Week 7 Experiment

For my experiment, I decided to look at gender diversity in the CS Department. For my dataset, I took the text of all of the students who are TA's this semester and classified them as either male or female based on their names. Below are the results.

Figure 1. # of TA's by gender for each course level

Figure 2. # of HTA's by gender for each course level

Figure 3. # of HTA's by CS Field (Upper Level courses only)

In figure 1, we can see that for intro level courses, there are an fairly even number of male and female TA's. However, in intermediate and upper level courses, there are almost double the number of male TA's compared to female TA's. In non-concentrator courses (cs0020, cs0030, cs0100) there are slightly more female TA's than male TA's.

I then wanted to take a look at gender diversity for the head TA's. There are significantly more male TA's and female TA's for intro and upper level courses, but the male-female ratio for intermediate and non-concentrator courses are fairly even (3:2 and 2:4 respectively).

Since the differences in male TA's to female TA's was so high, I decided to look at the different fields of CS to learn more about why this may be the case. I discovered that there were significantly more men than women in AI/ML courses (43 men to 12 women). There are also almost double the number of men in theory courses. Thus, ML/AI and theory courses at Brown seem to more more male dominated compared to other field in Computer Science.

I thought this project was really interesting and sheds some light on how the Brown CS Department is doing in terms of gender diversity. For a future project, it would also be really interesting to plot similar data, taking race into account.