About

Kelly Findley is a Teaching Associate Professor of Statistics at the University of Illinois Urbana-Champaign. She specializes in creating curricular materials that are scalable to large classes, conceptually driven toward core statistical ideas, and embedded in authentic examples to promote statistical inquiry and meaningful application. Much of her work at Illinois has focused on redesigning the Introduction to Biostatistics course, an accelerated introductory course with applications relevant for students pursuing careers in the medical field. Her course notes and lab assignments are shared openly and may be used and adapted freely, reflecting her commitment to accessible and effective teaching resources. As a statistics education researcher, Kelly Findley primarily conducts qualitative research. She collaborates with colleagues such as Nicola Justice, Florian Berens, and Chris Kinson to identify students' perspectives of statistics and explore how these perspectives evolve over time. Her research moves beyond deficit framings to identify the conceptual resources students express, with particular interest in student thinking around causality and generalizability in statistical design, as well as students' understanding of sampling distributions for the mean. This focus highlights her dedication to deepening understanding of student learning processes in statistics education. In addition to her teaching and research, Findley plays a significant role in graduate teaching assistant training and professional development. Alongside colleague Julie Deeke, she has helped establish dedicated training for first-year PhD students that emphasizes cohort unity, technology onboarding, and pedagogical discussions related to fundamental statistical topics. She has also contributed to the creation of a TA Training committee aimed at fostering a supportive community within the department, enhancing relationships between TAs and supervisors, and recognizing outstanding TAs for leadership, service, and pedagogical innovation.

Research topics

• Social Science
• Sociology
• Mathematics education
• Psychology
• Pedagogy
• Statistics
• Mathematics
• Epistemology
• Social psychology

Selected publications

• Why Come to Class? Post-Pandemic Perspectives from Students in an Introductory Statistics Course

  Journal of Statistics and Data Science Education · 2025-06-18

  articleOpen access1st authorCorresponding

  As more university instructors continue making recordings of in-person classes available, educators should carefully consider how modality options may affect learners. While most existing studies that compare learning modalities rely on survey studies and broader correlations, we conducted an interventional qualitative study to glean more theory about how students experience different modalities. Nine students enrolled in a large introduction to biostatistics course volunteered to participate. For two different 50-min class periods, participating students were randomly assigned to do one of the following: attend class in person, watch the class recording, or watch prerecorded videos made by the instructor. Interviews revealed that students’ ability to self-regulate their learning was a key indicator of whether they could learn richly and successfully with video-based modalities. In-person class attendance had value for several, but typically as a vehicle for maintaining discipline and good habits rather than as an opportunity to learn more richly. We theorize that developing students’ ability to plan, monitor, and evaluate their own learning processes plays a crucial role in their success across multiple modalities. Furthermore, supporting students to notice and focus on conceptual ideas in statistics may better support reflective learning in courses where class recordings are available.

  PublisherDOI

• Why Swipe Right? Career Interests and Aspirations of Incoming Statistics Majors

  Journal of Statistics and Data Science Education · 2024-11-14 · 1 citations

  articleOpen access1st authorCorresponding

  Undergraduate statistics programs can help students hone a wide range of quantitative, computational, and communicative skills as they prepare for a fruitful career. In this article, we explore what motivates students to choose a major in statistics and to what extent incoming statistics majors recognize these wider skills as part of doing statistics. To build theories regarding what motivates students toward statistics, we interviewed nine first-year statistics majors at a large public university and analyzed their responses using a grounded theory approach. Each student shared their views of “who” statistics is to them, what kind of career they aspired to, and what prior experiences oriented them toward studying statistics. A strong, cross-cutting theme that emerged was that of balance. For example, statistics appeared as a safe and lucrative career choice that catered to their mathematical strengths, but it could also be an exciting career choice that stoked their imaginations. We also found that students had different perspectives and expectations about the role of mathematics and coding that may impact their experience in the major. Implications for introductory course curricula, the importance of projects, and outreach programs are discussed.

  PublisherOA PDFDOI

• The Illusion of Randomness: Evaluating Student Sampling Performance

  CHANCE · 2024-07-02

  article
  PublisherDOI

• Disciplinary appropriation at the beginning of a statistics major

  2024-01-01

  articleOpen access

  Demand for skillsets in data analysis and computing has been rising quickly in recent years, but academic programs that prepare students for these positions still struggle with retention issues. In addition, statistics graduates are not representative of all parts of society, with women and people of color, among others, being underrepresented. We therefore look at those who enter a statistics major to understand how they navigate their program and find belonging. For the analysis of incoming undergraduates, we are guided by Levrini et al. (2015), who propose to look at identity development through the lens of disciplinary appropriation. Using the example of three students, we show that the operationalization developed by Levrini et al. (2015) is suitable for examining disciplinary appropriation at the beginning of studies. We present the operationalization and discuss how we made it usable in a domain- and target group-specific way.

  PublisherOA PDFDOI

• How Students’ Statistics Beliefs Influence Their Attitudes: A Quantitative and a Qualitative Approach

  Advances in mathematics education · 2023-01-01

  book-chapterOpen access
  PublisherOA PDFDOI

• RESOURCES AND TENSIONS IN STUDENT THINKING ABOUT STATISTICAL DESIGN

  Statistics Education Research Journal · 2023-12-13

  articleOpen access1st authorCorresponding

  Reform efforts in statistics education emphasize the need for students to develop statistical thinking. Critical to this goal is a solid understanding of design in the process of collecting data, evaluating evidence, and drawing conclusions. We collected survey responses from over 700 college students at the start of an introductory statistics course to determine how they evaluated the validity of different designs. Despite preferring different designs, students offered a variety of productive arguments supporting their choices. For example, some students viewed intervention as a weakness that disrupted the ability to generalize results, whereas others viewed intervention as critical for identifying causality. Our results highlight that instruction should frame design as the balancing of different priorities: namely causality, generalizability, and power.

  PublisherOA PDFDOI

• Lois Lane, Superman, and Iron Man: How Perspectives of Statistics Relate to Students’ Identities and Career Pursuits

  Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics · 2022 · 1 citations

  1st authorCorresponding
  • Sociology
  • Social Science
  • Mathematics education

  Incoming university students’ unique experiences with and perspectives of statistics may shape their learning trajectories, recruitment, and retention in the discipline. We completed qualitative case studies with three first-year statistics majors. Each student shared their views of “who” statistics is to them, how they imagined a career in statistics, and recalled their prior experiences and motivations for studying statistics. We contrast the students and remark on how their varying experiences relate to perspectives on their chosen field. Results varied in the perceived nature and content of statistics, and experiences engaging with rich data sets were associated with more substantive perspectives of the discipline. Future research will use follow-up interviews to examine the trajectories of students’ changing perspectives, participation, disciplinary identities, and interests.

  PublisherDOI

• NAVIGATING A DISCIPLINARY CHASM: THE STATISTICAL PERSPECTIVES OF GRADUATE TEACHING ASSISTANTS

  Statistics Education Research Journal · 2022 · 3 citations

  1st authorCorresponding
  • Sociology
  • Mathematics education
  • Social Science

  Graduate Teaching Assistants (GTAs) carry a substantial instructional role in introductory courses for many mathematics and statistics departments. As a result, many GTAs have first-hand influence on the initial statistical impressions of students from a range of disciplines. But as simultaneous learners of the discipline themselves, GTAs in statistics are still forming their conceptions of statistics and statistics instruction. Using multiple case study design, I conducted a longitudinal study with four, first-year statistics GTAs aimed at capturing their experiences and notions related to statistics. This paper highlights several important disciplinary perspectives and tensions expressed by the GTAs. In addition to examining their disciplinary notions, I also discuss noteworthy connections between the participants’ statistical perspectives and their pedagogical views for introductory statistics. Findings reveal that the participants struggled to reconcile how authentic statistical practice could be translated into the introductory curriculum. Implications for GTA training are discussed.

  PublisherOA PDFDOI

• Productive seeds in preservice teachers’ reasoning about fraction comparisons

  Mathematics Education Across Cultures: Proceedings of the 42nd Meeting of the North American Chapter of the International Group for the Psychology of Mathematics Education · 2020-12-23 · 1 citations

  article
  PublisherDOI

• What's in a name? Leveraging students' informal vocabulary in probability

  Teaching Statistics · 2020-11-24

  article1st authorCorresponding

  Abstract Providing opportunities for students to express ideas in their own words is key to promoting authentic disciplinary engagement and robust conceptual understanding. In this article, we discuss our experiences and observations related to students' informal vocabulary in the context of a middle school probability unit. We noticed that students' informal naming provided critical glimpses into their conceptions and tensions about sample spaces. The use of student‐suggested names also served to compress previous discussions and facilitate higher‐level conceptual thinking in later conversations. We share our experiences with informal naming in one curricular context and conclude with perceived benefits to allowing space for student naming as a broader instructional practice.

  PublisherDOI

Frequent coauthors

• Ian Whitacre

  Florida State University

  8 shared

• Karina K. R. Hensberry

  University of South Florida St. Petersburg

  5 shared

• Şebnem Atabaş

  University of Saint Joseph

  4 shared

• Jennifer Schellinger

  Florida State University

  4 shared

• Florian Berens

  University of Tübingen

  3 shared

• Nicola Justice

  2 shared

• Brein Mosely

  University of Illinois Urbana-Champaign

  1 shared

• Zhaolin Li

  1 shared

Education

• PhD in Mathematics Education, Curriculum & Instruction

  Florida State University

  2019

• M.S. in Statistics, Statistics

  Florida State University

  2015