While I have not spent much time teaching recently, I do have a variety of experience in the area—martial arts, 4th grade science, remedial algebra, and artificial intelligence—and hope to return to teaching someday. For me, the most difficult aspect of teaching is understanding the student’s perspective. It is easy to project your own biases, goals, and preferences on to the student. Not only is it wrong, but it can have a negative impact on the learning environment.
When I was studying martial arts, I enjoyed the training and I took it very seriously. For some reason it became a major part of my life and I dedicated much of my time and energy. As I became older and began teaching, I assumed my students had the same desire and focus. For the vast majority of them, that was just not the case. It wasn’t that they were weak or lacked fortitude—as I initially thought—they just had a different goal. Many were there for recreation, just to enjoy themselves; there is nothing wrong with that.
It has happened in reverse too. I have briefly taken up hobbies that I did not take seriously. A hobby that the instructor had dedicated their life to. I am sure they were just as infuriated with me as I had been with other students. When you take something seriously and others treat it flippantly, it is easy to feel disrespected or offended. It can be difficult to accept that people value things differently. Once I understood some students just wanted to train recreationally, I adapted my methods accordingly. I enjoyed teaching more and I think they enjoyed the classes more.
During my final year as an undergraduate, I taught a remedial algebra course for freshman college students. The students were conditionally accepted to the university and had to pass this course in order to stay. The content was basically a review of all the math most students would have learned prior to high school. We began with adding fractions and ended with factoring polynomials.
In my mind, these were all things that were simple and straightforward. Surely the reason the students did not already have mastery of these concepts was due to a lack of motivation. My plan was to teach concepts and demonstrate how useful some of this knowledge can be. There I am showing how easy it is to calculate 10% of a bill. I turn to the students and ask, “if 10% is $1.30, then what is 20%?” No response. A few did understand that it would be twice as much, but they could not tell me an exact amount. These were students that did know the multiplication tables.
Their difficulty was not with concepts or motivation, they just did not have the basic tools. They wanted to attend college and were willing to work to accomplish that goal. We spent most of the semester drilling the basics. While it might have been more interesting or rewarding to focus on the aspects I originally wanted to teach, learning the basics that should have already been part of their knowledge better served them. It is difficult to understand more advanced concepts if you constantly have to stop and pick up a calculator to answer 6 x 3.
During my second year of graduate school, I spent some time teaching science to 4th graders at local elementary schools. One of the first things I realized was that I had no idea what they already knew. Not only that, but I had no idea what they were even capable of understanding. It was a constant struggle for me to decide how much detail to give in explanations. How do you explain complicated concepts in terms of things a 10 year old already knows. It is a difficult task.
A few years later I taught a computer science course on Artificial Intelligence (AI) geared towards junior and senior undergraduates. Even though I was only a few years removed from being in the student’s seat for an identical class, I had trouble gauging their ability to follow what I was teaching. Part of the problem is that I am not teaching a younger version of myself; I am teaching a group of unique individuals with varying levels of experience and interest.
One of the focuses of the AI course was classical planning—a topic that I have little interest in and find quite boring. To me, working through planning assignments are tedious. I assumed the students would agree, so I blew through the material as quickly as possible. With the additional time, I introduced machine learning—a topic not usually discussed in this course. I put in a great deal of time into the lectures and truly felt they were my best lectures of the course.
At the end of the quarter, I asked the students to describe their favorite and least favorite parts of the class. To my surprise, the majority of the students wished we had spent more time on planning. They enjoyed working through the “tedious” assignments. Even worse, they hated the lectures on machine learning.