For most of my life, I have been a science student. My high school course load focused on biology, chemistry and physics, and I completed a Bachelor of Science in university, even adding in some extra science courses as electives along the way. This science background has meant that every time I’ve encountered research, it’s been through the lens of the scientific method:
- Make an observation
- Ask a question
- Form a hypothesis, or testable explanation
- Make a prediction based on the hypothesis
- Test the prediction
- Iterate (make a new hypothesis or prediction based on what you learned)
For years, it didn’t even occur to me that there were other methods through which to conduct research.
Even now, although I’m well aware there are many, many, many different research methodologies and many ways to do research that aren’t the scientific method, I still find myself resisting and questioning non-scientific methods.
One of the first papers we were asked to read in our Research Methods course was Autoethnography: An Overview. This paper defines autoethnography as “an approach to research and writing that seeks to describe and systematically analyze personal experience in order to understand cultural experience”. Personal experience? This type of research is a far cry from the scientific method.
So I set about identifying and trying to reconcile my areas of resistance.
Resistance Area #1: Generalizability
I was still in the very first section of the paper, History of
I was glad to see this issue addressed straight on later in the paper- and explained in a way that I could get behind. In traditional social science research, conducted using the scientific method, it’s up to the researcher to make sure the researcher is generalizable. They do this by making sure they have a large sample size, random samples, etc. In autoethnography, it’s up to the reader to determine whether the research is generalizable. The reader gets to decide “if a story speaks to them about their experience or about the lives of others they know”. How cool is that?
Resistance Area #2: Bias
In research using the scientific method, bias is like that family member everyone is ashamed of. You try and keep it as far away from you as possible, you pretend it don’t exist, you try to change it for the better, and you don’t really talk about it openly. Researchers use methods like the double-blind method to try and remove bias from their research, and end the day saying “look Ma, no bias!”.
Autoethnographers, on the other hand, are over here saying “look Ma! There’s bias everywhere, and that’s okay!”.
It’s actually kind of refreshing.
As the paper itself stated: “…autoethnography is one of the approaches that acknowledges and accommodates subjectivity, emotionality, and the researcher’s influence on research, rather than hiding from these matters or assuming they don’t exist“.
While I like the scientific method a lot, I also really like honesty and openness, and not feeling misled. And I think this is where the scientific method can sometimes take us. The two contrasting papers that we read for our first EDCI 568 course could not have made this more clear.
The conclusion a reader comes away with after reading Why Minimal Guidance During Instruction Does Not Work was, well, that discovery, problem-based, experiential and inquiry-based learning weren’t actually all that great, and didn’t have any research backing them up as effective methods of instruction.
The conclusion a reader comes away with after reading Teaching for Meaningful Learning was that project, problem and
Two different papers. Two different conclusions. Citations of the exact same source to back up their claim. How does that even make sense? Bias, that’s how. Unexamined, hidden bias.
Autoethnography is looking better and better.
I’m pretty sure it’s going to take me a long time to get used to the existence of research methods that aren’t the scientific method. That method is pretty ingrained in my brain, and I like having black-and-white answers. But I can also see and appreciate the value of other research methods.
Learning and unlearning. Is this what graduate school is all about?