Cana Fuest, PhD Candidate

People often categorize themselves by saying things such as, “I’m not good at math,” or, “I’m not a good writer.” These statements undermine the potential that everyone has to learn and grow and get good at things that they weren’t good at before.

As an example, for most of my life, I had not considered myself to be a “math person.” But during my PhD studies, I have become interested in data science, which requires some knowledge of mathematical concepts. I have even taken on the task of learning Python3 so that I can get a better handle on data science and machine learning. As someone without any sort of computer science background, I will say that I have felt like a kid trying to understand something very complicated. That is, until I started to see that I was grasping the concepts of Python. The realization that I am “getting it” has made me more determined to learn and master this programming language.

What I just described is something called building self-efficacy. Self-efficacy refers to someone’s belief in their ability to produce a desired outcome (Bandura, 1997). I began my PhD journey with an interest in the topic of self-efficacy, which evolved into a curiosity about artificial intelligence and recommender systems. But now I have come full circle to see how important the development of self-efficacy is in a learner to bring them to a place where they can see that they truly have the potential to learn challenging things.

Thanks for reading my reflection!

References

Bandura, A. (1997). Self-efficacy: The exercise of control. W.H. Freeman and Company.