Samenvatting WO RM1-10
Belangrijke woordenlijst A-Z:
2x2 factorial design: Experiment, test 2 interventions in 1 sample
Action research: research aimed at solving a practical problem
Case study: investigating a contemporary phenomenon in real-life context
Covert observation: People don’t know you are observing them
Critical research: paradigm seeking to empower people
Deductive research: test formulated assumptions
Design science: Scientifically solving a problem with innovative artifacts
Ethnography: Descriptive study, aimed at understanding something thoroughly (verstehen)
Evaluation: Design science: testing an implemented artifact in real context
Experiment: isolate cause & effect in controlled situation
External validity: Are results generalizable?
Fabrication: Researcher makes up data himself
Falsification: Researcher changes data to change results
Hawthorne effect: When subject behaves differently because someone is watching
Inductive research: develop theory based on data (theory-building)
Internal validity: Are measurements really because of manipulation of independent variable?
Interpretivism: there are multiple realities, which we can’t investigate neutrally
Interview: Interviewing someone (1 to 1, or in a group) to gather data
Mediating variable: between independent & dependent variable, explains relationship
Moderating variable: influence relationship (strengthen or weaken)
Observation: Observe through your senses to describe a setting, in the field
One group, pre&post test: Observation before → treatment → observation (1 group)
Overt observation: People know you are observing them
Paradigm: set of shared assumption/ways of thinking
Participant observation: The researcher takes part in the situation he is observing
Positivism: there is 1 truth, which we can investigate objectively
Pre test/post test control group: Observations before Static group comparison
Quasi-experiment: Experiment, can be 1 group, no control of variables, no random
assignment
Questionnaire: predefined set of questions
Reflexivity: Researchers should reflect on what might influence their ethnography
Reliability: You are consistent with measuring
Simulation: Experiment done by simulation of the real world
Solomon group design: 4 groups (both static group & pre / post test control group)
Static group comparison: 1 group receives treatment, 1 does not, comparison afterwards
Survey: Obtain same kind of information from large group standardized & systematically
(don't confuse with questionnaire)
Systematic observation: Plan in advance what you will observe
Triangulation: using multiple methods/strategies/theories to enhance validity
True experiment: Experiment comparing 2 groups, controlled setting, random assignment
Uncontrolled trial: Quasi-experiment, but no measuring before & after
Validation: Design science: testing an artifact without applying it in real context
Validity: You measure precisely what you want to measure
, HC1
- Inductive research: develop theory based on data (theory-building)
- Deductive research: formulate assumptions → test them
- Qualitative research: no numerical data (observation, interview)
- Quantitative research: numerical data (questionnaire)
Rigor: 1. Systematic conduct (research steps taken rationally, logical relationships)
2. Validity (Appropriate process used, findings indeed come from data)
Relevance. Relevant to who? practitioners, academics, etc
HC2
Philosophical paradigms (paradigm: set of shared assumption/ways of thinking)
Paradigm = ontology (is there such thing as reality?) + epistemology (how do we come to
reality?)
1. Positivism.
a. Ontology: there is 1 reality / truth
b. Epistemology: We can investigate reality objectively
Goal: find universal laws, disprove them and not confirm them (black swan theory)
3 important notions:
- Reductionism (split research in smaller parts)
- Repeatability (other researchers should get same results)
- Refutation (hypothesis should be disprovable)
(+) objective, testing causal relationships
(-) reductionism sometimes (almost) impossible
2. Interpretivism.
a. Ontology: there are multiple subjective realities
b. Epistemology: investigation through social constructs, not neutral
(+) high validity, high data quality
(-) more bias, hard to reproduce, long process, ‘non-scientific’
3. Critical research.
a. Ontology: multiple realities, but reality has dominating properties
b. Epistemology: investigate through social construct, also empowering people
Enhance validity through triangulation: use multiple methods (important for interpretivism)
HC3
Requirements for formulating RQ: Efficient (is it exactly what you want to know?) and
Steering (which type of knowledge & data you need)
Types of RQ: 1. Descriptive (describe something accurately)
2. Explanatory (demonstrate through which process)
3. Predictive (predict future cases)
4. Evaluative (assess situation)
5. Prescriptive (provide instructions)
Literature review types: I Ad hoc (searching google scholar), II Systematic process
Steps: 1. Search (google scholar etc, check references)
2. Assess, read & evaluate (assess quality, use grey literature only for motivation)
3. Combine & write (combine findings concept-centric, structure findings)
Conceptual model: develop by identifying variables & their relationships
- Moderating variable: influence relationship (strengthen or weaken)
Belangrijke woordenlijst A-Z:
2x2 factorial design: Experiment, test 2 interventions in 1 sample
Action research: research aimed at solving a practical problem
Case study: investigating a contemporary phenomenon in real-life context
Covert observation: People don’t know you are observing them
Critical research: paradigm seeking to empower people
Deductive research: test formulated assumptions
Design science: Scientifically solving a problem with innovative artifacts
Ethnography: Descriptive study, aimed at understanding something thoroughly (verstehen)
Evaluation: Design science: testing an implemented artifact in real context
Experiment: isolate cause & effect in controlled situation
External validity: Are results generalizable?
Fabrication: Researcher makes up data himself
Falsification: Researcher changes data to change results
Hawthorne effect: When subject behaves differently because someone is watching
Inductive research: develop theory based on data (theory-building)
Internal validity: Are measurements really because of manipulation of independent variable?
Interpretivism: there are multiple realities, which we can’t investigate neutrally
Interview: Interviewing someone (1 to 1, or in a group) to gather data
Mediating variable: between independent & dependent variable, explains relationship
Moderating variable: influence relationship (strengthen or weaken)
Observation: Observe through your senses to describe a setting, in the field
One group, pre&post test: Observation before → treatment → observation (1 group)
Overt observation: People know you are observing them
Paradigm: set of shared assumption/ways of thinking
Participant observation: The researcher takes part in the situation he is observing
Positivism: there is 1 truth, which we can investigate objectively
Pre test/post test control group: Observations before Static group comparison
Quasi-experiment: Experiment, can be 1 group, no control of variables, no random
assignment
Questionnaire: predefined set of questions
Reflexivity: Researchers should reflect on what might influence their ethnography
Reliability: You are consistent with measuring
Simulation: Experiment done by simulation of the real world
Solomon group design: 4 groups (both static group & pre / post test control group)
Static group comparison: 1 group receives treatment, 1 does not, comparison afterwards
Survey: Obtain same kind of information from large group standardized & systematically
(don't confuse with questionnaire)
Systematic observation: Plan in advance what you will observe
Triangulation: using multiple methods/strategies/theories to enhance validity
True experiment: Experiment comparing 2 groups, controlled setting, random assignment
Uncontrolled trial: Quasi-experiment, but no measuring before & after
Validation: Design science: testing an artifact without applying it in real context
Validity: You measure precisely what you want to measure
, HC1
- Inductive research: develop theory based on data (theory-building)
- Deductive research: formulate assumptions → test them
- Qualitative research: no numerical data (observation, interview)
- Quantitative research: numerical data (questionnaire)
Rigor: 1. Systematic conduct (research steps taken rationally, logical relationships)
2. Validity (Appropriate process used, findings indeed come from data)
Relevance. Relevant to who? practitioners, academics, etc
HC2
Philosophical paradigms (paradigm: set of shared assumption/ways of thinking)
Paradigm = ontology (is there such thing as reality?) + epistemology (how do we come to
reality?)
1. Positivism.
a. Ontology: there is 1 reality / truth
b. Epistemology: We can investigate reality objectively
Goal: find universal laws, disprove them and not confirm them (black swan theory)
3 important notions:
- Reductionism (split research in smaller parts)
- Repeatability (other researchers should get same results)
- Refutation (hypothesis should be disprovable)
(+) objective, testing causal relationships
(-) reductionism sometimes (almost) impossible
2. Interpretivism.
a. Ontology: there are multiple subjective realities
b. Epistemology: investigation through social constructs, not neutral
(+) high validity, high data quality
(-) more bias, hard to reproduce, long process, ‘non-scientific’
3. Critical research.
a. Ontology: multiple realities, but reality has dominating properties
b. Epistemology: investigate through social construct, also empowering people
Enhance validity through triangulation: use multiple methods (important for interpretivism)
HC3
Requirements for formulating RQ: Efficient (is it exactly what you want to know?) and
Steering (which type of knowledge & data you need)
Types of RQ: 1. Descriptive (describe something accurately)
2. Explanatory (demonstrate through which process)
3. Predictive (predict future cases)
4. Evaluative (assess situation)
5. Prescriptive (provide instructions)
Literature review types: I Ad hoc (searching google scholar), II Systematic process
Steps: 1. Search (google scholar etc, check references)
2. Assess, read & evaluate (assess quality, use grey literature only for motivation)
3. Combine & write (combine findings concept-centric, structure findings)
Conceptual model: develop by identifying variables & their relationships
- Moderating variable: influence relationship (strengthen or weaken)
