  Block-based programming environments such as Scratch are an essential entry
point to computer science. In order to create an effective learning environment
that has the potential to address the gender imbalance in computer science, it
is essential to better understand gender-specific differences in how children
use such programming environments. In this paper, we explore gender differences
and similarities in Scratch programs along two dimensions: In order to
understand what motivates girls and boys to use Scratch, we apply a topic
analysis using unsupervised machine learning for the first time on Scratch
programs, using a dataset of 317 programs created by girls and boys in the
range of 8-10 years. In order to understand how they program for these topics,
we apply automated program analysis on the code implemented in these projects.
We find that, in-line with common stereotypes, girls prefer topics that revolve
around unicorns, celebrating, dancing and music, while boys tend to prefer
gloomy topics with bats and ghouls, or competitive ones such as soccer or
basketball. Girls prefer animations and stories, resulting in simpler control
structures, while boys create games with more loops and conditional statements,
resulting in more complex programs. Considering these differences can help to
improve the learning outcomes and the resulting computing-related
self-concepts, which are prerequisites for developing a longer-term interest in
computer science.
