If you are looking for MDV-106 IGNOU Solved Assignment solution for the subject Research Methodology in Development Studies, you have come to the right place. MDV-106 solution on this page applies to 2022-23 session students studying in MADVS, PGDDVS courses of IGNOU.
MDV-106 Solved Assignment Solution by Gyaniversity
Assignment Code: MDV-106/ASST/TMA/2022-23
Course Code: MDV-106
Assignment Name: Research Methodology in Development Studies
Year: 2022-2023
Verification Status: Verified by Professor
Answer all the questions. All questions carry 20 marks each
1. What is a research design? What are the functions of a research design? Discuss Observational design in detail.
Ans) A research design is a strategy and framework for conducting an investigation to find answers to specific research questions. A traditional research design is a blueprint or detailed description of how a research study should be carried out, including operationalizing variables so they can be measured, choosing an appropriate sample to study, gathering data to serve as a foundation for testing hypotheses, and analysing the results.
A clearly defined research design is necessary for the seamless operation of the research processes, from selecting the research topic to data collecting, analysis, and report writing, in order to get the most information with the least number of resources and time. Research designs should be created with the utmost care because they have a significant impact on the validity of the research findings.
Functions of Research Design
The following features characterise an effective study design:
A research design would assist in determining a research problem and defending its choice.
It will include a thorough evaluation of prior research that has been done on the related issue and a synthesis of earlier publications.
Another purpose of a study design is to state the research problem’s hypothesis explicitly and concisely.
To specify the technique for collecting the data as well as the variables for which data would be required in order to test the given hypothesis.
To outline the analytical techniques that would be applied to test the theory.
Observational Design
In this kind of research design, participants are compared to a control group in order to reach a conclusion; however, the researcher does not completely control how treatments are distributed. The absence of manipulation of an independent or causative variable in an observational research design is the primary distinction between experimental and observational research. Simply by observing the independent and dependent variables' actual values, the researcher can determine whether they co-vary or not.
By using this approach, it is possible to prevent the introduction of misleading replies that could be caused by manipulative research techniques. An observational study provides valuable insight into a phenomenon while avoiding the moral and logistical challenges of organising a sizable, time-consuming research endeavour. There are two sorts of observational designs: unobtrusive observations, in which subjects are not aware that they are being watched, and direct observations, in which subjects are aware that the researcher is monitoring them.
Advantages: There is no set way that observational designs must be organised around a hypothesis; they can be flexible. The ability of the researcher to conduct an in-depth inquiry of a certain behaviour aids in identifying the relationships between the study's numerous characteristics. In observational designs, the variables under investigation are let to function without any human interference, therefore external validity is frequently very high. The findings of observational study can be applied to everyday life.
Caution: Designs used in observational research have poor internal validity. The data are not very reliable because it is difficult to reproduce them. The results cannot be generalised because they may only apply to the particular sample population. The researcher's prejudice may be present in the study. A cause and effect relationship cannot be established because nothing is modified. If a researcher is present during direct observations, the results may be distorted.
2. What is development research? What are the different methods of development research? Discuss the focus group discussion method in detail.
Ans) The majority of development research focuses on concerns with capacity, resources connected to livelihood security, and the guiding concepts that determine the goals and means of development. Utility-focused development research is conducted. It must be understood that this is neither fundamental nor pure research. It is action-oriented, practical, and applied research. It is not intended to advance or add to the body of knowledge in any particular discipline.
However, it often tends to advance knowledge in a particular subject or industry, leading to better practise. The knowledge is what improves how development practise is carried out. It opens up more opportunities for better understanding problems and details, which improves the efficacy of development practise. The goal of development research is to provide information on which the best choices can be made. The goal may be to help practitioners complete tasks or to address specific policy-related concerns.
Methods of Development Research
The techniques used in development research act as interactive or systematic systems of inquiry. No matter whether the type of development research being undertaken is programme focused or issue focused, the innovation of the development researcher lies in the assemblages of methodologies to meet the requirements of the context or research topic requires. Development researchers employ a broad variety of techniques, many of which are adapted from other disciplines, including participatory and traditional research approaches.
Studies of secondary sources, direct observation, semi-structured interviews, rating and scoring, various sorts of diagrams, case studies, games and role plays, workshops, informal and formal surveys, and other techniques are employed by development researchers. The development researcher's perceived demands are a major determinant of the approaches that are borrowed and applied.
There are four widely used methods:
Direct perception
Interviewing.
Discussion in a focus group.
The case study
Focus Group Discussion
Focus groups resemble group interviews in many ways. A moderator conducts the interview as a small group of interviewees discuss the issues raised by the interviewer. The crucial information in focus groups is what the group members say while they are conversing. The moderator is a skilled development expert who asks questions from a list of planned discussion topics, often known as a focus group discussion (FGD) checklist. Typically, there are six to eight participants with similar backgrounds.
Focus group discussions are distinguished by their explicit use of group interaction to generate knowledge and insights. Focus group discussion revolves around the fundamentals of listening and learning. Focus groups are becoming more widely accepted as a tool for development research. In situations where qualitative data is particularly useful, focus groups are used. FGDs typically produce a large amount of qualitative data. The knowledge, data, and insights created can be used to explain and comprehend specific empirical phenomena. The data obtained through FGD is frequently utilised to support, reinforce, or augment the claims made using quantitative data.
Steps in Conducting Focus Group Discussion
Planning: Focus groups are frequently semi-structured to permit conversation to flow while being facilitated. Consequently, meticulous planning is crucial.
Enlisting or selection of the group itself: There are typically seven to eight members in a focus group. The focus group's quality of discussion and the research's findings will depend on the informants present.
Moderating the focus group: With each subsequent focus group, you can improve this talent. Focus group moderators that are skilled or have expertise know how to frame the questions, order the questions, categorise the questions, and check the authenticity of the responses.
Analysing and Reporting: Even for skilled practitioners, this presents a challenge for many researchers. This calls for objectivity, and one must ensure that subjectivity and personal prejudices do not appear in the report.
3. What is meant measurement? Discuss the different kinds of measurement?
Ans) Any kind of science, whether it be social or natural, must have measurement. Any science seeks to measure events precisely and accurately, as well as the traits of the various units that make up a phenomena and their interactions. Giving numbers to things or happenings in accordance with regulations is measurement. The goal is to have data in a manner that allows variables to be connected to one another. We have to deal with a variety of social and psychological issues in social science research. One of the crucial steps in the research process is their measurement. The challenge of measuring social and psychological characteristics is difficult and complex.
Simply put, measurement is the process of assigning numerical values or other symbols or indicators (such as gender or occupational classifications) to things or events in accordance with a set of operating guidelines. When something is measured, it is always a property of the object or event and never just the thing itself. In this measurement method, the observer follows a plan or procedure that enables unambiguous classification of seen events into non-overlapping categories, with the categories then being assigned labels in the form of numbers or symbols.
Kinds of Measurement
Nominal: A variable measured on a "nominal" scale is a variable that does not really have any evaluative distinction. One value is really not any greater than another. A good example of a nominal variable is sex (or gender). Information in a data set on sex is usually coded as 0 or 1, 1 indicating male and 0 indicating female (or the other way around--0 for male, 1 for female). 1 in this case is an arbitrary value and it is not any greater or better than 0. There is only a nominal difference between 0 and 1. With nominal variables, there is a qualitative difference between values, not a quantitative one.
Ordinal: Something measured on an "ordinal" scale does have an evaluative connotation. One value is greater, larger, or better than the other. Product A is preferred over product B, and therefore A receives a value of 1 and B receives a value of 2. Another example might be rating your job satisfaction on a scale from 1 to 10, with 10 representing complete satisfaction. With ordinal scales, we only know that 2 is better than 1 or 10 is better than 9; we do not know by how much. It may vary. The distance between 1 and 2 maybe shorter than between 9 and 10.
Interval: A variable measured on an interval scale gives information about more or betterness as ordinal scales do, but interval variables have an equal distance between each value. The distance between 1 and 2 is equal to the distance between 9 and 10. Temperature using Celsius, or Fahrenheit is a good example, there is the exact same difference between 100 degrees and 90 as there is between 42 and 32.
Ratio: Something measured on a ratio scale has the same properties that an interval scale has except, with a ratio scaling, there is an absolute zero point. Temperature measured in Kelvin is an example. There is no value possible below 0 degrees Kelvin, it is absolute zero. Weight is another example; 0 lbs. is a meaningful absence of weight. Your bank account balance is another. Although you can have a negative or positive account balance, there is a definite and nonarbitrary meaning of an account balance of 0.
4. What are the different methods of qualitative data collection? Discuss in detail the case study method of qualitative data collection.
Ans) Qualitative methods are approaches to data collection that are more focused on describing meaning than making statistical inferences. They give detailed, informative descriptions. The most popular qualitative methodologies used in social science research are described in detail and compared in this section. In-depth interviews, focus groups, content analysis, and the case study method are a few of them.
Case Study Method
A common technique for qualitative analysis is the case study approach, which entails meticulous and thorough observation of a social unit, such as an individual, a family, an institution, a cultural group, or even the entire community. It is a method of study that emphasises depth over breadth. The case study emphasises more thoroughly examining a smaller set of circumstances and their connections. The case study discusses the processes that occur and how they relate to one another. A case study is essentially an in-depth examination of the specific unit being considered.
Finding the elements that collectively account for the behaviour patterns of the provided unit is the goal of the case study method. Case studies are "a comprehensive examination of a social unit, be that unit a person, a group, a social institution, a district, or a community," according to Pauline V. Young. In a nutshell, we can say that the case study method is a type of qualitative analysis where a person, situation, or institution is carefully and completely observed. Efforts are made to study every single aspect of the concerned unit in minute detail, and then generalisations and inferences are drawn from case data.
Characteristics:
With this approach, the researcher might choose one social unit or more for the purposes of his investigation.
Here, the chosen unit is thoroughly researched, that is, in great depth. In general, the investigation lasts a long time to determine the unit's natural history in order to gather enough data to make accurate inferences.
Using this methodology, we do an exhaustive analysis of the social unit, taking into account all its components. By using this approach, we want to comprehend the complexity of the variables at play inside a social group as a whole.
An effort is made to understand the causal components' reciprocal interrelationship with regard to the case study methodology.
Instead of using an indirect and abstract method, we directly examine the behaviour pattern of the relevant unit.
The case study approach generates insightful hypotheses and the data necessary to evaluate them, resulting in a method that enriches general knowledge over time. Generalized social science might suffer without it.
Assumptions: The case study approach is predicated on a number of presumptions. The following is a list of the key presumptions.
The belief that human nature is constant at its core, despite the fact that behaviour can change depending on the circumstances.
The presumption of researching the relevant unit's natural history.
The presumption of thorough study of the relevant unit.
Major Phases Involved:
Identifying and determining the status of the phenomenon under investigation or the focus unit
gathering information, looking into it, and researching the history of the phenomenon.
Identification and diagnosis of the underlying causes serves as the foundation for developmental rehabilitation.
application of corrective measures, such as therapy and treatment.
Follow-up programme to assess how well the treatment was received.
5. What are the different types of data? Discuss the graphical method of data presentation.
Ans) Using one of the sampling techniques/methods, we gather raw data in order to perform a study. Unless the raw data is presented in a way that makes sense, it cannot lead to any conclusions that are useful for the programme or in the formulation of policies. We must use the proper statistical tests and methodologies to examine the data in order to derive useful information from a study.
Types of Data
Two categories of data exist. Quantitative data, such as age, weight, height, and income, and qualitative data, such as occupation, sex, marital status, and religion. The following two types can be used to further categorise these.
Discrete: Data that can be categorised or grouped into groups, such male and female, and can only accept discrete values, as mentioned - nominal and ordinal scale.
Continuous: Continuous data are those that can take any value, including decimals. According to the definition of a continuous data in types of measurement, it is at least an interval or ratio scale. Even though an ordinal scale measurement does not meet all of the requirements for a continuous scale, it can nevertheless be included in this category. In the social sciences, it is challenging to measure variables on an interval or ratio scale; therefore, ordinal scale measurements must be used. The statistics based on such measurement may yield "under" or "over" estimations of the population parameter, it is further stressed.
Variable Types: In the analysis of data, two types of variables are employed.
Independent Variable: The term "independent variable" refers to the trait that is being observed or measured that is anticipated to have an impact on an event or outcome. It is unaffected by the occurrence or result, yet it may contribute to its variation or cause it.
Dependent variable: a variable whose value depends on how other factors in the relationship under study affect it. It is also known as a response, outcome, or criterion variable.
Graphical Presentation
Graphical presentation refers to the use of intuitive charts to visualise clearly and simplify data sets. Data obtained from surveying is ingested into a graphical presentation of data software. Then it is presented by some symbols, such as lines on a line graph, bars on a bar chart, or slices of a pie chart. In this way, users can achieve much more clarity and understanding than by numerical study alone.
The main agenda of presenting scientific data into graphs is to provide information efficiently to utilise the power of visual display while avoiding confusion or deception. This is important in communicating our findings to others and our understanding and analysis of the data. Graphical data representation is crucial in understanding and identifying trends and patterns in the ever-increasing data flow. Graphical representation helps in quick analysis of large quantities and can support making predictions and informed decisions.
Types of Graphical Representation:
Line graph
Histogram
Bar graph
Pie chart
Frequency polygon
Ogives or Cumulative frequency graphs
