Teaching Statistics
The Teaching Statistics group engages in a combination of research, pedagogy,
and classroom training. Members are interested in updating and modernizing
curriculum and assessment, pedagogical philosophy and development, best
classroom practices, student engagement, and outreach to a diverse community.
Current work includes:
 Redesigning the General Education introductory statistics
course to include modern Data Science concepts, active learning,
and adaptive material
 Thinkaloud interview studies to design more effective
assessment questions for identifying introductory level
misconceptions, and to understand how students learn statistics
 Building interactive tools for teaching statistics and for
students to analyze data, including
the Integrated Statistics
Learning Environment
 Teaching Statistics mini: pedagogy training and discussion
course for PhD students; once a semester covering rotating topics
 Summer Teaching Program for our graduate students –
training and support for students working as instructors and
teaching assistants over the summer
Faculty, students, and staff are welcome to join and work on projects when available; the below includes current, regular members (faculty, students).
 Rebecca
Nugent, Associate Dept Head and Director of Undergraduate
Studies, Statistics & Data Science
 Gordon
Weinberg, Instructor, Statistics & Data Science
 Alex Reinhart,
Assistant Teaching Professor, Statistics & Data Science
 Jerzy Wieczorek,
Assistant Professor, Mathematics and Statistics, Colby College
 Peter
Freeman, Assistant Teaching Professor, Statistics & Data
Science
 Philipp
Burckhardt, Postdoctoral Researcher, Statistics & Data Science
 Peter Elliott, PhD graduate, Statistics & Data Science
 Ciaran Evans, PhD student, Statistics & Data Science
 Amanda Luby,
Assistant Professor, Swarthmore College
 Mikaela Meyer, PhD student, Statistics & Data Science
 Josue Orellana, PhD student, Machine Learning and Center for the Neural Basis of Cognition
 Ron
Yurko, PhD student, Statistics & Data Science
Past members:
 Howard
Seltman, formerly Director of Master's in Statistical Practice
program, Senior Research Scientist, Statistics & Data Science
 Justin Hyun, PhD student, Statistics & Data Science
 Kevin Lin, PhD student, Statistics & Data Science
 Christopher Peter Makris, formerly Executive Director, Master's
in Statistical Practice program, Statistics & Data Science
Below is a partial list of current research/pedagogy projects:
 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 thinkaloud 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 thinkaloud 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.
 CMU
PreCollege: Data Science Experience

A program of activities and interactive data science
experiences designed for high school students, agnostic of
background or academic interests
Collaborators:
Current:
 Using ThinkAloud 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:
 Supercharging the Data Science Classroom: Giving students
agency and reach with new, interactive technologies
NSF:
DUE/IUSE, $2,000,000, five years
PI Nugent with C Genovese
(PI), P Burckhardt (Investigator)
 The
Carnegie Mellon Data Science Experience: Why take a course
in Data Science when you can Experience it?. SIGKDD Impact
program, $50K, 2018.
PI: Nugent, Key Personnel:
Weinberg, Burckhardt. Project
Publications/Presentations:
 A Reinhart, C Evans, A Luby, J Orellana, M Meyer, J Wieczorek,
P Elliott, P Burckhardt & R Nugent. Thinkaloud interviews:
A tool for exploring student statistical reasoning. Submitted.
Preprint.
 P Burckhardt, P W Elliott, C Evans, A Luby, M Meyer, J Orellana,
J Wieczorek, R Nugent & A Reinhart. Writing practical pre and
posttests for concepts in introductory courses, CMU Eberly
Teaching and Learning Summit, November 2019.
Poster.
 M Meyer, J Orellana, A Reinhart. Using ThinkAloud
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
RealTime Clustering of Student Responses into an ELearning
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 thinkaloud 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 elearning platform. Joint Statistical
Meetings, Vancouver, JulyAugust 2018.
 Burckhardt P, Chouldechova A, Nugent R. TeachIT: Turning the
Classroom into a Research Laboratory via Interactive ELearning
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 thinkaloud
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 ELearning 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