  In this paper, we replicated a Bayesian educational research project, which
explores the association between broadband access and online course enrollment
in the US. We summarized key findings from our replication and compared them
with the original project. Based on my replication experience, we aim to
demonstrate the challenges of research reproduction, even when codes and data
are shared openly and the quality of the materials on GitHub are high.
Moreover, we investigate the implicit presumptions of the researchers' level of
knowledge and discuss how such presumptions may add difficulty to the
reproduction of scientific research. Finally, we hope this article sheds light
on the design of reproducibility criterion and opens up a space to explore what
should be taught in undergraduate statistics education.
