Faculty, students, and staff are welcome to join and work on projects when available; the below includes current, regular members (faculty, students).

• Alex Reinhart, Assistant Teaching Professor, Statistics & Data Science
• Rebecca Nugent, Department Head, Statistics & Data Science
• Gordon Weinberg, Instructor, Statistics & Data Science
• David Brown, Associate Teaching Professor and Associate Director of First-Year Writing, English
• Michael Laudenbach, PhD student, English
• Ben Markey, PhD student, English
• Jerzy Wieczorek, Assistant Professor, Mathematics and Statistics, Colby College
• Peter Freeman, Associate Teaching Professor and Director of the Undergraduate Program, Statistics & Data Science
• Philipp Burckhardt, Postdoctoral Researcher, Statistics & Data Science
• Ciaran Evans, Assistant Professor, Department of Mathematics and Statistics, Wake Forest University
• Amanda Luby, Assistant Professor of Statistics, Swarthmore College
• Ron Yurko, Assistant Teaching Professor, Statistics & Data Science

Past members:

• Peter Elliott, PhD graduate, Statistics & Data Science
• Josue Orellana, PhD graduate, Machine Learning and Center for the Neural Basis of Cognition
• Mikaela Meyer, PhD graduate, Statistics & Data Science
• Howard Seltman, formerly Director of Master's in Statistical Practice program, Senior Research Scientist, Statistics & Data Science
• Justin Hyun, PhD graduate, Statistics & Data Science
• Kevin Lin, PhD graduate, Statistics & Data Science
• Christopher Peter Makris, formerly Executive Director, Master's in Statistical Practice program, Statistics & Data Science

Developing Expert Statistical Writing Skills in Novice Students

Studying the form and content of student writing in statistics courses, and how that writing differs from expert statistical writing, to develop new tools and techniques for teaching students to write statistical reports.

Adaptive/Active Learning for Early Statistics/Data Science

Characterizing students' interests, choices of major, and performance based on data analysis pipeline; how can we build adaptive early statistics and data science curricula for a diverse population that identify their best and likely different individual strategies?

Building Assessments for Introductory Statistics

Using think-aloud interviews to determine common misconceptions in early statistics and data science courses and subsequently build better assessment questions.

How Students Learn to Analyze Data

Using think-aloud interviews, classroom experiments, and interactive data analysis platforms to study how students learn to analyze data, the ways their analysis choices affect their results, and how we can best teach fundamental analysis skills.

Collaborators:

• Eberly Center for Teaching Excellence and Educational Innovation
• Women in Statistics, CMU Statistics & Data Science

Awarded:

• Dietrich College Research Seed Grant, $10,000. Supporting the pilot of Docuscope Write & Audit in Statistics & Data Science courses.
• Using Think-Aloud Interviews and Cognitive Task Analysis to Identify Misconceptions in Undergraduate Statistics Education. Carnegie Mellon ProSEED/Crosswalk program, $1000, Spring 2019.
  PIs: Josue Orellana, Mikaela Meyer.
• Women in Statistics at CMU: Fostering Collaboration through Formal Mentorship.
  Carnegie Mellon ProSEED/Crosswalk Program, $1700, Spring/Summer 2018
  PIs: Frisoli, Gallagher, Luby (alphabetical order).
  Grant submitted by Women in Statistics group.

Submitted/Under Review:

• Supporting Student Writing and Reasoning in Data Science Using a Scalable Automated Feedback System. NSF IUSE, submitted summer 2023. PI David Brown with co-PIs Suguru Ishizaki, Alex Reinhart, and Gordon Weinberg.

Publications/Presentations:

• M Laudenbach, D W Brown, Z Guo, S Ishizaki, A Reinhart, & G Weinberg. Visualizing formative feedback in statistics writing: A case study of student motivation using Docuscope Write & Audit. Preprint.
• A Reinhart, C Evans, A Luby, J Orellana, M Meyer, J Wieczorek, P Elliott, P Burckhardt & R Nugent. Think-aloud interviews: A tool for exploring student statistical reasoning. Journal of Statistics and Data Science Education 30 (2), pp. 100-113, July 2022.
• C Evans, A Reinhart, P Burckhardt, R Nugent, & G Weinberg. Exploring how students reason about correlation and causation. eCOTS 2020. Poster
• M Meyer, J Orellana, A Reinhart. Using Cognitive Task Analysis to Uncover Misconceptions in Statistical Inference Courses. eCOTS 2020. Poster
• P Burckhardt, P W Elliott, C Evans, A Luby, M Meyer, J Orellana, J Wieczorek, R Nugent & A Reinhart. Writing practical pre- and post-tests for concepts in introductory courses, CMU Eberly Teaching and Learning Summit, November 2019. Poster.
• M Meyer, J Orellana, A Reinhart. Using Think-Aloud Interviews and Cognitive Task Analysis to Identify Misconceptions in Undergraduate Statistics Education, Joint Statistical Meetings, July 2019. Poster
• P Burckhardt, C Genovese, R Nugent, R Yurko. Incorporating Real-Time Clustering of Student Responses into an E-Learning System, Joint Statistical Meetings, July 2019. Poster
• A Reinhart, P Burckhardt, P W Elliott, C Evans, A Luby, M Meyer, J Orellana, R Yurko, G Weinberg, J Wieczorek & R Nugent. Using think-aloud interviews to assess student understanding of statistics concepts. Breakout session. US Conference on Teaching Statistics (USCOTS), May 2019. Abstract, slides, handout
• R Nugent, R Yurko, P Burckhardt & F Kovacs. "Many Students, One Dataset": Using ISLE to Teach Reproducibility and the Impact of Data Analysis Decisions on Conclusions. Breakout session. US Conference on Teaching Statistics (USCOTS), May 2019. Abstract
• P Burckhardt, P W Elliott, C Evans, S Hyun, K Lin, A Luby, C P Makris, M Meyer, J Orellana, R Yurko, G Weinberg, J Wieczorek, R Nugent & A Reinhart. Developing an assessment for concepts in introductory statistics and data science. CMU Eberly Teaching and Learning Summit, October 2018. Poster. (People's Choice Award winner)
• Burckhardt P, Nugent R, Genovese C. How students make sense of data on an e-learning platform. Joint Statistical Meetings, Vancouver, July-August 2018.
• Burckhardt P, Chouldechova A, Nugent R. TeachIT: Turning the Classroom into a Research Laboratory via Interactive E-Learning Tools. Invited paper. Proceedings of the Tenth International Conference on Teaching Statistics (ICOTS10, July, 2018), Kyoto, Japan. Paper
• Yurko R, Nugent R, P Burckhardt. Detecting Data Analysis Patterns in Text and Graphs to Characterize Student Learning in an Introductory Statistics & Data Science Course, Classification Society Annual Meeting, June 2018.
• Yurko R, Nugent R. Using text analysis to characterize student learning in an introductory statistics & data science course, Electronic Conference On Teaching Statistics (eCOTS), May 2018. Video poster
• S Hyun, P Burckhardt, P Elliott, C Evans, K Lin, A Luby, C P Makris, J Orellana, A Reinhart, J Wieczorek, R Yurko, G Weinberg & R Nugent. Identifying misconceptions of introductory data science using a think-aloud protocol, Electronic Conference on Teaching Statistics (eCOTS), May 2018. Video poster
• Burckhardt P, Nugent R, Genovese C. Learning Data Science with the Help of a Data Exploration Tool. Electronic Conference On Teaching Statistics (eCOTS), May 2018. Video poster
• Burckhardt P, Chouldechova A, Nugent R. The ISLE Experience: Enhancing Classroom Instruction with Interactive E-Learning Tools, CMU Eberly Teaching and Learning Summit, October 2017.
• Burckhardt P, Elliott P, Hyun S, Lin K, Luby A, Makris CP, Orellana J, Reinhart A, Wieczorek J, Weinberg G, Nugent R. Assessment of Student Learning and Misconception Identification in Intro Statistics, CMU Eberly Teaching and Learning Summit, October 2017. Poster