Section A
.jpg)
A factorial design is an experimental design in which multiple factors (variables) are manipulated simultaneously. Each factor has multiple levels, and the design allows for the study of the main effects of each factor as well as the interactions between factors.
For example, imagine a study in which the effect of two different fertilizers (factor 1) and three different levels of irrigation (factor 2) on crop yield is investigated. The factorial design would involve applying all possible combinations of fertilizer and irrigation levels to different plots of land, and then measuring the yield of the crops. This would allow the researchers to examine the main effects of each factor (e.g. the effect of fertilizer A versus fertilizer B on crop yield) as well as any interactions between the factors (e.g. the effect of fertilizer A at high irrigation levels versus low irrigation levels).
2-Explain the assumptions, theories and steps of discourse analysis.
Discourse analysis is a method of studying written, spoken or signed language use. It examines language in context, with an emphasis on how language is used to construct and convey meaning.
Assumptions:Language is not just a means of communication, but also a social practice that is used to construct and maintain social relations and identities.
Discourse shapes and is shaped by social structures and power relations.
Theories:Michel Foucault's theory of power and knowledge, which argues that discourse creates and reinforces power relations by shaping our understanding of reality.
Critical Discourse Analysis, which examines the ways in which discourse is used to maintain and challenge power relations.
Steps:Identify the discourse, or language use, you want to analyze.
Contextualize the discourse by looking at the social and historical context in which it is produced and consumed.
Identify the participants in the discourse and the relationships between them.
Analyze the discourse itself, looking at things like vocabulary, grammar, and discourse markers.
Interpret the meaning of the discourse and how it is used to construct and convey meaning.
It's important to note that discourse analysis methodologies and steps may vary depending on the researcher's theoretical framework and field of study.
3-What are the different steps followed for conducting a scientific research?
Identifying the research question: The first step in conducting scientific research is to identify the research question or problem that needs to be addressed. This is usually done by reviewing existing literature and identifying gaps in knowledge or areas that require further investigation.
Developing a research design: Once the research question has been identified, the next step is to develop a research design that will be used to collect and analyze data. This includes deciding on the research methods, sampling techniques, and data collection methods that will be used.
Collecting data: After the research design has been developed, the next step is to collect data. This can include conducting experiments, surveys, interviews, or observations. The data collected should be relevant to the research question and of high quality.
Analyzing data: Once the data has been collected, it needs to be analyzed to determine if the research question has been answered. This can involve using statistical techniques, such as regression analysis or chi-squared tests, to determine if there is a relationship between the variables being studied.
Interpreting results: After analyzing the data, the next step is to interpret the results. This involves looking at the data in the context of the research question and determining what it means in relation to the problem being studied.
Communicating the results: The final step in conducting scientific research is to communicate the results to others. This can be done through publishing research articles, giving presentations at conferences, or writing reports for a wider audience.
Section B
4-Type of Quasi Experimental Designs.
Nonequivalent control group design: This design involves comparing two groups that are not randomly assigned, but are thought to be similar in terms of relevant characteristics. The treatment group receives the intervention, while the control group does not.
Pretest-posttest control group design: This design involves comparing a treatment group and a control group, both of which are given a pretest before the intervention. The treatment group receives the intervention, while the control group does not. Both groups are then given a posttest to measure the effectiveness of the intervention.
Time series design: This design involves collecting data on a single group over time, with the intervention being introduced at some point during the study. The data collected before and after the intervention can be compared to determine the effectiveness of the intervention.
Regression discontinuity design: This design involves comparing individuals who just meet or just fail to meet a certain criteria for an intervention. The effectiveness of the intervention can be determined by comparing outcomes for those who received the intervention to those who did not.
Matching design: This design involves matching individuals in the treatment group with individuals in the control group based on specific characteristics. The matched individuals can then be compared to determine the effectiveness of the intervention.
Identifying the research question: The first step in conducting scientific research is to identify the research question or problem that needs to be addressed. This is usually done by reviewing existing literature and identifying gaps in knowledge or areas that require further investigation.
Developing a research design: Once the research question has been identified, the next step is to develop a research design that will be used to collect and analyze data. This includes deciding on the research methods, sampling techniques, and data collection methods that will be used.
Collecting data: After the research design has been developed, the next step is to collect data. This can include conducting experiments, surveys, interviews, or observations. The data collected should be relevant to the research question and of high quality.
Analyzing data: Once the data has been collected, it needs to be analyzed to determine if the research question has been answered. This can involve using statistical techniques, such as regression analysis or chi-squared tests, to determine if there is a relationship between the variables being studied.
Interpreting results: After analyzing the data, the next step is to interpret the results. This involves looking at the data in the context of the research question and determining what it means in relation to the problem being studied.
Communicating the results: The final step in conducting scientific research is to communicate the results to others. This can be done through publishing research articles, giving presentations at conferences, or writing reports for a wider audience.
Section B
4-Type of Quasi Experimental Designs.
Nonequivalent control group design: This design involves comparing two groups that are not randomly assigned, but are thought to be similar in terms of relevant characteristics. The treatment group receives the intervention, while the control group does not.
Pretest-posttest control group design: This design involves comparing a treatment group and a control group, both of which are given a pretest before the intervention. The treatment group receives the intervention, while the control group does not. Both groups are then given a posttest to measure the effectiveness of the intervention.
Time series design: This design involves collecting data on a single group over time, with the intervention being introduced at some point during the study. The data collected before and after the intervention can be compared to determine the effectiveness of the intervention.
Regression discontinuity design: This design involves comparing individuals who just meet or just fail to meet a certain criteria for an intervention. The effectiveness of the intervention can be determined by comparing outcomes for those who received the intervention to those who did not.
Matching design: This design involves matching individuals in the treatment group with individuals in the control group based on specific characteristics. The matched individuals can then be compared to determine the effectiveness of the intervention.
5-Research Biases.
Research biases refer to any systematic errors or deviations in a study that may lead to inaccurate or unreliable results. These biases can occur at various stages of the research process, including during the design, data collection, analysis, and interpretation of results. Some common types of research biases include:
Selection bias: occurs when the sample of participants is not representative of the population being studied. This can happen when participants are not chosen randomly or when certain groups are excluded from the study.
Confirmation bias: occurs when researchers have a preconceived idea or hypothesis about the outcome of the study and only collect data that supports their hypothesis.
Observer bias: occurs when the researcher's own beliefs, expectations, or attitudes influence the way they collect and interpret data.
Publication bias: occurs when studies with positive or statistically significant results are more likely to be published in academic journals than studies with negative or non-significant results.
Recall bias: occurs when participants' memories or perceptions of events may be influenced by their knowledge of the study's aims or hypotheses.
To reduce research biases, researchers should use rigorous and transparent methods, such as randomization and blinding, to design and conduct their studies. Additionally, they should report all relevant data and consider alternative explanations for their findings.
6-Distinguish between field and experimental research design.
Field research design refers to studies that take place in natural settings, such as in a community or in the wild. These studies aim to observe and gather data on real-world situations, often without manipulating the environment or the subjects being studied. Field research is often used in anthropology, sociology, and other social sciences to understand how people interact with their environment and with each other.
Experimental research design, on the other hand, involves manipulating one or more variables in a controlled environment in order to study the cause-and-effect relationship between them. Experiments are typically conducted in a laboratory setting and aim to establish causal relationships between variables. They are often used in the natural and physical sciences, such as physics, chemistry, and biology, to understand how different factors influence a particular outcome.
In summary, field research is used to study real-world situations, while experimental research is used to establish cause-and-effect relationships in a controlled environment.
Field research design refers to studies that take place in natural settings, such as in a community or in the wild. These studies aim to observe and gather data on real-world situations, often without manipulating the environment or the subjects being studied. Field research is often used in anthropology, sociology, and other social sciences to understand how people interact with their environment and with each other.
Experimental research design, on the other hand, involves manipulating one or more variables in a controlled environment in order to study the cause-and-effect relationship between them. Experiments are typically conducted in a laboratory setting and aim to establish causal relationships between variables. They are often used in the natural and physical sciences, such as physics, chemistry, and biology, to understand how different factors influence a particular outcome.
In summary, field research is used to study real-world situations, while experimental research is used to establish cause-and-effect relationships in a controlled environment.
7-Types of questions that can be used in a survey research.
Closed-ended questions: These questions offer a set of predefined response options for the respondent to choose from, such as multiple-choice, rating scale, or yes/no questions.
Open-ended questions: These questions allow respondents to provide their own answer in their own words, such as "What do you think is the main reason for X?"
Likert scale questions: These questions ask the respondent to rate their agreement or disagreement with a statement on a scale, such as "Strongly Agree, Agree, Neutral, Disagree, Strongly Disagree."
Ranking questions: These questions ask the respondent to order a set of items according to their preference or importance.
Demographic questions: These questions ask the respondent about their personal characteristics, such as age, gender, education level, income, etc.
Filter questions: These questions are used to screen participants and determine if they meet the criteria for the survey, such as "Have you ever used product X?"
Matrix questions: These questions ask the respondent to rate multiple items or statements on a scale, in a grid format.
Single-select questions: These questions ask the respondent to select one option from a list of options.
Multi-select questions: These questions ask the respondent to select multiple options from a list of options.
Net Promoter Score (NPS) questions: These questions ask the respondent to rate how likely they are to recommend a product or service to others on a scale of 0-10.
Closed-ended questions: These questions offer a set of predefined response options for the respondent to choose from, such as multiple-choice, rating scale, or yes/no questions.
Open-ended questions: These questions allow respondents to provide their own answer in their own words, such as "What do you think is the main reason for X?"
Likert scale questions: These questions ask the respondent to rate their agreement or disagreement with a statement on a scale, such as "Strongly Agree, Agree, Neutral, Disagree, Strongly Disagree."
Ranking questions: These questions ask the respondent to order a set of items according to their preference or importance.
Demographic questions: These questions ask the respondent about their personal characteristics, such as age, gender, education level, income, etc.
Filter questions: These questions are used to screen participants and determine if they meet the criteria for the survey, such as "Have you ever used product X?"
Matrix questions: These questions ask the respondent to rate multiple items or statements on a scale, in a grid format.
Single-select questions: These questions ask the respondent to select one option from a list of options.
Multi-select questions: These questions ask the respondent to select multiple options from a list of options.
Net Promoter Score (NPS) questions: These questions ask the respondent to rate how likely they are to recommend a product or service to others on a scale of 0-10.
8-Strategies of interpreting data in a qualitative research.
Thematic Analysis: This method involves identifying patterns and themes in the data by coding, categorizing, and analyzing data. This strategy is useful for identifying patterns and themes in the data that are not immediately apparent.
Grounded Theory: This method involves developing a theory based on the data collected. This strategy is useful for identifying patterns and themes in the data that are not immediately apparent and for developing new theories.
Narrative Analysis: This method involves analyzing the stories and narratives that are told by participants. This strategy is useful for understanding how participants experience and make sense of their experiences.
Discourse Analysis: This method involves analyzing the language and discourse used by participants. This strategy is useful for understanding how participants use language to construct meaning and how language shapes their experiences.
Content Analysis: This method involves analyzing the content of the data, such as text, images, or videos. This strategy is useful for identifying patterns and themes in the data that are not immediately apparent.
Case Study Analysis: This method involves analyzing data from a specific case or group of cases. This strategy is useful for understanding the unique experiences of a specific group or individual.
Ethnographic Analysis: This method involves analyzing the culture and social interactions of participants. This strategy is useful for understanding how participants' experiences are shaped by their social and cultural context.
Section C
9-Difference between causal comparative and experimental research design.
Causal comparative research design compares groups that have already experienced an event or condition to determine if there is a causal relationship. Experimental research design manipulates variables to determine cause and effect.
10-Definition of research design.
Research design refers to the overall plan and structure of a research project. It includes the methods and procedures used to collect and analyze data, as well as the specific steps taken to ensure the validity and reliability of the findings. A well-designed research project will clearly outline the research question, hypotheses, and methods used to achieve the desired outcome.
Thematic Analysis: This method involves identifying patterns and themes in the data by coding, categorizing, and analyzing data. This strategy is useful for identifying patterns and themes in the data that are not immediately apparent.
Grounded Theory: This method involves developing a theory based on the data collected. This strategy is useful for identifying patterns and themes in the data that are not immediately apparent and for developing new theories.
Narrative Analysis: This method involves analyzing the stories and narratives that are told by participants. This strategy is useful for understanding how participants experience and make sense of their experiences.
Discourse Analysis: This method involves analyzing the language and discourse used by participants. This strategy is useful for understanding how participants use language to construct meaning and how language shapes their experiences.
Content Analysis: This method involves analyzing the content of the data, such as text, images, or videos. This strategy is useful for identifying patterns and themes in the data that are not immediately apparent.
Case Study Analysis: This method involves analyzing data from a specific case or group of cases. This strategy is useful for understanding the unique experiences of a specific group or individual.
Ethnographic Analysis: This method involves analyzing the culture and social interactions of participants. This strategy is useful for understanding how participants' experiences are shaped by their social and cultural context.
Section C
9-Difference between causal comparative and experimental research design.
Causal comparative research design compares groups that have already experienced an event or condition to determine if there is a causal relationship. Experimental research design manipulates variables to determine cause and effect.
10-Definition of research design.
Research design refers to the overall plan and structure of a research project. It includes the methods and procedures used to collect and analyze data, as well as the specific steps taken to ensure the validity and reliability of the findings. A well-designed research project will clearly outline the research question, hypotheses, and methods used to achieve the desired outcome.
11-Significance of hypothesis formulation.
Hypothesis formulation is an important step in the scientific process as it helps to guide research and experimentation by providing a clear and testable statement of what is expected to be observed. It allows researchers to make predictions and develop a plan for testing these predictions through observation and experimentation. This helps to ensure that the research is focused and efficient, and that the results obtained can be used to support or refute the original hypothesis.
12-Meaning of reliability.
Reliability refers to the consistency and dependability of a product, service, or system. It measures how well something performs over time and under different conditions. A reliable product or service is one that can be trusted to work consistently and without failure. Reliability is an important aspect of quality and customer satisfaction.
13-Method of snow ball sampling.
Snowball sampling is a method of sampling where initial participants are chosen at random and then they are asked to refer other participants who fit the criteria of the study. This process continues until a sufficient sample size is reached. It is often used in research when studying hard-to-reach or hidden populations.
14-Difference between independent and dependent variable.
Independent variables are the variables that are manipulated or changed in an experiment in order to observe the effect on the dependent variable. Dependent variables are the variables that are being measured or observed in an experiment in response to changes in the independent variable. In simple terms, independent variable causes changes and dependent variable is affected by the independent variable.
15-Relevance of grounded theory.
Grounded theory is a research method that emphasizes the importance of understanding social phenomena through the perspectives and experiences of the individuals involved. It allows for the development of a theoretical understanding that emerges from data collected through observation and interview, rather than being preconceived by the researcher. This approach is particularly useful in understanding complex phenomena and uncovering previously unknown patterns or relationships.
16-Meaning of ethnography.
Ethnography is the study and systematic recording of human cultures and societies, typically through fieldwork and participant observation. It aims to understand and describe the customs, beliefs, practices, and social organization of a particular group or community.
17-Criteria for selecting a case study.
When selecting a case study, it is important to consider the following criteria: relevance to the research topic, availability of detailed information and data, representativeness of a larger population, and the ability to generalize findings to other similar cases. Additionally, it should be an interesting and compelling case that captures the attention of the reader.
18-Concept of cross sectional survey research design.
Cross-sectional survey research design is a method of studying a population at a specific point in time. It involves collecting data from a representative sample of the population and analyzing it to identify patterns and trends. This design is often used to understand the prevalence of a particular condition or behavior in a population and can provide valuable insights for public health and policy decisions.
----------------------------------------------------------------------------------------------------------------------------------------------
Please reads the answers carefully if any error please show in the comment. This answers are not responsible for any objection . All the answers of Assignment are above of the paragraph. If you like the answer please comment and follow for more also If any suggestion please comment or E-mail me.
Thank You!
.jpg&description=Ignou mapc-005 assignment 2023 ){kind=link}
0 Comments