Research Methods

Quantitative

Quantitative

• Numerical

• Tests ideas

• Measurable

• Objective

Qualitative

• non numerical

• describe and understand

• subjective

Experiments

• Quantitative

• deductive (starts with an idea to test)

• cause/effect

• IV/DV

• hypo

True experiment

• lab/field

• manipulated IV

• allows for random allocation to conditions

• better control of extraneous variables due to test environment

Quasi experiments

• no manipulated IV ——> pre existing variable about the participant

• less controlled extraneous variables

  = more doubt over cause/effect

Natural Experiment

• no manipulated IV ——> a naturally occuring change

• less control of extraneous variables

  = more doubt over cause/effect

• Often uses a pre/post test design

Correlation

• quantitative

• deductive (starts with an idea to test)

• co-variables

• testing a relationship between two variables

• no manipulated variables —> measure existing variables

• know the direction and strength of correlation (r-value)

Case Study

• qualitative

• longitudinal

• instrumentals vs intrinsic

• mixed methodology (triangulation of method)

• mix of data and inferences

• informs theory

• inductive (starts with data —→ theory)

• difference between intrinsic/instrumental case studies

Survey

• Quantitative

• information gathering (no additional agenda unlike correlations)

• standardised

• closed-ended questions

• often uses rating scales

Interviews

• qualitative

• inductive (starts with data —> theory)

• understanding experience from the participant perspective

• often uses inductive content analysis (ICA) to analyse data

• Types (and features of these)

  • unstructured

  • semi-structured

  • focus-groups

• inductive content analysis

Naturalistic Observation

• qualitative

• inductive (stars with data —> theory)

• takes place in the participants natural environment

• can collect quantitative data

  e.g tallies

• can collect qualitative data —> often uses content analysis (ICA) to analyse this

• no manipulated variables/interference with the environment (unlike experiments)

• Watching

  • overt/covert

  • participant/non participant

Sampling techniques

• random

• volunteer

• purposive

• snowball

• opportunity/convenience

(EC) During

• protection from harm (physical and psychological)

• right to withdraw

• informed consent (3 parts: knowledge, willingness, capacity)

• deception

• debrief

Reporting

• integrity —> data fabrication/p-hacking

• confidentiality

• sharing data verification purposes

Applying Findings

• social implications

• handling of sensitive results

• creating ethically beneficial/useful interventions interventions and strategies

Generalisability: To the target population

Quantitative: population validity

Affected by: sample (size, method, characteristics/demographics)

Generalisability: Beyond the study

Quantitative: Ecological Validity

Affected by: level of control/mundane realism

Generalisability: To the theory

Quantitative: construct validity (extent to which a test/tool accurately measures the theoretical construct it intends to measure)

Transferability: To the target population

Qualitative: representational generalizability

Affected by: sampling method, sample demographics

Transferability: Beyond the study

Qualitative: case to case transferability

Affected by: contexts/cases that share similar characteristics

Transferability: To the theory

Qualitative: theoretical generalizability

Inductive Content Analysis (ICA)

1) read / re-read

2) coding

3) categories

4) conclusions

Bias

• leads results towards a particular answer

• reduce credibility of research meaning data is not accurate

• can originate from researcher or participant

Sampling bias, Reporting bias, Confirmation bias, Leading questions bias

Credibility

• quality of being trusted/believed

• shouldn’t be impacted by bias

Social desirability bias, Dominant response bias, Sensitivity bias, Demand characteristics, Reactivity

Personal Reflexivity

reflections on person beliefs and expectations (bias) in attempt that they don’t impact conclusions of the study

Epistemological Reflexivity

reflections on research choices, planning to overcome research weaknesses and being aware of limitations when conclusions are drawn

Double-Blind

neither participant nor researchers know who is who to reduce risk of researcher expectations/bias

Reflexivity journal

personal reflexivity & credibility checks

Triangulation

Way to decrease bias

Method: use multiple research methods

Researcher: use multiple researchers in recoding, analysis and reporting

data: gather data from multiple recourses

Data saturation

where no more ideas can be extracted from the data