Today’s blogpost is brought to you by Sami Murphy.
I have been conducting research since I was a sophomore in college, meaning that I have been participating in data collection and analysis processes for almost 5 years. Throughout my brief career as a researcher, I have worked in various research settings. I started my research career by working in a neuroscience lab (what is neuroscience?) that investigated the neural substrates of language, otherwise known as the way our brain works and adapts when processing or utilizing language. While doing this, I also started doing research at a local children’s hospital investigating the effects of traumatic brain injuries, epilepsy and seizures, and other critical cases in children. I spent a great deal of time working at the local children’s hospital and have been fortunate enough to publish a lot of research that was conducted there. While achieving my graduate degree and working on a psychology-related thesis project, I started working at the STEM Center at SIUE and assisting with a number of nationally funded educationally based research projects. This is where I currently work and perform the majority of my research!
Reading that, you might have a lot of questions…
How do you collect data for these various projects?
How do you come up with results?
What does that mean?
How does it work?
To begin, there are two main types of research: qualitative and quantitative. Qualitative research contains non-numerical data, meaning that there are no numbers involved and no statistics. Qualitative data collection may involve interviews with participants or even observations of what a participant is doing. The analyses for this type of research can be very subjective and up to interpretation. Qualitative research analyses often involve numerous people to ensure that the interpreted results are reliable and aren’t based on one researcher’s opinions and biases. Quantitative research contains numerical data and relies on statistical processes for analysis. Quantitative data collection may include a survey that can be transferred in a numerical total or a test that measures something very specific. The analyses for this type of research are not very subjective and rely on numbers to show validity and statistical strength. Quantitative research analysis involves a lot of equations. Luckily, modern technology has allowed for the creation of computer programs that run detailed statistical equations for researchers and it only takes a matter of seconds. There are even times that we are able to combine qualitative and quantitative research to create an even more reliable research project and provide more detailed results. This is called mixed methods.
To give some better examples, here are brief explanations of projects I have worked on and which type of research they fall into. When researching a child’s memory abilities following a brain injury, a series of tests can be utilized to produce numerical data, or quantitative data, that can be used to better understand the effects of a brain injury on specific types of memory. When researching the change in a child’s interest in STEM over time, a series of interviews can be conducted to gather qualitative data that can be coded and interpreted. There are many ways that you can add both quantitative and qualitative aspects to studies. Observational data could make a quantitative brain injury memory study stronger, or a survey could make a qualitative child interest study stronger. Mixed model studies are very convenient when attempting to get more detailed data.
No matter the type of data collected, doing research is a great way to contribute to society as a whole. By contributing to research, you are indirectly helping someone in the future. That someone may be a scientist, a clinician or physician, a teacher, a child in school, someone that has been affected by something out of their control, or even the environment. The possibilities are endless! If you are interested in learning more about research, stay up to date with our blog and try out some of our citizen science app activities. These apps allow for citizens to easily contribute to scientific data collection via virtual means. This data collection helps scientists to produce studies that will later get published and help our communities.