The Journal of Statistics and Data Science Education Jackie Dietz Best Paper Award

The Journal of Statistics and Data Science Education (JSDSE) Jackie Dietz Best Paper Award was established in 2011 to honor Jackie’s contributions as the founding editor of the journal from 1993 to 2000. JSDSE (formerly the Journal of Statistics Education) was founded as an open-access journal with no author publication charges to help foster pedagogical discussions and to share best practices. More on Jackie’s many contributions to the journal and the profession can be found in Rossman and Dietz (2011) and Horton (2022). The Jackie Dietz award is presented annually to the best paper among all those appearing in JSDSE in the previous year.

What makes a “best” paper? Table 1 displays the names, authors, and year of publication for the first 13 recipients. Looking back at the winners, it’s clear that the winning papers are asking important questions and exploring the big picture of data science and statistics education.

Table 1: Previous winners of Jackie Dietz JSDSE Best Paper Award.

Title	Citation	Year
Integrating Data Science Ethics Into an Undergraduate Major: A Case Study	Baumer et al. (2022)	2022
Using Team-Based Learning to Teach Data Science	Vance (2021)	2021
Data Visualization: Bringing Data to Life in an Introductory Statistics Course	Hudiburgh and Garbinsky (2020)	2020
The ASCCR Frame for Learning Essential Collaboration Skills	Vance and Smith (2019)	2019
Assessing the Association Between Precourse Metrics of Student Preparation and Student Performance in Introductory Statistics: Results from Early Data on Simulation-Based Inference vs. Nonsimulation-Based Inference	Tintle et al. (2018)	2018
On Enthusing Students About Big Data and Social Media Visualization and Analysis Using R, RStudio, and RMarkdown	Stander and Valle (2017)	2017
Repeated Random Sampling in Year 5	Watson and English (2016)	2016
A Comparison of Student Attitudes, Statistical Reasoning, Performance, and Perceptions for Web-Augmented Traditional, Fully Online, and Flipped Sections of a Statistical Literacy Class	Gundlach et al. (2015)	2015
Investigating Student Understanding of Histograms	Kaplan et al. (2014)	2014
Primarily Statistics: Developing an Introductory Statistics Course for Pre-service Elementary Teachers	Green and Blankenship (2013)	2013
Redesigning a Large Introductory Course to Incorporate the GAISE Guidelines	Woodard and McGowan (2012)	2012
Development and Assessment of a Preliminary Randomization-Based Introductory Statistics Curriculum	Tintle et al. (2011)	2011
Telling Data Stories: Essential Dialogues for Comparative Reasoning	Pfannkuch et al. (2010)	2010

The formal criteria for the award call for papers that:

• improve statistics and data science education at all levels, including elementary, secondary, post-graduate, continuing, and workplace education,

• enhance the exchange of a diversity of interesting and useful information among educators, practitioners, and researchers around the world,

• address an audience who teaches data science and statistics, as well as those interested in research on statistical and probabilistic reasoning,

• share original, novel ideas,

• provide new insights in some area of statistics and data science education,

• are useful: they have the potential to benefit a wide audience of readers,

• include practical ideas data science and statistics teachers can use to improve their teaching,

• deal with important and substantive ideas,

• demonstrate some depth of investigation in a topic,

• are well-written: engage and entice the reader, and/or

• express ideas clearly, efficiently, and accurately.

Papers are selected by an awards committee consisting of six members appointed by the President Elect of the American Statistical Association and presented at the Joint Statistical Meetings. Robin Lock, John Holcomb, Michelle Everson, Erin Blankenship, and Roxy Peck have served as chairs of the award committee.

What other insights can we make of these award winning papers? Figure 1 displays a wordcloud of the words that appear most commonly in the titles, keywords, and abstracts of these papers. The centrality of data, statistics, students, science, and learning jump out at us.

Figure 1: Wordcloud of all title words, keywords, and abstracts from papers that have won the JSDSE Jackie Dietz Award.

Taylor & Francis is now hosting a collection of these winning papers (JSDSE Jackie Dietz Best Paper Award Collection 2023) to make it easy to review these prize-winning papers (see https://www.tandfonline.com/journals/ujse21/collections/best-paper-jackie-dietz-award). I hope that you have a chance to explore them if you haven’t already.

This issue of the Journal of Statistics and Data Science Education features 10 papers on a variety of topics. Tackett (2023) shares three principles to modernize an undergraduate regression analysis course. These principles include (a) providing students with the opportunity to engage with complex and relevant data, (b) building skills and proficiency to undertake reproducible workflows, and (c) developing student communication and teamwork skills. The other papers published in this issue explore a number of important topics: describing the implications of ChatGPT and the advent of large language models, evaluating a “nudge” to improve student attitudes, improving accessibility of teaching materials, bringing Spotify into the classroom, incorporating annotated lesson notes, leveraging large classes, using project-based learning, addressing the challenges of COVID-19, and fostering improvements in written communication.

Will one of these papers be designated the best paper of 2023?

Data Availability Statement

Per journal policies, data and code associated with this editorial can be found at https://doi.org/10.17605/OSF.IO/746ZR.

Disclosure Statement

The authors have no conflicts of interest to declare.