1.6 Creating research questions and studies
Consider the following scenario:
While at Cafe C one day enjoying a small, organic, almond-milk, half-strength, decaffeinated latte2, Nim sighed, ‘Exams start next week. I suppose we’ll all start feeling stressed soon.’
‘Ah,’ Jane said, ‘I had better buy more teabags then.’
‘Tea bags? Why?’’ asked Nim, not unreasonably.
‘Everyone knows that Earl Grey tea relaxes students…’ said Jane, looking upwards then closing her eyes dreamily.
‘How do you know?’ Nim retorted, unintentionally aggressive.
‘It does,’ snapped Jane. ‘Earl Grey relaxes people.’
Nim considers studying Jane’s assertion as a practical SCI110 project.
- Nim needs to determine a population to study. Which of these would be a useful and practical population to use? Or is there a different population that is ‘better’ to use? Explain your reasoning.
- All university students.
- Female university students about to do an exam.
- USC students.
- Queensland university students.
- Identify an outcome that Nim can measure to answer the research question. Justify your answer.
- Which of these comparisons do you think Nim should use? Why?
- Between drinking Earl Grey tea and coffee.
- Between drinking Earl Grey tea and black (ordinary) tea.
- Between drinking Earl Grey tea and water.
- Between exam time and other times of the semester.
- Between students and non-students.
- Explain why ‘Between before and after drinking Earl Grey tea’ is not a comparison.
- Construct a well-worded interventional research question that Nim can ask to assess Jane’s assertion, clearly identifying P, O, C and I.
- Briefly describe how to set up an experimental study for answering your proposed research question.
- Construct a well-worded relational research question that Nim can ask to assess Jane’s assertion, clearly identifying P, O and C.
- Briefly describe how to set up an observational study for answering your proposed research question.
- List any terms that may need defining.
- Using this research question, identify the response and explanatory variables, and hence the data that needs to be collected to answer the question.
Sometimes called a Why-Bother…↩︎