Zusammenfassung der Ressource
Overview of
Research Methods
- Types of data
- Primary Data- collected by researcher
themselves.
- Secondary Data- Collected by someone else, used by researcher.
- Quantitative Data- Numerical.
- Qualitative Data- Written/ Spoken, other forms (e.g. photos)
- Practical Issues
- Time and money- Some methods
are more costly or time
consuming.
- Requirements of funding bodies-
those funding research may select
the topic + type of data and the
presentation
- Personal skills & characteristics-
May affect the choice of method.
E.g. May struggle to establish the
rapport with interviewees.
- Subject matter- Some
topics/groups may be harder to
study than others.
- Research opportunity- If there is
an unexpected opportunity for
research, time consuming methods
(e.g. Questionnaires) won't be able
to be used.
- Ethical issues
- Informed consent- All participants have to agree to take part,
being fully aware of what the research is about.
- Confidentiality & Privacy- Mustn't reveal names or
personal details of participants.
- Effects on research participants- Must avoid physical or mental
harm on participants.
- Vulnerable groups- Extra care when working with
certain groups i.e. children, elderly, victims of crime or
mentally ill.
- Covert research- Some argue it's unethical as
people are unaware they're being studied,
however can be the only way.
- Theoretical issues
- Validity- Method which produces a true picture.
- Reliability- Consistent results when repeated.
- Representativeness- Sample is cross-section of the wider
group the researched is based on.
- Methodological perspective- Positivists prefer quantitative data;
Interpretivists prefer qualitative data.
- Theoretical perspective- Social action
(Micro) perspectives prefer qual. methods
for meaning; Structural (Macro) perspective
prefer quant. methods for society shaping
behaviour.
- Quantitative or Qualitative
- Positives- Quantitative: High
reliability, Bigger samples,
Generalisation, and Predictions of
behaviour.
- Interpretivists- Qualitative: High validity, More detailed;
However smalls samples so hard to generalise.
- Triangulation- Combing different
methods (e.g. Quant. + Qual.)