorous manner.
The type of research study chosen will largely depend on the research question and the available resources. For instance, experimental research designs are used to test causal relationships between variables, while observational research designs are used to observe and describe phenomena in their natural settings.
The research population refers to the group of individuals that the research aims to study, and the sample size is the number of individuals that the researcher intends to include in the study. Sampling techniques are used to select individuals from the population, and they include random sampling, stratified sampling, and cluster sampling.
Data collection methods include surveys, interviews, observations, and experiments, while data analysis techniques include descriptive statistics, inferential statistics, and content analysis. Ethical considerations refer to the guidelines and regulations that researchers must follow to protect the rights and well-being of research participants.
Structure and Function of the Research Design
Research design is the blueprint or the plan for conducting research that enables the researcher to systematically collect, analyze, and interpret data to answer research questions or test hypotheses. The research design encompasses the overall plan, including research questions, study population, data collection methods, data analysis techniques, and ethical considerations. It also includes the type of research study, sample size, sampling techniques, and data collection and analysis tools. A well-designed research study is a crucial aspect of research that helps ensure the validity and reliability of the results obtained.
In order to construct a high-quality research study, the framework of the research design is formed of various components, each of which needs to be given careful consideration. These components consist of the research topic, the type of study design, the research population and sample size, the sampling techniques, the means for collecting data, the techniques for analysing data, and the ethical issues.
The research question is an essential component of the study design, and it should be understandable, particular, and capable of being answered. The research question serves as a compass for directing the research design and as a check to guarantee that the study objectives can be attained. It is essential to keep in mind that an excellent research topic is one that is clearly outlined, measurable, and pertinent to the group that is being investigated.
The type of research design is another key element of research design. The type of research design will depend on the research question, the study population, and the available resources. Common types of research designs include experimental, quasi-experimental, observational, and descriptive studies. Each research design has its strengths and limitations, and it is essential to choose the appropriate research design to ensure the study's objectives are achievable.
The research population refers to the group of individuals from which the sample is drawn. The research population is a critical aspect of research design as it helps determine the sample size and sampling technique to be used. The sample size is the number of participants that the researcher aims to include in the study, and it is important to have an adequate sample size to ensure the study is representative of the population.
Sampling techniques are methods used to select participants from the population. Sampling techniques include random sampling, stratified sampling, and cluster sampling. The choice of sampling technique will depend on the study's objectives, research question, and resources available. The sampling technique should be carefully chosen to ensure that the sample is representative of the population.
Data collection methods are the means by which data is collected from the study participants. Data collection methods include surveys, questionnaires, interviews, observations, and experiments. The choice of data collection method will depend on the research question and the study objectives. Data collection methods should be carefully chosen to ensure that they are appropriate and valid for the study.
Data analysis techniques are the means by which the collected data is analysed to draw conclusions and answer research questions. Data analysis techniques include descriptive statistics, inferential statistics, and content analysis. The choice of data analysis technique will depend on the research question and the type of data collected. Data analysis techniques should be carefully chosen to ensure that they are appropriate for the study.
Ethical considerations are an essential aspect of research design, and they ensure that the study is conducted in an ethical and responsible manner. Ethical considerations include informed consent, confidentiality, and privacy of the participants, minimizing risk to participants, and ensuring that the research is conducted in a non-discriminatory manner.
In conclusion, the study design is an essential component of the research process because it provides a methodical strategy for data collection, analysis, and interpretation. The research topic, the type of study design, the research population and sample size, sampling strategies, data collection methods, data analysis techniques, and ethical issues are all included as parts of the research design. Each of these components is essential for developing the study design and ensuring that the research is carried out in a manner that adheres to the highest standards of scientific rigour. In order to assure the validity and dependability of the results that were acquired, it is vital to conduct research that was thoughtfully designed.
Q 3. Define sampling. Explain the classification of sampling methods.
Ans) Sampling is the process of selecting a subset of individuals or units from a larger group, population or dataset to gather information or draw conclusions about the entire group. The subset that is selected is known as the sample, and it is typically smaller in size than the population it represents. Sampling is a fundamental tool in statistical analysis, research and data science and is used to make inferences about the larger population. The goal of sampling is to select a sample that is representative of the population in order to minimize sampling bias and increase the accuracy of the results. Sampling is used in many fields, such as market research, social science, medical research, and ecology, among others.
Classification of Sampling Methods
Sampling is a critical technique used in research to select a subset of individuals or groups from a larger population to draw inferences and conclusions about the entire population. There are different sampling methods that researchers use, each with its own strengths and limitations.
There are two broad categories:
Probability sampling is a sampling technique that involves selecting a random sample from the target population, in which each individual in the population has an equal chance of being selected. Probability sampling methods include simple random sampling, systematic sampling, stratified sampling, and cluster sampling.
Simple Random Sampling: Simple random sampling is a probability sampling method where every member of the population has an equal chance of being selected for the sample. This method involves selecting individuals at random without any bias or predetermined selection criteria. To achieve this, researchers often use random number generators or tables to generate a sequence of random numbers that correspond to the members of the population. The individuals with those numbers are then selected for the sample. The main advantage of simple random sampling is that it provides a representative sample that is free from bias. However, it requires a complete list of the target population, and it can be time-consuming and expensive to obtain such a list.
Systematic Sampling: Systematic sampling is a probability sampling method where the population is first divided into a list of numbered intervals, and a sample is selected at regular intervals from this list. For instance, if the population size is 10,000 and the sample size is 100, the researcher would select every 100th individual from the population list. The main advantage of systematic sampling is that it is more efficient than simple random sampling, as it is less time-consuming and less expensive. However, it is more susceptible to bias than simple random sampling, as the researcher may inadvertently introduce bias by selecting individuals at regular intervals that may have some systematic order or pattern.
Stratified Sampling: Stratified sampling is a probability sampling method where the population is divided into subgroups or strata based on specific characteristics, such as age, gender, or income level. A random sample is then drawn from each stratum to ensure that the sample is representative of the entire population. This method ensures that the sample is proportionate to the population in each stratum, which helps to ensure that the sample is representative of the entire population. The main advantage of stratified sampling is that it provides a more accurate representation of the population by ensuring that the sample contains an adequate number of individuals from each subgroup. However, it requires a complete list of the target population and may not be practical when there are many subgroups.
Cluster Sampling: Cluster sampling is a probability sampling method where the population is divided into groups or clusters, and a random sample of these clusters is selected. Then, all individuals within the selected clusters are included in the sample. This method is commonly used when the population is geographically dispersed or difficult to access
Non-probability sampling is a sampling technique that does not rely on random selection of individuals from the population. Rather, non-probability sampling methods use non-random selection techniques such as convenience sampling, purposive sampling, and snowball sampling.
Convenience Sampling: Convenience sampling is a non-probability sampling method where individuals are selected based on their availability and accessibility to the researcher. For example, a researcher may choose to survey individuals who are nearby, who have easy access to the research location, or who are willing to participate. Convenience sampling is often used in exploratory studies or studies with a limited budget, as it is a quick and inexpensive way to obtain a sample. However, it is subject to selection bias, as the sample may not be representative of the entire population.
Purposive Sampling: Purposive sampling is a non-probability sampling method where individuals are selected based on specific criteria or characteristics. The researcher identifies individuals who are likely to provide the most informative data and include them in the sample. For example, a researcher may choose to include individuals who have a certain level of expertise or experience, or who belong to a particular group or demographic. Purposive sampling is often used in qualitative research or when the research question requires a specific type of participant. However, it is subject to researcher bias, as the researcher may choose individuals who fit their preconceived notions or who are more likely to provide the desired results.
Quota Sampling: Quota sampling is a non-probability sampling method where individuals are selected to ensure that the sample has a specific distribution of characteristics. The researcher sets quotas for each demographic category, such as age, gender, or education level, and then selects individuals who meet these quotas. For example, a researcher may set a quota for 50% males and 50% females and then select individuals who fit these criteria. Quota sampling is often used when it is difficult or impossible to obtain a complete list of the target population, or when the research question requires a specific distribution of characteristics. However, it is subject to selection bias, as the researcher may select individuals who fit the quotas based on convenience or personal judgement.
Snowball Sampling: Snowball sampling is a non-probability sampling method where individuals are selected based on referrals from other participants in the sample. The researcher begins by identifying a small number of individuals who fit the target population and then asks them to refer other individuals who fit the criteria. Snowball sampling is often used when the target population is difficult to identify or access, such as when studying illegal activities or stigmatized behaviours. However, it is subject to selection bias, as the initial participants may only refer individuals who share similar characteristics or behaviours.
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