library("tidyverse")
install.packages("ggthemes")
library(ggthemes)

data_to_viz <- read_csv("data/data-to-explore.csv")

filter(data_to_viz, !is.na(gender)) %>%
  ggplot() +
  geom_bar(aes(x = subject, fill = gender), width = .5, position = "dodge") +
  labs(title = "Course Enrollment & Gender",
       subtitle = "Do we still have issues getting females students into STEM courses?",
       caption = "Are more male students taking science in online courses?") +
  theme_pander() +
  scale_x_discrete("Online Science Course", 
                   labels = c("AnPhA" = "Anatomy", "BioA" = "Biology",
                              "FrScA" = "Forensics", "OcnA" = "Oceanography",
                              "PhysA" = "Physics")) +
  scale_y_continuous("Enrollment")

Most schools are attempting to increase their recruitment for diverse populations in STEM. Specifically with regard to the perceived gender gap, this analysis explored enrollment in five online science courses. Data collected over four semesters was plotted comparing number of students enrolled by gender and course. Where students chose not to self-identify, those instances were eliminated from the data. For each of five online science courses offered, three showed a significant disparity where female enrollment far outweighed their male counterparts. The other two courses, Biology and Physics, were relatively close in enrollment. From this small sample, getting female students interested in science doesn’t seem to be the issue.