Recent tise items

R Statistical Programming in Higher Education: A Scoping Review

Sun, 21 Jun 2026 00:00:00 +0000

This scoping review explores the ways that R has been used in applied research college courses in social sciences and reports on the relevant studies. The included studies, meeting the eligibility criteria, comprise both quantitative and qualitative work in higher education, non-computer science (or related) disciplines, at both the undergraduate and graduate levels. Through a comprehensive and rigorous literature search and screening process, 21 articles are included in the review, covering outcomes on academic performance, course recommendations, and student perceptions of using R.

LLteacher: A Tool for the Integration of Generative AI into Statistics Assignments

Sun, 21 Jun 2026 00:00:00 +0000

As generative AI becomes increasingly embedded in everyday life, the thoughtful and intentional integration of AI-based tools into statistics education has become essential. We address this need with a focus on homework assignments. We propose the use of LLMs as an opportunity for instructors to integrate more pedagogical approaches into homework design, by developing an open-source tool named LLteacher. This LLM-based tool preserves learning processes and it guides students to engage with AI in ways that support their learning, while ensuring alignment with course content and equitable access. We illustrate LLteacher's design and functionality with examples suitable to an undergraduate Statistical Computing course in R, showing how it supports two distinct pedagogical goals: recalling prior knowledge and discovering new concepts. While this is an initial version, LLteacher is an example of one possible pathway for integrating generative AI into statistics courses,...

DistPlotter: An Application that Creates High-Quality Plots of Univariate Distributions

Sat, 20 Jun 2026 00:00:00 +0000

Coverage of distributions, such as normal and t (among others), is prevalent in courses focused on probability and/or statistics irrespective of the discipline. In this article, we discuss existing software that can be used to create plots of univariate distributions and highlight several limitations of these tools. We then introduce a free, web-based, point-and-click application that we developed to address these limitations. The application is designed for both instructor and student use and supports interactive exploration of distributions. Visualizations of distributions can support conceptual understanding, and hands-on interactions with such tools can help students develop deeper insight into distributional behavior. To facilitate classroom implementation, we provide sample activities that can be incorporated at the introductory, intermediate, and advanced levels.

Use of a Reproducible R Shiny Web App to Promote Students' Interest in Coding

Wed, 13 Aug 2025 00:00:00 +0000

Programming or coding plays a crucial role in ensuring reproducibility in data analysis. Among the various programming languages in the field of data science, R stands out as a powerful tool capable of implementing a diverse range of statistical and graphical techniques. Unfortunately, in general education, lots of non-computing majors do not take a typical programming course due to their fear of the command line. A web app Rstats (http://esumath.shinyapps.io/rstats) was developed to promote students’ interest in R programming while learning introductory statistics, irrespective of their coding background. The web app provides a user-friendly point-and-click interface for data analysis, allowing students to explore statistical concepts without having to write code directly. But reproducible R code for the data analysis will be generated and displayed in the web app. Thus students can learn the programming language R during data analysis with the web app. By removing the intimidation...

Automated grading workflows for providing personalized feedback to open-ended data science assignments

Fri, 19 Jul 2024 00:00:00 +0000

Open-ended assignments - such as lab reports and semester-long projects - provide data science and statistics students with opportunities for developing communication, critical thinking, and creativity skills. However, providing grades and qualitative feedback to open-ended assignments can be very time consuming and difficult to do consistently across students. In this paper, we discuss the steps of a typical grading workflow and highlight which steps can be automated in an approach that we define as an automated grading workflow. We illustrate how gradetools, a new R package, implements this approach within RStudio to facilitate efficient and consistent grading while providing individualized feedback. We hope that this work will help the community of data science and statistics educators use gradetools as their grading workflow assistant or develop their own tools for assisting their grading workflow.

Access Statistics Canada’s Open Economic Data for Statistics and Data Science Courses

Tue, 16 Jan 2024 00:00:00 +0000

This article is about the two conflicting goals when teaching statistics or data science courses based on real-world data in a business school environment. We propose to look at structured socio-economic data about the Canadian economy. Canada was ranked 8th in 2017 by Open Data Watch (Government of Canada) for its data accessibility policy. Statistics Canada offers several ways to access data across its over 11,000 data tables. We built an R package to ease access to Statistics Canada's open economic data. With this package, we offer students another option to collect data about the Canadian economy.

NormalityAssessment: An Interactive Classroom Tool for Testing Normality Visually

Sun, 27 Feb 2022 00:00:00 +0000

Many inferential and predictive statistical procedures possess underlying theoretical assumptions that should be met in order for the results of those procedures to be considered reliable. One assumption associated with methods for population means, including linear regression coefficients, is that of normality of a population(s). When assessing normality, two graphical tools that are often utilized are normal quantile-quantile (QQ) plots and histograms. However, while these tools are popular, they still present challenges for many who use them due to the subjectivity oftentimes involved when examining them. In this article, we describe a free, interactive Shiny application, downloadable as an R package, which implements two procedures recently developed for graphical inference with a specific emphasis on assessing normality. The application was created and designed with a focus on statistics education.

Supporting Statistics and Data Science Education with learnr

Thu, 27 Jan 2022 00:00:00 +0000

A modern statistics or data science course aims to equip students with both conceptual and computing skills. This is a challenging task as instructors do not want to increase students’ cognitive load with new tools and technical details and have to balance limited teaching time to help students in achieving the learning outcomes of both content and tool use. Interactive tutorials, built with the R package learnr, can support student learning with progressive reveal of content, interactive code exercises, and quizzes with automatic feedback, and an interface with the potential to reduce technical burdens via deployment as a web application. We describe different use-cases for learnr tutorials including introductory and upper-level statistics and data science courses based on our own teaching experiences. We also discuss the common benefits and lessons learned from implementing and teaching with learnr tutorials.

An educator’s perspective of the tidyverse

Sat, 1 Jan 2022 00:00:00 +0000

Computing makes up a large and growing component of data science and statistics courses. Many of those courses, especially when taught by faculty who are statisticians by training, teach R as the programming language. A number of instructors have opted to build much of their teaching around use of the tidyverse . The tidyverse, in the words of its developers, "is a collection of R packages that share a high-level design philosophy and low-level grammar and data structures, so that learning one package makes it easier to learn the next" (Wickham et al. 2019). The shared principles have led to the widespread adoption of the tidyverse ecosystem. No small part of this usage is because the tidyverse tools have been intentionally designed to ease the learning process and cognitive load for users as they engage with each new piece of the larger ecosystem. Moreover, the functionality offered by the packages within the tidyverse spans the entire data science...

Building Interactive Tutorials for Teaching Psychological Statistics Online with learnr

Wed, 23 Jun 2021 00:00:00 +0000

Faculty are increasingly tasked with online teaching duties. This paper provides a how-to guide to using the learnr package for R. This package allows instructors to create seamless interactive tutorials that can use video, quizzes, and exercises run in R to foster student engagement and learning of statistics. Since the beginning of the Covid-19 pandemic, more faculty than ever are teaching online. learnr tutorials provide a format that allows for greater student engagement with materials by providing opportunities to test knowledge and practice after viewing short videos on topics. I provide concrete instructions for developing learnr tutorials for teaching introductory statistics and provide insights from having applied these technologies for over a year. learnr is a tool that can assist instructors in leveraging valuable teaching opportunities afforded by the technology is a manner that requires only small changes in their more prevalent...

Not just normal: Exploring power with Shiny apps

Fri, 1 Jan 2021 00:00:00 +0000

Statistical power is an important topic taught in most graduate-level and undergraduate-level mathematical statistics courses, but it is often difficult to understand conceptually. Visualizing the power curve, sampling distributions, and how they interact can help students more easily conceptualize power, but the creation of such visuals can be difficult and time-consuming. Interactive web applications provide a way for students to dynamically visualize power, and many web applications for understanding power exist. However, most of these applications assume samples are drawn from a Normal population, concern only the sample mean, and/or were created for introductory classes. In this paper, we describe a web application suitable for undergraduate-level and graduate-level mathematical statistics courses that was created to allow users to visualize the complex relationships underlying power for multiple different statistics and population distributions (available at https://powerapp.shinyapps.io/powerapp/);...

Learning Design and Student Behavior in a Fully Online Course

Fri, 1 Jan 2021 00:00:00 +0000

Student’s behavior in an online course is strongly influenced by the learning design of the course, however there are not many discipline-focused studies investigating how students engage with the Learning Management System and course materials. This paper investigates an asynchronous and fully online introductory statistics course with a collaboration component (Collaborative Keys). This study evaluates how students use these and other resources, if they are being used as intended, and how the use is related to performance. We extend the educational analytics literature and introduce a new measure to quantify how students transition between resources, and we evaluate how these transitions differ by student performance over the course of an entire term. The results suggest that the use of course’s resources is related to student achievement, with higher performing students focusing on video-related resources and showing more consistency and effectiveness in their use of resources...

A Modern Look at Freedman's Box Model

Thu, 18 Jul 2019 00:00:00 +0000

This paper revisits the box model , a metaphor developed by David Freedman to explain sampling distributions and statistical inference to introductory statistics students. The basic idea is to represent all random phenomena in terms of drawing tickets at random from a box. In this way, random sampling from a population can be described in the same way as everyday phenomena, like coin tossing and card dealing. For Freedman, box models were merely a thought experiment; calculations were still done using normal approximations. In this paper, we propose a more modern view that treats the box model as a practical simulation framework for conducting inference. We show how concepts in introductory statistics and probability classes can be motivated by simulating from a box model. To facilitate this simulation-based approach to teaching box models, we developed an online, open-source "box model simulator".

Data Moves

Tue, 1 Jan 2019 00:00:00 +0000

When experienced analysts explore data in a rich environment, they often transform the dataset. For example, they may choose to group or filter data, calculate new variables and summary measures, or reorganize a dataset by changing its structure or merging it with other information. Such actions background, highlight, or even fundamentally change particular features of the data, allowing different types of questions to be explored. We call these actions data moves . In this paper, we argue that paying explicit attention to data moves, as well as their purposes and consequences, is necessary for educators to support student learning about data. This is especially needed in an era when students are expected to develop critical literacy around data and engage in purposeful, self-directed exploration of large and often complex datasets.

The TSHS Resources Portal: A Source of Real and Relevant Data for Teaching Statistics in the Health Sciences

Mon, 1 Jan 2018 00:00:00 +0000

The use of real and relevant data in the statistics classroom is an ideal for many teachers of statistics, as these offer clear benefits for engagement with the kinds of real world applications that students will encounter in the future. Yet, the time required to identify and obtain well-documented data and to prepare classroom teaching materials is often prohibitive. In this paper we review the many benefits of using real and relevant data, and use these to define the characteristics of a well-documented health sciences data resource. We review the barriers to using real and relevant data in teaching. Lastly, we introduce the Teaching of Statistics in the Health Sciences (TSHS) Resources Portal (https://www.causeweb.org/tshs/), a source for well-documented health-related datasets and teaching materials. This dynamic resource provides a means to both obtain and contribute peer-reviewed educational materials. The target audience of the tool is teachers of statistics in health...

Students Making Sense of Multi-level Data

Mon, 1 Jan 2018 00:00:00 +0000

This study builds on research of Konold, Finzer, and Kreetong (2014), which demonstrated that students with little or no training in statistics or data analysis created nested tables or narratives to encode data that had an underlying hierarchical structure. The question remains whether students can understand and work with such structures when they are presented with them. In this study, we examine the reasoning of a seventh-grade student as she used the data-analysis environment CODAP to explore data about the growth of plants. The data were represented in a case table that structured them hierarchically at three levels. We attend in particular to her developing understanding of both the hierarchical case table and related graphs at the level Curcio (1987) refers to as “reading the data.” Critical to her coming to understand the data was 1) coming to see the graphs and table as dynamic rather than static representations, and 2) using dynamic linking among the objects...

Using Twitter to Energize the Introductory Statistics Class

Mon, 1 Jan 2018 00:00:00 +0000

In an effort to increase student learning in the introductory statistics class and simultaneously cater to their social media personas, an innovative pedagogical approach was developed using the social media platform Twitter. Our approach took advantage of over two decades’ worth of research findings regarding the established and successful pedagogical innovations in the teaching of statistics. By deploying a planned multi-tier approach that rests heavily on active learning strategies, we observed favorable outcomes from student learning, including active class participation, enhanced engagement and enjoyment, application of statistics concepts to everyday life, and aspects of improvement in statistical literacy, reasoning and thinking skills. This innovation used a combination of analytical writing, small group discussions, and Socratic discussion to accomplish these results.

Classroom Management with RStudio Server Professional

Mon, 1 Jan 2018 00:00:00 +0000

We introduce a new RStudio addin that facilitates the exchange, grading, and real-time supervision of student work in RStudio. We discuss the results of using the addin in a course in Fall 2016, and conclude with future extensions. Readers who will find the addin of benefit to their own teaching will find installation instructions in the addin's GitHub repository. The source code is released under the LGPL version 3.

Dynamic Data in the Statistics Classroom

Mon, 1 Jan 2018 00:00:00 +0000

The call for using real data in the classroom has long meant using datasets which are culled, cleaned, and wrangled prior to any student working with the observations. However, an important part of teaching statistics should include actually retrieving data from the Internet. Nowadays, there are many different sources of data that are continually updated by the organization hosting the data website. The R tools to download such dynamic data have improved in such a way to make accessing the data possible even in an introductory statistics class. We provide five full analyses on dynamic data as well as an additional nine sources of dynamic data that can be brought into the classroom. The goal of our work is to demonstrate that using dynamic data can have a short learning curve, even for introductory students or faculty unfamiliar with the landscape. The examples provided are unlikely to create expert data scrapers, but they should help motivate students and faculty toward more engaged...

The fivethirtyeight R Package: "Tame Data" Principles for Introductory Statistics and Data Science Courses

Mon, 1 Jan 2018 00:00:00 +0000

As statistics and data science instructors, we often seek to use data in our courses that are rich, real, realistic, and relevant. To this end we created the fivethirtyeight R package of data and code behind the stories and interactives at the data journalism website FiveThirtyEight.com. After a discussion on the conflicting pedagogical goals of "minimizing prerequisites to research" (Cobb 2015) while at the same time presenting students with a realistic view of data as it exists "in the wild," we articulate how a desired balance between these two goals informed the design of the package. The details behind this balance are articulated as our proposed "Tame data principles for introductory statistics and data science courses." Details of the package's construction and example uses are included as well.

Data Visualization on Day One: Bringing Big Ideas into Intro Stats Early and Often

Sun, 1 Jan 2017 00:00:00 +0000

In a world awash with data, the ability to think and compute with data has become an important skill for students in many fields. For that reason, inclusion of some level of statistical computing in many introductory-level courses has grown more common in recent years. Existing literature has documented multiple success stories of teaching statistics with R, bolstered by the capabilities of R Markdown. In this article, we present an in-class data visualization activity intended to expose students to R and R Markdown during the first week of an introductory statistics class. The activity begins with a brief lecture on exploratory data analysis in R. Students are then placed in small groups tasked with exploring a new dataset to produce three visualizations that describe particular insights that are not immediately obvious from the data. Upon completion, students will have produced a series of univariate and multivariate visualizations on a real dataset and practiced describing them.

Comparison of Learning Outcomes for Simulation-based and Traditional Inference Curricula in a Designed Educational Experiment

Fri, 1 Jan 2016 00:00:00 +0000

Conducting inference is a cornerstone upon which the practice of statistics is based. As such, a large portion of most introductory statistics courses is focused on teaching the fundamentals of statistical inference. The goal of this study is to make a formal comparison of learning outcomes under the traditional and simulation-based inference curricula. A randomized experiment was conducted to administer the two curricula to students in an introductory statistics course. Students of the simulation-based curriculum were found to have improved learning outcomes on topics in statistical inference; however, a clear violation of between-student independence due to group administration of curriculum treatments casts considerable doubt on the statistical significance of these results. A simulation study is used to demonstrate the volatility of Type I error rates in educational studies where classroom level covariance structures exist by comparisons are made on the student level.

Student Approaches to Constructing Statistical Models using TinkerPlots ^TM

Fri, 1 Jan 2016 00:00:00 +0000

Statistical literacy skills and technological literacy skills are becoming increasingly entwined as the practice of statistics shifts toward more reliance on the power of technology. More and more, statistics educators suggest reforming introductory college statistics courses to include more emphasis on technology and modeling. But what is the impact of such a focus on student learning? This research examines a small sample of students. The students received a reform-oriented curriculum focused on modeling and simulation using TinkerPlots ^TM technology. The data reported here is from students written work at the end of the term on their final assessment. They had access to TinkerPlots ^TM for the assessment and we share the ways they used the technology to create statistical models. This work provides insights into the ways students’ construct models and how they interpret the models they construct within the context of the original statistical...

Web Application Teaching Tools for Statistics Using R and Shiny

Fri, 1 Jan 2016 00:00:00 +0000

Technology plays a critical role in supporting statistics education, and student comprehension is improved when simulations accompanied by dynamic visualizations are employed. Many web-based teaching tool applets programmed in Java/Javascript are publicly available (e.g., www.rossmanchance.com, www.socr.ucla.edu). These provide a user-friendly interface which is accessible and appealing to students in introductory statistics courses. However, not all statistics educators are fluent in Java/Javascript and may not be able to tailor these apps or develop their own. Shiny, a web application framework for R created by RStudio, facilitates applet development for educators who are familiar with R. We illustrate the utility, convenience, and versatility of Shiny through our collection of 17 freely available apps covering a range of topics and levels (found at www.statistics.calpoly.edu/shiny). Our Shiny source code is publicly available so that anyone may tailor our apps as desired....

R Markdown: Integrating A Reproducible Analysis Tool into Introductory Statistics

Wed, 1 Jan 2014 00:00:00 +0000

Nolan and Temple Lang argue that “the ability to express statistical computations is an es- sential skill.” A key related capacity is the ability to conduct and present data analysis in a way that another person can understand and replicate. The copy-and-paste workflow that is an artifact of antiquated user-interface design makes reproducibility of statistical analysis more difficult, especially as data become increasingly complex and statistical methods become increasingly sophisticated. R Markdown is a new technology that makes creating fully-reproducible statistical analysis simple and painless. It provides a solution suitable not only for cutting edge research, but also for use in an introductory statistics course. We present experiential and statistical evidence that R Markdown can be used effectively in introductory statistics courses, and discuss its role in the rapidly-changing world of statistical computation.

Using Lexical Analysis Software to Assess Student Writing in Statistics

Wed, 1 Jan 2014 00:00:00 +0000

Meaningful assessments that reveal student thinking are vital to the success of addressing the GAISE recommendation: use assessments to improve and evaluate student learning. Constructed-response questions, also known as open-response or short answer questions, in which students must write an answer in their own words, have been shown to better reveal students' understanding than multiple-choice questions, but they are much more time consuming to grade for classroom use or code for research purposes. This paper describes and illustrates the use of two different software packages to analyze open-response data collected from undergraduate students’ writing. The analysis and results produced by the two packages are contrasted with each other and with the results obtained from hand coding of the same data sets. The article concludes with a discussion of the advantages and limitations of the analysis options for statistics education research.

Introduction to Special Edition: The Future of the Textbook

Mon, 2 Dec 2013 00:00:00 +0000

A brief overview of the papers and commentaries in this special edition.

Comment: The Future of the Textbook

Tue, 22 Oct 2013 00:00:00 +0000

Commentary on The Future of the Textbook.

Textbooks 2.0

Tue, 22 Oct 2013 00:00:00 +0000

Technology allows us to offer great improvements on the traditional paper-bound textbook. I describe reasons for why electronic textbooks will become the norm in the near future.

ZIG: Response

Tue, 22 Oct 2013 00:00:00 +0000

Response to Commentaries.

West: Response

Tue, 22 Oct 2013 00:00:00 +0000

Response to Commentaries.

OpenIntro Statistics: an Open-source Textbook

Tue, 22 Oct 2013 00:00:00 +0000

The traditional textbook is a familiar and useful tool that has served well for centuries. Here, we discuss OpenIntro Statistics, a new textbook that seeks to retain the long-standing points of excellence among traditional textbooks, while overcoming what is potentially the most important traditional limitation: exclusivity. OpenIntro Statistics is a completely open-source textbook, which can be downloaded for free and edited by anybody. Its content meets the highest established standards, and is is written, edited, and reviewed by faculty from leading universities. In this paper, we provide support for the assertion that OpenIntro Statistics retains as many of the advantages of a traditional textbook as possible, while empowering the largest possible audience to owna nd edit introductory content in statistics. We also discuss how the open-source textbook model differs from other technologically...

Response: C-RDB

Tue, 22 Oct 2013 00:00:00 +0000

Response to Commentaries.

Comment: Let's All Write and Teach with e-Books!

Tue, 22 Oct 2013 00:00:00 +0000

Commentary on The Future of the Textbook.

Comment: Focusing on Learning

Tue, 22 Oct 2013 00:00:00 +0000

Commentary on The Future of the Textbook.

Comment: Technology and the Future of Statistics Education

Tue, 22 Oct 2013 00:00:00 +0000

Commentary on The Future of the Textbook.

The Course as Textbook: A Symbiotic Relationship in the Introductory Statistics Class

Tue, 22 Oct 2013 00:00:00 +0000

In the past several decades, the statistics textbook has evolved to include a variety of ancillary materials intended to supplement students’ learning and assist the teacher (e.g., workbooks, study guides, audio program, test banks, PowerPoint slides, links to applets and websites, etc.). Given the capabilities of modern technology and the need for change in content and pedagogy in the introductory statistics course, a new vision of a textbook is offered, one that exploits new technology, provides modern content, and is a more integral part of the course. Rather than serving as a supplement to a course, the modern textbook needs to embody the course. An example of such a text in the context of a unique, new introductory statistics course is provided.

Preface to the Special Edition

Sat, 3 Aug 2013 00:00:00 +0000

Introductory remarks

Faculty Attitude towards Technology-Assisted Instruction for Introductory Statistics in the Context of Educational Reform