An essential skill for STEM undergraduates is the ability to understand the world by manipulating, visualizing, and analyzing data to make or evaluate claims. Current online debate, without peer-reviewed literature, explores which of two common R syntax environments (base R or tidyverse) is best for teaching novice R users. In an in-person undergraduate course on evolutionary biology, we implemented two coding curricula: one using base R (n = 49 students) and the other using tidyverse (n = 58 students). We compared these two curricula using several dimensions of student success: interpretation of syntax, creation of appropriate data visualizations and analyses, and an absence of sex bias in performance. A linear model revealed prior experience had the largest estimated effect, followed by syntax environment; sex had the smallest effect. Pedagogical approaches that ensure students have repeated opportunities for practice and that implement techniques to overcome student frustration and anxiety are likely more important than syntax environment when learning coding in biology classes. Furthermore, the small effect of sex combined with the high proportion of females in the biological sciences suggests introducing computer programming in biology may allow females to discover interest and ability that they may not have had if computer programming was the sole propriety of computer science departments.