  Nolan and Temple Lang (2010) argued for the fundamental role of computing in
the statistics curriculum. In the intervening decade the statistics education
community has acknowledged that computational skills are as important to
statistics and data science practice as mathematics. There remains a notable
gap, however, between our intentions and our actions. In this special issue of
the *Journal of Statistics and Data Science Education* we have assembled a
collection of papers that (1) suggest creative structures to integrate
computing, (2) describe novel data science skills and habits, and (3) propose
ways to teach computational thinking. We believe that it is critical for the
community to redouble our efforts to embrace sophisticated computing in the
statistics and data science curriculum. We hope that these papers provide
useful guidance for the community to move these efforts forward.
