Leading a peer mentoring scheme means that I get a constant stream of messages and emails from first- and second-year psychology students. It is that time of the year where second-year students are choosing their final-year units and planning what they want to do for their final year research project (their dissertation).
The most common question I receive is: ‘Which is easier, quantitative or qualitative research?’ Of course, some researchers will have some biased views on this – probably based on what they are involved with themselves. But any good researcher will know that there is no straightforward answer to this question.
I remind students that they need to consider their research question. I conceptualise it between two questions: ‘what’ and ‘why’
The ‘what’ questions typically relate to a research question that requires a quantitative analysis to get a view of what variables influence other variables, or even how and to what extent one variable influences other variables (note that I use influence here, but such a question may also seek to establish causality).
The ‘why’ question, in my mind, would typically require a qualitative analysis. Why are students not receptive to feedback? Why is there a spike in teenage STD contraction? These questions will require asking samples from the population you’re interested in.
Of course, as with most things, there are some exceptions to this rule. For example, a ‘what’ question may require a qualitative analysis. Such as: ‘How does stress at work relate to quality of life in people working night shifts?’ This inevitably means seeking out a sample of people working nights shift.
Alternatively, a ‘why’ question may require a quantitative analysis. But researchers tend to form these ‘why’ questions in the way of a hypothesis. They may have an initial ‘why’ question, but then reflect this in an experimental hypothesis. For example: Why a consumer behaves in a certain why or how they’d feel if a certain situation were to take place.
A lot of students are also concerned about the time consumption of research for a final-year dissertation project. It is important to recognise that one approach (quantitative versus qualitative) is not necessarily faster than the other.
I conceptualise the time consumption of the methods as following, and find this helps students (for quantitative, then qualitative respectively):
data collection > data analysis
data collection < data analysis
I have also noticed something peculiar, and I believe I may have experienced this myself before getting more involved in research: statistics anxiety.
Many students are coming to me asking how hard statistics is and whether they will get lots of support from their supervisors on their ‘independent’ projects.
I know many current final-year students, and second-year students, who are opting for a qualitative research project just to avoid running statistical analyses. It is apparent that this reasoning for choosing a qualitative project is a wrong one, especially the aforementioned discussion on choosing a method based on your research question.
This raises an important question: Are universities failing to engage students in Research Methods and Statistics? Unfortunately, in my own opinion (as a student), the answer to this question is yes, yes they are.
However, there is a way to fix this. Universities need to realise that the current way of teaching Research Methods and Statistics is failing. I have had countless lectures on different statistical tests, which are important, but I have had to retain knowledge on different pieces of logic and philosophy, which is impractical. At the end of the day, the real world of research does not require this knowledge. It requires you to:
- Formulate a research question;
- Read the literature;
- Design an experiment (or qualitative alternative);
- Collect data;
- Analyse that data;
- Interpret your results.
In my second-year I had a multiple choice question section of my examination, which I strongly believe was pointless on many levels. I failed this section of the examination. The second half of the examination required me to read some SPSS outputs, interpret them, and write up design, results, and discussion (first paragraph) sections of a laboratory report.
I excelled this section of the examination. This, of course, is far more representative of real-life research. I also wonder why students are not being assessed on their quantitative knowledge via using software such as SPSS – this is one of the most common statistics software that researchers use in the real world.
The concern that I have here is that Research Methods and Statistics is not being taught, nor examined, in a practical or realistic way. Another concern I have is that universities are giving the limelight to quantitative methodology, and not giving enough to qualitative methodology. In my first- and second-year, I had six lab classes that were quantitative-based and only two that were qualitative-based – both of which based on thematic analysis and nothing else.
This will lead students to believing that qualitative methodology is secondary to quantitative methodology. I cannot help but find the irony in this. Psychologists, with a wealth of knowledge on behaviour and attitudes, are still yet to develop curricula that will make the researchers of tomorrow. Universities have a duty to teach students to decide for themselves which is most important. In the case of those lab classes I mentioned above, surely this should be a 50/50 split.
I think academia needs to reflect about the current way in which Research Methods and Statistics is taught. The discipline really must pay attention to the apparent trade-off between quantitative and qualitative methodology and the impression that it makes on students.
Callum Mogridge is an undergraduate psychology student at the University of Manchester. He leads the peer support on the degree programme.