1. The Research Process Interpretivist Positivist
1.Observation of an issue and exploration of existing research
2. Development of a research question
3. Quantitative or Qualitative?
4. Which method is most appropriate?
5. How will I get my participants?
I want my research to be:- Objective, value-free, scientific, credible, generalisable and statistical. I want to look for patterns,trends and correlations. Feelings can’t tell me anything about a population.
QUANTITATIVE
I want my research to gain an in depth understanding, a true insight of experiences, I’m not worried about being scientific, generalisable or objective, what’s the point of trying to be value-free, we all have values! QUALITATIVE
To collect numerical data I must use a very structured method such as:- Questionnaire with closed questions, Structured interviews,
Official statistics or conduct an experiment under controlled conditions. Numerical data
To get rich descriptive data I will need to allow participants to open up and discuss things in a natural way. I will need to use a flexible method such as:- interviews, observations, focus groups, diaries. Descriptive data
To be scientific and get an unbiased sample of my population I should use a form of random sampling, simple, stratified or systematic. I will need a sampling frame from an authority. When I have my participants selected I will contact them
I’m not going to generalise my findings so I don’t need a large sample and I can’t get in depth information from hundreds of people anyway I won’t have time so I’ll use opportunity, volunteer, snowball or quota sampling.

2. Quantitative Qualitative
6. Define the concept you are measuring? 7. Create a hypothesis/aim 8. Consider ethics 9. Collect data and analyse it
Quantitative
Qualitative
I need to say clearly how I will define the topic of study so that I can measure it. I need to devise scores for things so I can get numerical data. Operationalisation I should conduct a pilot study to check I have done this properly
I don’t need numerical data so I don’t need to restrict the meaning of the concept. I can wait and see what participants as long as I aim to keep the information relevant.
I must devise a specific prediction of what I will find to see if my data supports it or not
A broad aim for my research will do for now. I don’t need to restrict myself with a scientific hypothesis.
I must consider issues like, consent, sensitivity to issues, right to withdraw, deception of pps, confidentiality of data and privacy. I shouldn’t study people without them knowing my true aims but sometimes this may be necessary. If that’s the case I must debrief them at the end.
I will have raw data from questionnaires, interviews or experiment and will need to count up and collate frequencies of responses. I will have to display the data in the form of statistics and graphs. Then I can statistically analyse the data for correlations and patterns
I will have lots of descriptive data from interviews or observations. I cannot analyse this statistically and I would not want to. I must look for emerging themes of interest within the accounts of participants and then write about them in a descriptive way.

3. Conclusions and evaluation.
Quantitative
Qualitative
10. What conclusions can I draw from my findings?
11. Are my conclusions correct?
I need to look at the data and decide whether it supports my hypothesis. If there is a significant correlation or difference then I can accept my hypothesis.
I can draw conclusions based on what I actually found. This may be different from my original ideas. My conclusions could be broad overall ideas.
I wanted numerical data so I had to restrict the responses of my pps, this means I don’t have the full truth. Also I did not build much of a rapport with my pps so they may have answered falsely or given answers that made them look good (social desirability bias). I can’t really get a good understanding from statistical data so my research may lack validity. I can’t show cause and effect with a correlation, it may be coincidence.
Did I operationalise the concept properly? Have I measured the right thing? Did I have a representative sample so I can generalise my findings?
Science is about gaining the truth. I need to think about alternative explanations for my findings and problems with my research
I wanted rich descriptive data so I had to collect lots of data which is now difficult to analyse. If I repeated the research I wouldn’t get the same results again. I therefore have low reliability. Does this mean what I have found is invalid as it may not apply to a wider population? I can only be sure by repeating the research? This means I have low generalisability. Also validity may be compromised by the Hawthorne effect or by my own values and judgements. Going Native would be a problem is I did not maintain my objectivity during the research. I may be biased!
12. What’s Next?
I may need to consider further questions that could be researched around this topic. I could start again with a new question/hypothesis, I could further support my research with quantitative or qualitative research, I could combine methods, use different researchers, I could repeat my research in other settings. With enough work I may get published !!

4. More on issues to consider in research
Generalisability – Will I be able to apply my findings to the wider population?
Reliability – How will I ensure my research is consistent?
Operationalisation – Have I measured the concept properly?
Validity – How will I ensure my findings are accurate?
Ethics – Have I followed ethical guidelines and protected my participants?
Representativeness – Do my participants accurately represent the target population?
What other variables may affect the validity of my study? Demand characteristics, the Hawthorne effect, researcher bias, ambiguity, social desirability bias, lack of responses, interpretation of the data, biased sample, political motives
What about the time and cost involved?