Karteikarten
Research methods
Karten in diesem Stapel (20)
- 1Within-subjects design Between-subjects design- Every participant is exposed to all levels of the independent variable
- Participant is exposed to one level of the independent variable - 2Correlational design- Variables are (not) related to each other, no IV or DV
- 3Quantitative methods Qualitative methods- Methods with number-data, deductive. Within, between, and correlation
- Methods with elaborate answers, inductive. Interviews - 4Causal claims Association claims Explorative questions- IV causes DV
- Variable is related to another variable
- What is the experience? - 5Independent variable Dependent variable- What you manipulate
- What you measure - 6Repeated measures Concurrent measures- Participants are exposed to the IV's at different times, you measure the DV twice
- Participants are exposed to the IV's simultaneously, you measure the DV once - 7Pros and cons of within-subjects design- Pro: fewer participants, less individual differences, more powerful
- Con: can be unethical or impossible, risk of giving away the hypothesis, order effects - 8Order effect Counterbalancing- The effect that practice, fatigue, or carryover can have on your data
- Making sure that participants experience the IV levels in different orders to get rid of order effects - 9Walking in different environments - within-subjects study- Good: within-subjects design, counterbalancing, urban environment is quiet
- Bad: experimenter walked with participant, tested only non-stressed, demand characteristics - 10Pros and cons of between-subjects design- Pros: participants don't know hypothesis, no order effects, useful when treatment cannot be reversed
Con: more individual differences, confounding variables, more participants - 11Post-test only design Pre-test, post-test design Matched pairs design- Measures are made after the exposure
- Measures are made before and after the exposure
- Participants are put in the condition based on e.g. their performance on a test - 12Eliminating systematic variability- Random allocation, pre-test, matched pairs design, or within-subjects design when possible
- 13Facebook and feeling of rejection - between-subjects study- Good: between-subjects design, different measuring methods
- Bad: unethical, parametric test on ordinal data - 14Pros and cons of correlational design- Pros: can be used when experiments are impossible or unethical, tells that there is a relation between variables
- Cons: cannot show cause-effect, often uses self-report - 15Willpower and diabetes therapy - correlational study- Good: correct use of design, seperates self-control and theories of self-control
- Bad: used parametric test on ordinal data, social desirability - 16Connectedness with nature and cognitive styles - correlational study- Good:
- Bad: social desirability, possible order effect, judgemental paper, claims of causation, wrong design (could have done an experiment) - 17Pros and cons of qualitative designs- Pros: detailed, in-depth, participant-led, meaningful, high level of ecological validity
- Cons: not generalisable, complex data, time-consuming - 18Important features of quantitative research Important features of qualitative research- Falsification, validity, and reliability
- Reflexivity, rigour, relevance, and resonance - 19Ultrarunner's experience - qualitative design- Good: ???
- Bad: ??? - 20Coding- Sensitising concepts (seeing different things in the same answer)
- Make themes
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- Psychology Karteikarten am Research methods, erstellt von Michella x am 07/05/2018.
- Erstellt von
- Michella x
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