YRM21306_Summary Research Methodology RESIT.docx

YRM21306\_Summary Research Methodology Lecture 1: **Scientific research** has to be/is: - **Systematic** - To use procedures and measurement instruments that are **reliable** (consistent) and **valid** (measures what it is supposed to measure). - **Objective** -...

YRM21306\_Summary Research Methodology Lecture 1: **Scientific research** has to be/is: - **Systematic** - To use procedures and measurement instruments that are **reliable** (consistent) and **valid** (measures what it is supposed to measure). - **Objective** - To be **unbiased** (using facts/no prejudice), use **non-normative** results (that do not state values or opinions) and is **transparent** (justifies) choices and trade-offs. - **Theory-dependant**/theoretical - Is undertaken within a framework of a **set of philosophies** (e.g. positivism, interpretivism, critical theory, pragmatism, postmodernism) and **adds to existing knowledge**/theory (knowledge gap)...the research should be replicable by other humans. Personal preference must have no influence at all. Distinctions in scientific research: - **Descriptive** - Describes something in the world (1 variable) - e.g. how large is the population of storks in the Netherlands? - Typically answer 'what', 'how'. 'who', 'where', 'when' questions. - **Correlational** - Investigates the **relationship** between two (or more) variables. Do NOT imply causation. - e.g. is the number of storks related to the number of babies? - Typically answer 'to what extent' or 'what is the relationship between' questions. - **Explanatory** - **Explains why things are as they are -- causation.** - **e.g. is the number of babies caused by the number of storks?** - **Typically answer 'why' and 'how' questions (influence, affect, have an impact on, result in, lead to..).** Primary data versus secondary data: - **Primary** - Collected by yourself; through field work or laboratory research. - e.g. through surveys, questionnaires, interviews, observations, experiments, focus groups. - Goal: to answer specific research question. - **Secondary** - Primary data that is collected by others, and now collected by desk research. - e.g. through academic journals, government/industry reports, databases, books/newspapers. - No specific goal of answering the research question. Note: secondary data can provide background/context to primary data. Using both is beneficial for enhancing validity & reliability, and to provide richer insights. Fundamental approaches: - **Empirical research** - Is based on observed and measured phenomena: 'real world'. - Either direct or indirect measurements. - e.g. experiments, surveys, observations, case study to gather data. - Produces data-driven results (evidence-based insights) to confirm/refute hypotheses (what?/why?). - **Non-empirical research** - Is based on theoretic analysis, logical reasoning and existing research. - e.g. literature interviews, theoretic modelling, conceptual analysis. - Produces theoretic insights to advance the understanding of concepts (what does it mean?/how to understand it better?) Different types of sciences: - **Beta** - Natural & technical sciences - **Gamma** - Social sciences - **Alpha** - Arts & humanities (language, law, philosophy) The relationship between beta-gamma is important to prevent technocratic failure, as they do not always fit the socio-cultural reality (or the other way around). Research approach: - **Quantitative** - Measures through variables/numbers to turn it into usable stats. - Reality is perceived in 'research units', 'variables' and 'values'. - Research unit: the unit you want to say something about -- where the variable belongs to. - Variable: a concept in measurable terms/characteristic of a research unit. - Values: the outcomes belonging to a variable. - Focusses on testing hypotheses, cause-effect, predict -- often starts from an hypothesis. - Reductionist approach: identifying regularities that apply to many cases (general patterns). - **Qualitative** - Describes the world in terms of words. - Focusses on meaning, concepts, definitions, characteristics, ect. - To identify specifics in purposively selected cases (holistic approach). Research orientation: - **Applied/practice-oriented** - **Gain knowledge for solving a practical problem.** - **Outcomes: practical solutions, interventions, policies, technologies that address the problem.** - **e.g. investigating what the main reasons are for drinking water shortages in rural areas in Ghana.** - **Fundamental/theory-oriented** - **Gain knowledge to expand existing knowledge about a specific topic (without application in mind).** - **Does NOT start from a practical problem.** - **Outcome: new theories, models, insights that can contribute to the understanding of study.** - **e.g. investigating the DNA of apples.** Any good scientific research project has both theoretical and (indirect) practical relevance! Research cycles: **Empirical cycle** **Goal**: building and testing of theories\ Starting point: observing/knowledge of a problem **Building** phase (exploring): observation -- induction. **Testing** phase: deduction -- testing of hypotheses -- evaluation **Empirical cycle** - **Observation** - Observing phenomena, or identifying a problem that needs research -- often start with a particular issue/trend observed in real world. - **Induction** - Based on the observations, a general assumption if formulated: from specific (the problem you observed) to general \> bottom-up reasoning. - **Deduction** - Applying of the general assumption from the induction phase to specific examples in the world: from general to specific. A testable (clear, measurable, specific) hypothesis on the examples is formulation. - **Testing** - Data are collected to test the hypothesis -- is it true or not? - e.g. experiments, surveys, observations. - Ensure reliability and quality of data. - **Evaluation** - Results from the testing phase are compared to (analysed) the general assumption from the induction phase -- is it supported or refuted (drawing conclusions)? **Regulative cycle** Note: it's a policy formation cycle, NOT a research cycle. Only used for practical (societal) problems. **Regulative cycle** - **Problem identification** -- what is the problem? - You conduct the research to further explore (the extent of) the problem. - Screening: the problem is unknown and becomes visible after research. - **Diagnosis -- what is the cause of the problem?** - **Research to find the causes of the problem \> empirical cycle** - **Design -- what can we do to solve the problem?** - **Compare different interventions that might solve the problem \> e.g. the use of a pilot research \> is it a feasible intervention? \> decisions are made.** - **Implementation** - **Intervention is implemented -- progress is monitored -- intermediate/preliminary outcomes are measured.** - **Evaluation -- has the problem been solved?** - **Effectiveness of intervention is assessed -- benefits vs costs of intervention.** For context \> conceptual vs technical design phase: - Conceptual - Phase were the overall idea/framework of a study are developed. - Focusses on defining the problem -- goals -- general approaches without delving into specifics. - Technical - Phase where detailed specifics and plans for implementing the study are developed. - Translation conceptual design into specific, actionable plans & detailed designs. Lecture 2: **Research objective**: describes your motivation to do the research -- what do you hope to achieve through your research? - **External objective** -- objective in relation to the problem (broad) - States the problem you want to help solve/improve. - **Internal objective** -- objective in relation to the research (narrow) - States knowledge to be produced. Difference in research orientation: - **Practice oriented research** - Objective: to help solve/improve problem A by finding out/examining/investigating B. - **Theory oriented research** - Objective: to investigate/examine/find out B. - Formulating your research objective: 1\. What is the problem?\ 2. What is the objective? \- In relation to the problem.. \> help solve the problem.\ - In relation to the research.. \> what knowledge. Research questions: - **General research question (GRQ):** - Needs to be answered to reach, and should be in line with, the research objective. - Consists of several specific research questions (SRQs). - **Specific research questions (SRQ):** - Cover segments of the GRQ: focus on something specific withing the GRQ. - Answer to all SRQs make up answer to GRQ. Tools to derive SRQs: - **Tree diagram** - **Used to subdivide a complex concept in more specific aspects** - **Path diagram** - **To identify additional concept(s) that play a role in the expected relationship** - **Only suitable if GRQ is correlation OR explanatory.** Lecture 3: Operationalization: from concepts to variables \> how to measure your concepts (theoretical/abstract). - Simple concepts need one variable (e.g. age, temperature, height). - Complex concepts (consisting of multiple aspects) need more variables (e.g. scale 1-10) Steps to operationalization (based on Kumar): Likert scale: - Used to measure attitudes, opinions, perceptions by asking respondents to indicate the level of agreements -- disagreements. - Calculate total score -- recode score. Reliability & measurement validity: - **Reliability** - The quality of the measurement instrument or operationalization. - Will it give the same result every time? - **Measurement validity** - Does the instrument measure what it is supposed to measure without error? - Measurement error: the deviation between the unit's score on the variable and true score. - Observed score = true score + measurement error. Lecture 4: **Study design**: the strategy ('blue print') to how a research project is done. Quantitative study designs: - **Experimental study design** - **Cross-sectional study design** - **Longitudinal study design** - **Case study design** **Measurement scale** of variables: - **Nominal** - Values with distinct categories/no order. - e.g. gender, type of specie. - **Ordinal** - Values have a meaningful order - No equal distances between values - e.g. education level, scores on 5-point Likert scale. - **Interval** - Equal distance between values - No natural zero - e.g. temperature in Celcius degrees, years from a calendar. - **Ratio** - Values are ordered with equal distances between them - Natural zero (0 = absence of variable). - e.g. income in euros, number of children, length in cm. A table with a number of symbols Description automatically generated with medium confidence Hypothesis: state expectations about reality. - **Non-relational** hypothesis - Expectations about (the level/the distribution of) 1 or more variables. - e.g. \