On this page I want to speak to experiences in my undergraduate degree that contributed to my development as an academic. To do so, I'll refer to some of the University of Victoria's 10 Core competencies, which are skills and attributes valued by employers that UVic tries to teach studnets throughout their programs. In an effort to be transparent, I want to talk about some competencies I feel strong in, and also some areas I am weaker in. Its important to me to acknowledge areas that need work, communicate that to my peers, and commit to improving those skills.
Research and Analysis
For almost two and a half years I have been an active part of research in the Theoretical and Applied Neuroscience (TAN) Lab at UVic. I started as a research assistant (RA) and have since advanced to independent research projects and supervision of other research projects. An indicative example of my research competency is my first independent research project, an experiment on the neural bases of clinical decision making. This involved a multi-step progress in an area I had little-to-no experience in. First, I conducted an extensive literature review. I had first thought that this process would be similar to that of other work I have done in classes, but quickly learned that my methods were not sufficient to meet the standards of real academia. Through trial and error, and seeking help from more experienced peers, I learned a new method of literature review that surpassed my previous style in depth, efficiency, and overall understanding. Then, I set out to learn and implement both data collection and analysis techniques throughout the data gathering phase of the project. Data collection involved an extensive training process, some of which I learned during my time as an RA. I augmented supervised learning with data collection trials on myself to better understand how participants see the experiment. Data analysis was certainly the most difficult aspect of the process to learn, as I had learned nothing about the necessary techniques for this data set in my time as an RA. Again, this process took a lot of self-teaching through trial and error and consulting with my more experienced supervisor. By the time this process was over, I had learned to investigate, conduct, and analyze my data. This project has since been presented at an academic conference (NOWCAM, 2019), and is currently in the writing process for my honours thesis and eventual journal submission.
Since I finished data collection for my first project, I have used the basic skills I learned and applied them to numerous other TAN Lab projects, such as research on fatigue and teamwork, and working with novel research methodology. My work has earned me some awards (NSERC USRA, JCURA) and a supervisory role in other projects. In my time in the TAN Lab, I have consistently shown research skill through identifying the need for new experiments, initiating these new projects, and problem solving for both my own and other projects. All of my achievement in research was founded on skills I learned conducting my first research project, which I have consistently developed over time to build a framework for my future career in neuroscience.
Since I finished data collection for my first project, I have used the basic skills I learned and applied them to numerous other TAN Lab projects, such as research on fatigue and teamwork, and working with novel research methodology. My work has earned me some awards (NSERC USRA, JCURA) and a supervisory role in other projects. In my time in the TAN Lab, I have consistently shown research skill through identifying the need for new experiments, initiating these new projects, and problem solving for both my own and other projects. All of my achievement in research was founded on skills I learned conducting my first research project, which I have consistently developed over time to build a framework for my future career in neuroscience.
Project and Task Management
I have achieved reasonable success in project and task management primarily through the use of my task scheduling system. The basics of the system, which I learned shortly after high school and have used since, are that each task associated within a larger project is assigned a letter (A, B, or C). “A” level tasks are of the upmost importance, and should be completed before other tasks. “B” tasks are of somewhat importance, and “C” tasks are of the least relative importance. By organizing productivity this way, tasks can be assigned to others in order of importance and urgency. For example, when I personally use this system for academics, I assign each task in a given month “A”, “B”, or “C” and use that for time management. I set “letter goals” weekly, where I commit to finishing at least one “A” task, two “B” tasks, and 3 “C” tasks.
This system can be beneficial for group projects as well, as I found when supervising a lab project this past summer. A group of researchers and I were tasked with completing an ethics package for a relatively complicated study that would require all of our combined efforts. An ethics package consists of 15-20 different sub-sections to complete that describe different aspects of the research project. We worked together to assign each section a letter based on its importance to the overall submission. For example, “Description of Research Methods” was an “A” task, while “Contact Information” was a “C” task. Using this and time-based “letter goals”, we were able to divide the work relatively easily and completed the project punctually. This method becomes even more helpful when multiple projects are ongoing simultaneously. Letters can be assigned to tasks not only according to the project they fit within, but also relative to other projects. If one project is more time sensitive than others, “A” tasks from those other projects may be shifted to “B tasks to reflect this, and vice-versa.
I have used the letter system for project management through my university career, which has led to success in time management for academics and in the workplace. I still use it for nearly every scheduled task in my life, and implement it with reasonable success in the work environment when managing group projects. One absent portion of my project management competency is my available toolset for when my ABC system may not work. I rely heavily on scheduling everything with this method, and when situations arise where it is not appropriate my task management may suffer.
This system can be beneficial for group projects as well, as I found when supervising a lab project this past summer. A group of researchers and I were tasked with completing an ethics package for a relatively complicated study that would require all of our combined efforts. An ethics package consists of 15-20 different sub-sections to complete that describe different aspects of the research project. We worked together to assign each section a letter based on its importance to the overall submission. For example, “Description of Research Methods” was an “A” task, while “Contact Information” was a “C” task. Using this and time-based “letter goals”, we were able to divide the work relatively easily and completed the project punctually. This method becomes even more helpful when multiple projects are ongoing simultaneously. Letters can be assigned to tasks not only according to the project they fit within, but also relative to other projects. If one project is more time sensitive than others, “A” tasks from those other projects may be shifted to “B tasks to reflect this, and vice-versa.
I have used the letter system for project management through my university career, which has led to success in time management for academics and in the workplace. I still use it for nearly every scheduled task in my life, and implement it with reasonable success in the work environment when managing group projects. One absent portion of my project management competency is my available toolset for when my ABC system may not work. I rely heavily on scheduling everything with this method, and when situations arise where it is not appropriate my task management may suffer.
Continuous Learning
An essential skill for any academic researcher is upkeep with new knowledge relevant to their field. I frequently try to practice this skill within the scope of my research projects, but also within the broader scope of neuroscience.
Once I started conducting research in specific areas of neuroscience (learning, decision making, cooperation), I found myself moving away from understanding other areas (cognitive control, memory, perception, etc.). This kind of behaviour is not a good way to start a career in research, in my opinion. It is important to have a strong understanding of your own research topics, but knowledge in others will help build your library for future work and appreciation for other disciplines. To put this into practice, I set 3 distinct learning goals over the past summer to supplement my research projects. First was an ongoing goal to continuously check for new research in the field of interbrain neural synchrony, my primary research topic, to ensure that I can consider any new findings into my study. It is tempting to conduct research based on what I read when I started, so I try to frequently search for new papers, conference presentations, and other resources on the subject. Second, I set a practical skills goal to become proficient in coding using MATLAB, both for analysis and creating experiment tasks. This is an absolutely essential skill for anyone with a career in neuroscience research (not MATLAB specifically, more coding in general), and by starting early I am building a stronger base for coding expertise going forward. Finally, my last learning goal was to understand the topic of cognitive control. This topic is not explicitly studied within our lab, with the exception of one recent publication, but it has growing interest in the neuroscience community. As researchers become more able to study this unique neural construct, it will become a more popular site of inquiry. By studying it now and building a basic knowledge, I open myself to understanding new work and possibly studying it in the future myself.
While I was only able to fully complete my second learning goal for the summer, I am still working on the other two. Once I complete those two, I will set two more. I want to be clear about my dedication to continuous learning, so I am logging my new educational endeavors on my learning blog page.
y philosophy going forward is that while I am a researcher, I am still a student, and should be pursuing new knowledge in any way I can.
Once I started conducting research in specific areas of neuroscience (learning, decision making, cooperation), I found myself moving away from understanding other areas (cognitive control, memory, perception, etc.). This kind of behaviour is not a good way to start a career in research, in my opinion. It is important to have a strong understanding of your own research topics, but knowledge in others will help build your library for future work and appreciation for other disciplines. To put this into practice, I set 3 distinct learning goals over the past summer to supplement my research projects. First was an ongoing goal to continuously check for new research in the field of interbrain neural synchrony, my primary research topic, to ensure that I can consider any new findings into my study. It is tempting to conduct research based on what I read when I started, so I try to frequently search for new papers, conference presentations, and other resources on the subject. Second, I set a practical skills goal to become proficient in coding using MATLAB, both for analysis and creating experiment tasks. This is an absolutely essential skill for anyone with a career in neuroscience research (not MATLAB specifically, more coding in general), and by starting early I am building a stronger base for coding expertise going forward. Finally, my last learning goal was to understand the topic of cognitive control. This topic is not explicitly studied within our lab, with the exception of one recent publication, but it has growing interest in the neuroscience community. As researchers become more able to study this unique neural construct, it will become a more popular site of inquiry. By studying it now and building a basic knowledge, I open myself to understanding new work and possibly studying it in the future myself.
While I was only able to fully complete my second learning goal for the summer, I am still working on the other two. Once I complete those two, I will set two more. I want to be clear about my dedication to continuous learning, so I am logging my new educational endeavors on my learning blog page.
y philosophy going forward is that while I am a researcher, I am still a student, and should be pursuing new knowledge in any way I can.