Horton Works to Improve Reproducibility,
Equity as New JSDSE Editor
Nicholas Horton is Beitzel Professor of Technology and Society (statistics and data science) at Amherst College. He co-chairs the National Academies Committee on Applied and Theoretical Statistics and has been involved in a number of data science initiatives. Horton previously served as an associate editor, section editor, and guest editor for the Journal of Statistics and Data Science Education. Upon his appointment as editor in 2022, we asked him a few questions about the journal and his editorial goals.
Why and when was JSDSE established?
The journal, originally named the Journal of Statistics Education, was founded in 1993 as an open-access journal with no author fees by North Carolina State University. It was started by the late Jackie Dietz and managing editor Tim Arnold. Their goal was to provide an outlet for high-quality articles about statistics education that could allow statistics educators to share their knowledge and be recognized for their work. It was founded as an electronic journal at a time when relatively few existed. The journal was renamed in 2021 to acknowledge the growing role of data science.
Who is JSDSE for?
Articles in JSDSE are intended to be broadly accessible and to address the broad landscape of statistics and data science education. My hope is that instructors (from K–12 to graduate level), curriculum developers, and educational researchers benefit from the articles published.
Would you tell us a little about the other JSDSE editors?
The journal wouldn't exist without the efforts of the editorial board, which consists of six section editors (Jennifer Green, Matt Hayat, Laura Le, Kelly McConville, Kevin Ross, and Juana Sanchez) and 33 associate editors with diverse backgrounds and expertise. Each is responsible for carrying out peer-review of the papers submitted to the journal, making a recommendation regarding suitability for publication, and providing useful feedback to authors.
The journal also wouldn't exist without the hundreds of peer reviewers who contribute their time and expertise on behalf of the journal. I’m often struck by their insights and helpful ideas. The continuing pandemic has stretched everyone, but the reviewers continue to serve their critical and effective role.
Behind the scenes, ASA Journals and Publications Manager Eric Sampson, Editorial Coordinator Jean Scott, and Rebecca Corpier from Taylor & Francis help keep everything moving.
Why did you accept the position as editor?
I agreed to be editor because I believe in the mission of the journal as an open-access venue for data science and statistics educators to share best practices, research findings, and approaches to teaching. I’ve been involved as a member of the editorial board since 2010, serving as the section editor for data sets and stories and section editor for data science. As editor, it’s been great to see how all the parts and pieces come together.
Have you made any specific changes to the journal, or do you plan to?
Former editor Jeffrey Witmer and his predecessors left me the journal in excellent health, so one of my main goals is to continue to do what they’ve done! In addition, I have been planning some other initiatives, including a special issue on reproducibility and responsible workflow and additional growth of our coverage of data science education. Finally, it’s important to ensure the journal encompasses diverse, equitable, and inclusive characteristics. There are too many barriers to participation by authors, reviewers, and editorial board members. I’m committed to working on these important issues during my tenure as editor.
What is the most enjoyable part of being a JSDSE editor?
My work as an editor has been keeping me busy: There’s a lot involved in processing the approximately 200 submissions per year and publishing three issues per year. Each paper is considered by two or three peer reviewers plus an associate editor and me. What’s been most rewarding and enjoyable has been seeing how those comments and critiques shape and improve a paper. While multiple iterations are needed, the end result is worth the effort by the authors and review team.