Research Methods Syllabus Overview PDF

Syllabus overview – Research Methods THEME Key definitions and concepts Social research is concerned with finding out about the world that we live in. COURSE - Social research methods provide us with the farmwork and tools we need to investigate and...

Syllabus overview – Research Methods THEME Key definitions and concepts Social research is concerned with finding out about the world that we live in. COURSE - Social research methods provide us with the farmwork and tools we need to investigate and study the vast array OVERVIEW AND of fascination and complex phenomena in society in a rigorous way. INTRODUCTION - Some common elements literature reviews, concepts and theories, research questions, sampling of cases, data collection, data analysis, and write-ups of research findings. - Conducing is complicated and things to not always go to plan. - (A theory is a set of ideas that aims to explain something) How do we know things: Informal observations, selective observations, overgeneralization, authority, scientific methods à theory of science 1. Ontology – What is (the nature of being and reality) - Realism (objectivism= quantitative research). Objectivism in ontology: The belief that reality exists independently of our perceptions or beliefs. A researcher believes there is a single, measurable truth about human behavior, like facts in the natural sciences. - Idealism (constructivism= qualitative research). Constructivism in ontology: The belief that reality is socially constructed by individuals or groups. Knowledge is shaped by experiences, culture, and interactions, meaning there isn´t one objective truth. 2. Epistemology – what can be known (what is knowledge), - Positivism (quantitative): The philosophical position that only sensory experience (sanseerfaring) can provide us with knowledge of the world. That observable evidence is the only form of defensible scientific findings. - Interpretivism (qualitative): An epistemological position that requires the social scientist to grasp the subjective meaning of social action. A method that analyses based on the beliefs, norms and values of the culture of the society in which it takes place. It is a qualitative method used to analyze data related to human actions in sociology.  3. Methodology- How do we known? This is the general approach or strategy that guides how researchers go about acquiring knowledge, aligning with their ontological and epistemological assumptions. 4. Methods – These are the specific techniques or tools used for data collection and analysis, such as interviews, surveys, and statistical analysis. Ontology influences epistemology, which then shapes methodology and methods! What is a methodology – how we research/our research designs à a blueprint for a scientific study, what, why, how, of a study/research project. Influences all of the research design: - What scientific problems that are interesting to research THEORY, - How we formulate research questions METHODOLOGY, - What literature that’s interesting to review METHODS, - What constitutes as data/interesting data ETHICS - What techniques of data gathering that’s available to us - The ways we analyze and interpret the data Qualitative: end up in theory, theory as something that emerges out of research. - Focus: exploring ideas or formulation hypotheses/theories - Analysis: Summarizing, categorizing, interpreting - Expressed in: words - Sample: few respondents - Questions: open-ended - Characterized by: understanding, context, complexity, subjectivity - Methods: semi- structured and unstructured interviews, qualitative observations and ethnographies, various forms of discourse analysis, qualitative document analysis, case studies (can be mixed with quantitative research). - Quality: is measured by the transparency and clarity of your methodological and analytical approach. Trustworthiness: refers to the extent to which the study’s findings genuinely reflect the participants perspective and experiences 1.) Credibility: ensures that the findings are believable form the participants viewpoint, 2.) Transferability: Refers to the degree to which findings can be applied in other contexts, though this isn’t as strict as generalizability in quantitative research, 3.) Dependability: Focuses on the  stability of data over time and under similar conditions, 4.) Confirmability: Indicates that the findings are shaped by the participants and not researcher bias) Reflexivity: is essential in qualitative research because it acknowledges that researchers bring personal backgrounds, experiences, and biases that can shape data interpretation. Ethics: This ensures that readers can follow and understand each step of the research process, increasing the study's trustworthiness. Thick description: Thick description enables readers to grasp the full context, enhancing the potential transferability of findings to other similar settings. - Uses often inductive reasoning to the relationship between theory and research(observationà pattern à theory) - Example: Problem statementà A lot of crime in downtown Kristiansand according to the newspapers. How do we explain it? Research question: crime and class are correlated, but downtown Krs isn’t that poor, what other factors can play in? Data: Interviews with police officers and social workers Findings: crime concentrated around nightlife Conclusion: Our theory is that some types of crimes have geographies dependent on neighbourhood activity. Perhaps media report some crime (violent) and not other (economic criminality)? Quantitative: start with theory, theory comes before and prompts research. - Focus: testing hypotheses or theories - Analysis: math and statistical analysis - Expressed in: numbers, graphs, tables, fewer words - Sample: many respondent - Questions: close- ended or multiple choice - Characterized by: testing, measurement, objectivity, replicability - Methods: questionnaire and surveys, quantitative content analysis, which evaluates documents and texts, secondary data analysis, which evaluates data already collected by others, structured observations, which involves systematically observing and recording behavior, & experiments and prototypes. - Quality:  Reliability: can we rely on the result? Is the research sound and solid in terms of measurements and instruments? Can it be replicated. Reliability can be measured and quantified by itself. Validity: Do we measure what we say we measure? Generalizability: are the result true also for other contexts? - Uses often deductive approach/ reasoning to the relationship between theory and research (Theory à observation à conclusion) - Example: Problem statement à A lot of crime in downtown Kristiansand according to the newspapers. How do we explain it? Hypothesis: Crime and class are correlated Data: Crime statistics and income statistics on neighborhood level Analysis: Regression analysis Findings: -0.5 correlation (pretty strong) Conclusion: Downtown Krs is a poorer than average neighborhood, which explains why there is more crime there. Hypothesis stands. Mixed methods: A combination of approaches oftentimes a quantitative beginning, followed by a qualitative deep dive Abduction reasoning: neither data-driven nor hypothesis-driven but conducts parallel and equal engagement with empirical data and extant theoretical understanding. Values: reflect the personal beliefs or the feelings of a researchers - The value-free approach: Some believe that social scientist should be value-free and objective because research that simply reflects the personal biases of the researcher (s) cannot be considered valid and scientific. - The reflexive approach: This involves trying to identify and recognize the impact of their social location – that is, their gender, age etc., the kind of data that they produce and analyze during their research process. (Having a fixed set pf values and beliefs can also be a barrier to understanding the people we study.) - The conscious partiality approach: Research that is knowingly and even deliberately influenced by values.  The role of theory – most researchers have a theoretical understanding, use concepts etc to understand their field – before they enter it. Theory here is not “social theory”, but an idea about the outcome of the research. All start with a theoretical understanding/luggage/glass. Research design: In this book, we use this term to refer to a framework or structure within which a researcher collects and analyses their data. A choice of research design reflects decisions about the priority being given to a range of RESEARCH dimensions of the research process (such as causality and generalization) and is influenced by the kind of research PROBLEM, question that is posed. RESEARCH 1. Experimental design: establishing casual connection. A controlled setup where researchers manipulate one or DESIGN, more variables to observe their effect on other variables, often using random assignment. Commonly used to test RESEARCH cause-and-effect relationship. QUESTIONS 2. Cross- sectional design: sampling across a population. A study that analyzes data from a population at a specific point in time. It’s useful for understanding relationships between variables within a snapshot of time, but it doesn’t show cause and effect. 3. Longitudinal design: understanding change over time. A study that follows the same subjects over a long period, observing changes over time. It’s useful for tracking development, trends, or long-term effects but can be resource intensive. 4. Case studies: examining the experiences of people in specific situations and/or institutions. An in-depth study of a single subject, group, or organization. This approach provides detailed insights into complex issues but may not be generalizable to larger populations. 5. Comparative design: making comparisons between different context. A study that compares two or more groups or cases to identify similarities and differences. It’s useful for understanding contrasts across different contexts, often to test theories in varying conditions.  A QUALITATIVE THESIS A QUANTITATIVE THESIS 1. Introduction: 1. Introduction: Research problem Research problem Research question (hypothesis) Background Background 2. Theory/literature review 2. Methodology, methods, data, sources, ethics 3. Methodology, methods, data, sources, ethics 3. Theory/literature review 4. Data presentation and analysis 4. Data presentation and analysis 5. (Discussion) 5. (Discussion) 6. Conclusion 6. Conclusion - Research problem: a statement about an area of concern. Not necessarily a problem to be solved by you, but a gap in knowledge that a researcher can fill. You will not be able to answer these questions! Or solve these problems, but you can add to the field of knowledge on those “themes” Example: Green Infrastructure and Biodiversity Conservation à How can cities integrate green infrastructure, such as parks, green roofs, and urban forests, into their planning to enhance biodiversity, improve air and water quality, and mitigate the urban heat island effect while accommodating urban expansion? - Research question: specifies what you´re looking for/researching. Limits what you are not interested in. Helps you sort literature, theory, data etc. Example Qualitative Research Question: How does Baneheia contribute to the well-being and sense of community among urban residents in Kristiansand? Example Quantitative Research Question: What is the correlation between the extent of urban green space coverage and the diversity and abundance of wildlife species in Kristiansand? - (How to identify a research problem and formulate a research question: identify a research gap in order to formulate a research question & choose a perspective, such as planners, user, politicians etc.) - Literature review: finding literature. To learn about the field. To position yourself in the field. To find research gaps. To find inspiration. To justify your study. To find theory. to find doable methodologies and methods. Etc.  Common problems associated with literature searching: 1.) The problem of coverage- use multiple databases to find all relevant studies, 2.) Terminology - choosing appropriate search terms can be difficult, as different fields or authors may use varying terms to describe similar concepts. This can lead to missed articles that use alternate language or jargon, 3.) Sensitivity - in a literature search refers to capturing as many relevant studies as possible, but high sensitivity can lead to an overload of irrelevant articles, 4.) what to include and exclude in your search. Types of litterateur review: 1. Systematic reviews: aim to answer a specific research question by identifying, appraising, and synthesizing all high-quality research evidence available. They follow a rigorous, transparent, and replicable process, often including meta-analyses to combine quantitative data. The purpose is to provide a comprehensive summary of existing research, minimize bias, and inform evidence-based practice. 2. Scoping studies: are exploratory reviews that map out the key concepts, theories, sources, and gaps in a broad research area. Tends to focus on broader topics of investigation than the specific research question of systematic review. There is less emphasis on research quality. The purpose is to identify the scope, extent, and nature of research on a topic, highlight key findings, and inform future research directions. 3. Narrative review: Narrative reviews, also known as traditional or literature reviews, provide a narratively driven overview of research on a topic. These reviews are useful for gaining a broad understanding of a topic, especially when exploring theoretical perspectives or emerging areas. The purpose is to offer a general overview, synthesis, or critical perspective on a body of literature, often used to contextualize research within a larger theoretical framework. Evaluating the quality of social research - Originality: Relevance- resonate with the wider body of literature, timeliness – relate to everyday and/or public life, interest – who might be interested. - Rigour (the quality of being extremely thorough and careful): Transparency- to specify what you are doing and why, credibility- is the data reliable and valid, ethics – conduced the research with right ethics. - Significance: Alignment – aims, methods and findings are alignment, transferability – the use outside your field, contribution – inform current thinking, policy, or practice?  Methodology and methods: emphasizes the need to choose methods that align with the research question and explain why certain methods are appropriate. Qualitative interviews: attempt to generate data about how people understand and experience particular aspect of the human world. 1. Structured interviews: An interview, usually in the context of survey research, in which all respondents are QUALITATIVE asked exactly the same questions in the same order with the aid of a formal interview schedule. INTERVIEWS- 2. Semi-structured interviews: More open to the flow of questions, and the conversation is more dynamic. A series RESEARCH of potential topics are identified and explored in a manner that is responsive to the purpose of the interview and ETHICS AND the needs of the interviewee. INTERVIEWS 3. Unstructured interviews: They are very open in respect to themes, questions, and responses. Often only the briefest of direction is offered to the participant, who then respond on almost entirely their own terms. 4. The focus group: A focus group is focusing on the group and not the individuals. Focus groups offer a distinct method of generating data based on group interaction and discussion. Synchronous online focus group: Takes place in real time, within an hour or an hour and a half of a day. Asynchronous online focus group: Takes place over the course of hours, days or even weeks depending on the level of depth and conversation insight teams need. Recording: ensures accuracy by capturing the exact words of participants, along with tone, pauses, and emotions. Transcription: involves converting audio or video recordings into written text for analysis. Research ethics – must be consideration in all part of a research project à the design of, the doing of, the writing up, the dissemination. - Key principles of ethical practice: 1. Informed consent: Participants must be fully informed about the research purpose, procedures, potential risks, and their rights. They should consent voluntarily without coercion  a. Internet research and the use of social media: Obtaining consent can be challenging because users may not expect their publicly shared information to be used in research. Researchers should consider whether users view their posts as public or private and obtain consent where feasible. b. Working with venerable groups: Additional protections are necessary, such as providing clear, accessible information and seeking assent from guardians when appropriate. 2. Harm: Researchers should minimize any potential physical, psychological, or social harm to participants. 3. Deception: Deception involves misleading participants about aspects of the study, which is generally discouraged unless necessary for study integrity. 4. Privacy: Respect for participants' privacy entails limiting access to personal data and avoiding intrusive questions 5. Anonymity: Anonymity protects participants' identities, preventing anyone from linking data back to them. This is crucial in sensitive research areas where revealing identities could lead to harm or discrimination. 6. Confidentiality: Confidentiality involves safeguarding participants’ data and ensuring that information is not disclosed beyond the agreed research scope (third party). Ethical review board and committees: Undertaking any form of research that brings you into contact with other people is now virtually impossible without receiving some sort of “stamp of approval” before you step into the field. The process usually submitting a research proposal, and accompanying ethics form, to an ethics review committee or board. à NESH guidelines: ethical guidelines for research in Norway to provide a framework for conducting ethical research. They aim to ensure that research respects the rights, dignity, and well-being of participants and upholds the principles of academic integrity and public accountability. Ethical towards: 1. The research community - Freedom and independence, but also collegiality. Good citation practice, plagiarism, fabrication, distortion, concealment 2. The research participants - The responsibility to inform, Consent to participate, Protection of children, Anonymity, Confidentiality, Storage and sharing of research material, Risk of harm and disadvantage, Future generations  3. Groups and institutions - Disadvantaged and vulnerable groups, Respect for cultural differences, Cultural heritage 4. Commissioners and funders and collaborators - Independence in research, Transparency about funding, roles, and interests, The right to publication and public presentation 5. Dissemination of research - Ethics is normative and relates to epistemologies 1. Post-) Positivist research: Research is neutral. Describes what is. Ethical guidelines important, and somewhat straightforward. 2. Interpretivist research: Research is shaped by the researcher. Positionality is important and ‘hard truths are rare’. Research ethics is important but cannot fully be captured through guidelines. 3. Critical research: Research is power tool. The researcher should be an agent of social change. Ethical research is research that aims to progress the cause of the disenfranchised. Participant observation: A qualitative research method where researchers immerse themselves in a social setting, often engaging with participants to observe behaviors routings, and interactions in their natural contacts. Directed toward capturing the rich detail and diversity of experience that occurs “out there! In the human world. Collecting data PARTICIPANT while ethnography. OBSERVATIONS - Ethnography: a research method central to knowing the world from the standpoint of its social relations. (ETHNOGRAPHIE S) Situating participant observation - Observations are not isolated events; they are shaped by: - Gaining access: Closed settings: These are restricted environments where access is controlled, such as private organizations, institutions, or communities. Gaining entry into these spaces often requires permission from gatekeepers or developing trust with insiders, and it can affect how the researcher is perceived and what they are allowed to observe. Open settings: These are public or semi-public spaces where access is easier, like parks, events, or online forums. While access may be simpler, the scope and nature of observations can still be shaped by social norms and the researcher’s visibility in the setting.  - Insider or outsider: Whether the researcher is an insider or outsider shapes their access, the level of trust they build with participants, and the depth of insights they can gain. Standpoint theory reminds researchers to be aware of how their positionality affects what they observe and understand. - Research roles: you will need to choose whether you will take an overt or covert role. Overt methods are those in which the researcher makes themselves known as a researcher to those engaged in the research process. Covert methods on the other hand are those in which the researcher identity is not revealed to those the researcher is investigating. Implicit: Information or meaning that is implied or suggested but not directly stated. In an ethnographic study, cultural norms or values might be implicit, requiring the researcher to interpret body language or unspoken social rules. Explicit: Something that is clearly and directly stated or presented, leaving no room for interpretation or ambiguity. In a quantitative survey, the questionnaire used, the statistical analysis applied, and the exact variables measured are explicitly laid out. Research strategy: how you orientate you research to the data you are going to collect and analyze. Case studies CASE STUDIES, As exhaustive as possible. The more methods the merrier. A case can be a phenomenon, an event, an individual, a TRIANGULATION, goup, an organization, a community. Can use any method you want. Instead of finding the trend through random AND MIXED sampling purposive sampling. Having specific reasons for selecting the case. Kinda like a method but more of an METHODS approach to research design. - Case study is often related to the sociological concept of grounded theory. The idea that theory should be a product of empirical observation. Grounded theory is flexible methods, fieldwork, observe and interview to reach “a theory about…” - A case can be a phenomenon, an event, an individual, a goup, an organization, a community - Different types of cases (the classification is important because it forms the way you approach things, and is actually a finding, a result, in itself) 1. The critical case Purpose: A critical case is selected because it represents a critical test of an existing theory or assumption. It is chosen to challenge or validate established knowledge.  Characteristics: Critical cases are often selected when researchers want to investigate the boundaries or limitations of a theory. They are typically cases where the phenomenon of interest is expected to be most evident. 2. The extreme or unique case Purpose: An extreme or unique case is chosen when researchers want to explore a case that is highly unusual, atypical, or extreme in some way. This type of case is selected to investigate something out of the ordinary. Characteristics: Extreme or unique cases may have features, circumstances, or characteristics that are not commonly found in other cases within the same domain. They can provide insights into rare or exceptional situations. 3. The representative or typical case Purpose: A representative or typical case is chosen to provide an example that is considered typical or representative of a larger population or category. This type of case is often used when researchers aim to generalize findings to a broader context. Characteristics: The goal is to select a case that is considered average or typical in terms of the characteristics, behaviors, or experiences under study 4. The revelatory case Purpose: A revelatory case is selected when researchers want to gain a deep understanding of a particular phenomenon, often to generate new insights or theories. This type of case may hold the potential for revealing novel and valuable information. Characteristics: Revelatory cases may not fit typical patterns or expectations, but they have the potential to uncover hidden or unexpected aspects of the phenomenon. Researchs choose them to "reveal" something new. 5. The longitudinal case Purpose: A longitudinal case study involves the study of a single case over an extended period, allowing researchers to examine changes, developments, or processes over time. Characteristics: Longitudinal case studies provide insights into how a case evolves, transforms, or adapts over time. They are useful for understanding the dynamics and temporal aspects of a phenomenon. To sum up the key characteristics of a case study:  1. In-Depth Exploration: Case studies aim to provide a thorough and comprehensive analysis of the subject under investigation. Researchers collect a rich set of data from a variety of sources, such as interviews, observations, documents, and archival records. 2. Contextual Understanding: Case studies emphasize the importance of understanding the context in which the case exists. This includes the historical, cultural, social, and environmental factors that may influence the case. 3. Holistic Perspective: Researchers often examine the case as a whole, looking at various aspects and dimensions, rather than focusing on a single variable or factor. This allows for a holistic view of the case. 4. Qualitative Data: Case studies primarily rely on qualitative data, such as narratives, descriptions, and open-ended responses. Quantitative data may also be used, but it is often in a supplementary role. 5. Small Sample Size: Case studies typically involve a limited number of cases, often one or a few. The emphasis is on the depth of analysis rather than the breadth of coverage. 6. Longitudinal or Retrospective Study: Case studies can involve longitudinal studies (examining a case over time) or retrospective studies (analyzing a case that has already occurred). 7. Inductive Approach: Case studies often take an inductive approach, where researchers develop theories or generalizations based on the specific case(s) studied. Inductive: An approach to the relationship between theory and research in which the researcher uses the research results to generate theory. Compare with deductive. 8. Rich Description: The results of a case study are presented in a narrative format that provides a detailed and rich description of the case, allowing readers to gain insights and draw conclusions. Triangulation Cross- verification. Making sure we are right. A methology approach that involves using multiple sources, methods, data, theories, and/or researchers to study a phenomenon, problem or research question. Enhance the validity, reliability a more comprehensive understanding, reduces researcher bias, improved robustness. à Data Validation: Triangulation helps validate research findings by comparing and contrasting data from different sources or methods. When different data sources or methods produce similar results, it increases the confidence in the accuracy of the findings. Different types of triangulations: 1. Methodological Triangulation: This involves using multiple research methods to study the same phenomenon. Do different methods produce the same or different results? 2. Data Triangulation: Different forms of data (qualitative, quantitative), different databases, different actors. 3. Researcher Triangulation: Multiple researchers independently collect and analyze data to ensure objectivity and reduce bias. 4. Theory Triangulation: Theory triangulation involves using different theoretical frameworks or perspectives to interpret the same data. This approach can help researchers gain a more comprehensive understanding of a phenomenon and identify potential biases or limitations in a single theoretical perspective. Benefits: - Increased reliability: By using multiple sources or methods, researchers can reduce the chances of errors or bias in the data collection and analysis process. - Enhanced validity: Triangulation helps confirm the accuracy of research findings by corroborating evidence from different angles. - A more comprehensive understanding: By considering multiple perspectives or sources, researchers can develop a richer and more nuanced understanding of the research topic. - Reduced researcher bias: In qualitative research, using researcher triangulation can minimize the influence of a single researcher's bias on data interpretation. - Improved robustness: The use of triangulation can make research findings more robust and resistant to criticism. Mixed methods Qualitative & quantitative approaches in one study. Needn´t be constrained geographicaly, as case studies often are. Key characteristics: - Integration of methods: use of both qualitative and quantitative research methods. - Sequential or concurrent design: Sequential: One method helps or leads to the design of the other. Example: A quantitative study to investigate the role of gender for micro- finance loans. A qualitative study with lenders explores why.  Concurrent: Both are carried out simultaneous. Example: Studying the effectiveness of educational interventions through surveys with students (measuring results) and interviews with teachers (to learn about teaching methods) - Equal emphasis: both qualitative and quantitative data are given equal importance. - Complementarity: used to complement (utfylle) each other. Qualitative methods provide insights into the "why" and "how" of a phenomenon, while quantitative methods provide data on the "what," "how much," and "how many. - Triangulation: often incorporates triangulation, which involves comparing findings from qualitative and quantitative data to validate or enhance the quality of the research. - Pragmatic approach: driven by the research question. Researchers select methods that best suit the research objectives, rather than adhering strictly to one methodological paradigm. - Applied in various research phases: mixed methods can be applied in different phases of research. Generalization: When you assume something based on one experience. A general statement obtained by inference (A conclusion reached based on evidence and reasoning) from specific cases. Causality: The study of how things influence one other, how causes lead to effects. - Nature of Quantitative Research: Quantitative research focuses on using numbers to understand social behavior, often with a deductive approach and a positivist, objectivist view of social reality. - Research Questions: Common types of questions in quantitative research include descriptive/exploratory, QUANTITATIVE relational, and causal questions, each serving a different purpose in exploring data and relationships. METHODS - Concepts and Measurement: Concepts are fundamental in quantitative research, requiring clear measurement through indicators, which are essential for data collection and analysis. - Data Collection Methods: Mainly questionnaires, surveys and secondary data analysis. Includes surveys, sampling, experiments, and the use of existing data. Surveys can be conducted face-to-face, by phone, mail, or online. Proper sampling techniques are essential to ensure representativeness and valid results. - Data Analysis: Descriptive statistics is methods used to describe data and their characteristics.  Inferential Statistics is methods to make inferences (estimates or predictions) about what we don’t know. Involves different levels of analysis: univariate (analyzing one variable), bivariate (relationship between two variables), and multivariate (more complex relationships). Common software for analysis includes SPSS, Stata, R, and Python. - Bivariate and Multivariate Analysis: Techniques like contingency tables, correlation, and regression are used to analyze relationships between variables, testing hypotheses and assessing statistical significance. - Validity and Reliability: Ensuring the research is valid and reliable is crucial, which involves consistency in measurement and accurately capturing the intended concepts. - Critique of quantitative research: Problematic to treat the social world the same as the natural world. Artificial measurement process. - Samling techniques: Sampling is essential for representativeness in quantitative studies, with methods like probability sampling allowing results to be generalized to the larger population. Factors affecting sample size, such as response rates and sampling error, are crucial to consider in quantitative design. Factors such as time and cost, the heterogeneity of the population and the kind of analysis is also affecting sample size. Probability sampling: a sampling strategy which incorporates some form of random selection, meaning that everyone in the population has an equal chance of being included in the study. 1. Simple random sample: equal chance of being selected 2. Systematic sample: Individuals are selected at regular intervals from a list 3. Stratified sample: The population is divided into subgroups (strata) based on certain characteristics (e.g., age, gender, income level), and then a random sample is taken from each subgroup 4. Cluster sample: The population is divided into clusters (usually based on location or other natural groupings), and then entire clusters are randomly selected. Non-probability sampling: strategies that are not random in nature and are commonly associated with qualitative research (but also often feature in quantitative research). 1. Convenience sample: Participants are selected based on their availability and ease of access. 2. Snowball sample: Existing participants recruit future participants from their acquaintances, forming a "snowball" effect.  3. Quota sample: The researcher divides the population into subgroups and then gathers a set number of participants from each group, ensuring each subgroup is represented 4. Theoretical and purposive sampling: Participants are chosen based on their relevance to the research question or theory being developed. - Different software packages NVivo: A statistical software package that facilitates the management and analysis of qualitative data. Stata: A widely used statistical software package that allows quantitative data to be managed and analyzed. SPSS: Statistical Package for the Social Sciences is a widely used computer program allowing quantitative data to be managed and analyzed. Variables - Levels of measurement: 1. Ratio: has absolute zero 2. Interval: Scale with where categories are equally distanced and constant 3. Ordinal: Categories that can be ranked 4. Nominal: categories which cannot be ranked 5. Dichotomous: data that only has 2 categories - Measures of Central tendency: 1. Mean: Sum all values in distribution, then divide by total number of values 2. Median: middle point whiting entire range of values 3. Mode: Most frequently occurring value - Measure of dispersion (Standard deviation, range) help summarize and describe data characteristics effectively - Independent Variable (IV): The independent variable is the one that researchers manipulate or control to observe its effect. It’s considered the "cause" or "predictor" in an experimental setup. For example, in a study on the effect of study hours on exam scores, the independent variable would be the number of hours studied. - Dependent Variable (DV):  The dependent variable is what researchers measure or observe to see how it changes in response to the independent variable. It’s considered the "effect" or "outcome." In the example above, the dependent variable would be the exam score, as it depends on the amount of study time. - Independent Variable and Dependent Variable Relationship: The goal is to see if changes in the independent variable lead to changes in the dependent variable. This relationship is foundational to understanding cause and effect in quantitative research. Approaches to CA and DA take the position that language is a focused of research interest and not just a medium through which research participants communicate with researchers. DISCOURSE Conversation analysis ANALYSIS - Objective and Focus: CA aims to understand the structure and patterns of everyday conversations. Its focus is on the “how” of communication—specifically, how interactions unfold in natural settings. It looks closely at aspects like turn-taking, pauses, repairs, and intonation. - Theoretical Background: Rooted in ethnomethodology, CA emphasizes that social interactions are orderly and that people use particular conversational practices to make sense of their everyday lives. - Methodology: CA uses highly detailed transcription methods (such as Jeffersonian transcription) to capture the nuances of speech, including pauses, laughter, and emphasis. It is often based on audio or video recordings of naturally occurring interactions, and it involves micro-level analysis. - Data and Application: Data in CA often consist of transcriptions of real-life conversations in various contexts (e.g., doctor-patient interactions, classroom discussions). It's applied in fields like sociology, linguistics, and social psychology, especially where understanding social practices and structures is key Discourse analysis - Objective and Focus: DA, on the other hand, has a broader scope. It studies how language constructs social realities, power relations, identities, and social norms. The focus is not just on conversation structures but on the wider context of language use, including written and spoken texts, symbols, and broader discursive practices.  - Theoretical Background: DA is often associated with post-structuralist and critical theories, with influences from Foucault, Derrida, and other social theorists. It emphasizes that language both reflects and shapes social structures and ideologies. - Methodology: DA involves analyzing the content, themes, and underlying assumptions within the language. It may look at larger texts (such as media reports, policy documents) or transcripts of conversations but is less concerned with the micro-details of speech. - Data and Application: Data can range from political speeches to media articles to social media posts. DA is used in disciplines like media studies, political science, and cultural studies, particularly when examining how power, identities, and ideologies are constructed and contested. Content analysis: an approach to the analysis of documents and text that seeks to quantify their content in terms of predetermined categories and in a systematic and replicable manner. The term is sometimes used in connection with qualitative research as well. Practice question Course overview and introduction 1. What is ontology concerned with a. The techniques used to collect data b. The nature of reality and existence c. The methods used for analyzing data d. The ethical considerations in research Correct Answer: B) The nature of reality and existence 2. Which of the following best defines epistemology? a. The study of ethical considerations in research b. The examination of social structures in data  c. The study of how we can know and gain knowledge about reality d. The use of qualitative data in social sciences Correct Answer: C) The study of how we can know and gain knowledge about reality 3. Which research paradigm assumes that reality is socially constructed and subjective? a. Positivism b. Realism c. Interpretivism d. Pragmatism Correct Answer: C) Interpretivism 4. What is a key characteristic of the positivist research paradigm a. It prioritizes understanding over measurement b. It emphasizes causality and verification c. It views reality as subjective d. It relies solely on qualitative methods Correct Answer: B) It emphasizes causality and verification 5. According to the course, which method is likely used in an interpretivist research approach? a. Statistical analysis b. Experiments c. In-depth interviews d. Surveys Correct Answer: C) In-depth interviews 6. Which of the following methods would most likely be used in a positivist approach? a. Focus groups b. Questionnaires and statistical analysis c. Auto-ethnography d. Document analysie Correct Answer: B) Questionnaires and statistical analysis Methodology 1. Which of the following best describes 'methodology' in research?  a. The process of collecting data b. The overall strategy and rationale guiding the research design and methods c. A specific technique used to analyze data d. The hypothesis formulation process Correct Answer: B 2. What is the main difference between qualitative and quantitative methodologies? a. Qualitative focuses on large datasets, while quantitative focuses on narratives. b. Quantitative is more exploratory, while qualitative is hypothesis-driven. c. Qualitative interprets non-statistical data, whereas quantitative analyzes numerical data. d. Both use the same methods for different purposes. Correct Answer: C 3. Which of the following research designs is most associated with the quantitative approach? a. Ethnography b. Survey research c. Grounded theory d. Discourse analysis Correct Answer: B 4. In qualitative research, 'trustworthiness' and 'credibility' are measures of: a. Statistical accuracy b. Data validity c. Data reliability d. Research quality Correct Answer: D 5. Which reasoning method involves starting with observations and developing a theory? a. Deductive b. Inductive c. Abductive d. Hypothetical-deductive Correct Answer: B 6. A mixed methods approach often involves:  a. Using only qualitative methods to analyze data b. Combining quantitative and qualitative approaches for triangulation c. Using qualitative data to confirm quantitative hypotheses d. Relying solely on surveys and case studies Correct Answer: B 7. In a study, if the researcher aims to measure a single reality and obtain objective results, the likely epistemology is: a. Constructivism b. Pragmatism c. Positivism d. Subjectivism Correct Answer: C 8. Which term refers to the ability of research findings to be applied to broader contexts outside the study? a. Credibility b. Generalizability c. Transferability d. Reflexivity Correct Answer: B Research design 1. What is a primary purpose of a research design? a. To develop a detailed budget for a study b. To provide a blueprint for a scientific study, including what, why, and how of the research project c. To list all possible methods that could be used in research d. To summarize previous research on a topic (Correct answer: B) 2. Which of the following is an example of a research problem? a. "How do cultural norms influence women's decision-making power in Quito?" b. "What factors are contributing to climate change?" c. "What strategies are effective in empowering women in developing countries?"  d. All of the above (Correct answer: D) 3. When developing a research question, what is the purpose of refining it? a. To expand the scope of research b. To narrow the focus and clarify the research’s aim c. To ensure it aligns with every existing theory in the field d. To ensure it provides a complete solution to a problem (Correct answer: B) 4. In qualitative research, choosing a perspective is essential because: a. It ensures the study is objective and unbiased b. It provides a specific lens through which the research problem is explored c. It eliminates the need for a literature review d. It reduces the need for data collection (Correct answer: B) 5. Which of the following is NOT recommended when writing the methodological chapter? a. Stating why a particular method is suitable for the research question b. Explaining the strengths and weaknesses of the chosen methodology c. Defining a qualitative study without relating it to the research question d. Integrating methodological literature relevant to the specific study (Correct answer: C) Qualitative interview: research ethics and interviews 1. What should be a key ethical consideration in all stages of a research project? a. Budgeting and funding b. Ethics, from design to dissemination c. Scheduling d. Peer review process Answer: B) Ethics, from design to dissemination 2. According to the NESH guidelines, researchers have ethical obligations toward several groups. Which of the following is NOT explicitly mentioned? a. Research participants b. The general public c. Commissioners and funders d. Research community Answer: B) The general public 3. Which research approach believes in the neutrality of research, aiming to describe "what is" rather than acting as an agent for change? a. Interpretivist research b. Critical research c. (Post-)Positivist research d. Constructivist research Answer: C) (Post-)Positivist research 4. In qualitative interviews, semi-structured interviews are typically characterized by: a. Strict adherence to a fixed set of questions b. No pre-prepared questions c. An interview guide with themes allowing for flexibility d. Multiple-choice questions only Answer: C) An interview guide with themes allowing for flexibility 5. Which type of interview question aims to encourage the interviewee to elaborate on a specific point? a. Introducing questions b. Direct questions c. Probing questions  d. Specifying questions Answer: C) Probing questions 6. For research involving personal data collection, students are advised to notify in advance. How many days are recommended for this notification? a. 15 days b. 20 days c. 30 days d. 60 days Answer: C) 30 days Triangulation, casestudy and mix-methods 1. What is the primary purpose of triangulation in research? o A) To reduce the sample size o B) To enhance the validity and reliability of findings o C) To increase the number of methods used o D) To limit researcher bias 2. Which of the following is NOT a type of triangulation? o A) Methodological triangulation o B) Theory triangulation o C) Data triangulation o D) Participant triangulation 3. One benefit of triangulation is: o A) It allows researchers to use only qualitative methods o B) It confirms findings by cross-verifying data from different sources o C) It requires only one researcher to ensure objectivity o D) It reduces the number of sources used in the study 4. In a mixed methods study, quantitative methods are typically used to find out:  o A) The “why” and “how” of a phenomenon o B) The “what,” “how much,” and “how many” aspects o C) Only qualitative outcomes o D) Researcher biases 5. Which design involves using one method to lead to the design of the next? o A) Concurrent o B) Sequential o C) Mixed o D) Parallel 6. Mixed methods research emphasizes: o A) The exclusive use of qualitative data o B) Integration of qualitative and quantitative data o C) The elimination of triangulation o D) A focus solely on statistical analysis 7. What is the main goal of a case study? o A) To generalize findings across multiple cases o B) To provide an in-depth analysis of a single case or a small number of cases o C) To replace qualitative methods with quantitative ones o D) To eliminate the need for sampling 8. Which of the following is a characteristic of a representative case study? o A) It is selected to reveal something new o B) It exemplifies typical characteristics of a larger population o C) It challenges existing theories o D) It is longitudinal by nature 9. A longitudinal case study is primarily used to: o A) Test a hypothesis over a short period o B) Observe changes in a case over an extended period o C) Replace the need for sampling o D) Generalize findings across multiple cases Quantitative methods 1. Which of the following best describes the main approach of quantitative research? A) It focuses on in-depth, subjective exploration of social phenomena. B) It seeks to understand social behavior through numeric data and a deductive approach. C) It involves a highly flexible, interpretivist approach to data analysis. D) It is based on participant observation and ethnographic methods. Answer: B) It seeks to understand social behavior through numeric data and a deductive approach. 2. In quantitative research, which variable is manipulated to observe its effect on another variable? A) Dependent Variable B) Independent Variable C) Control Variable D) Moderator Variable Answer: B) Independent Variable 3. Which type of question would explore a simple association between two variables? A) Descriptive B) Relational C) Explanatory D) Causal Answer: B) Relational 4. What is the purpose of using a random sample in quantitative research? A) To ensure the sample is larger than the population. B) To increase the diversity of responses. C) To improve the generalizability of the findings. D) To eliminate the need for a control variable. Answer: C) To improve the generalizability of the findings. 5. Which of the following data collection methods involves structured interviewing?  A) Survey B) Participant Observation C) Focus Group D) Case Study Answer: A) Survey 6. What does a high standard deviation indicate in a dataset? A) The values are very close to the mean. B) The values are widely spread around the mean. C) The mean value is inaccurate. D) The data distribution is skewed. Answer: B) The values are widely spread around the mean. 7. Which statistical test would be appropriate for examining the relationship between two nominal variables? A) Pearson’s r B) Chi-square test C) T-test D) Regression Analysis Answer: B) Chi-square test 8. Which of the following best describes a dependent variable? A) It is the variable manipulated by the researcher. B) It is the variable that responds to changes in another variable. C) It controls the effect of the independent variable. D) It moderates the relationship between two variables. Answer: B) It is the variable that responds to changes in another variable. 9. What is a major critique of quantitative research as discussed in the presentation? A) It overemphasizes subjective perspectives. B) It lacks generalizability.  C) It treats the social world too similarly to the natural world. D) It is primarily qualitative in nature. Answer: C) It treats the social world too similarly to the natural world. 10. Which measure of central tendency is most appropriate when dealing with skewed data? A) Mean B) Median C) Mode D) Range Answer: B) Median Discourse analysis