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Generative AI in Statistics

Generative AI can both help and hinder instructors and students of statistics. This collection presents a framework for considering how we might use AI in classroom activities, a call for healthy skepticism, and examples of using AI to start and iterate on a programming task.

Instructional Practices
Updated December 2024
Rich Ross headshot
Rich Ross
Assistant Professor
Statistics
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01

A Framework for Considering How We Might Use AI in Classroom Activities

Rich Ross

I share a model I created of four main types of learning activities that instructors and students may use in the classroom, and how AI can help and hinder instructors and students who engage in each type of activity.

Headshot of Rich Ross
Rich Ross
Think about how your learning activities fit into the four categories in this framework. After doing so, consider how to incorporate AI in those activities (or not). This framework strives for balance, not favoring or despising the use of AI in any learning activity.  
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Countless educators have enumerated many different types of learning activities and other classroom activities. Many of these lists can be quite instructive, but I’d like to focus on four main types of learning activities that instructors and students may use in the classroom. These four types of activities are: acquisition, synthesis, genesis, and iteration.

As I mention each, I’ll try to highlight how AI can both help and hinder instructors and learners who engage in the given type of activity. In creating this resource, I’ve tried to take a balanced view towards generative AI: I don’t view the technology as solely positive or solely negative; hopefully you find the resources useful as you consider the use of these tools in your own courses.

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02

Using Generative AI with Healthy Skepticism

Rich Ross

I share example questions where ChatGPT's answers are great (and where they aren't), and discuss how we can share similar examples to help students understand the risks of leaning too much on AI tools.

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Rich Ross

Some instructors warn students that generative AI can be a dangerous crutch. After reading this post, I hope that you can share examples with your students that illustrate both the power of generative AI and its limitations, which helps students focus on learning content.

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03

A New Era of Learning: Considerations for ChatGPT as a Tool to Enhance Statistics and Data Science Education

Journal of Statistics and Data Science Education

In this article, Amanda R. Ellis and Emily Slade (University of Kentucky) explore how we can leverage ChatGPT in course materials for statistics and data science education, including one way to have students approach a programming task in statistics.

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Rich Ross

I find that the authors' suggestions are a wonderful starting point, and instructors can tailor this prototype to fit the needs of their students and learning objectives.

It inspired me to do the following: One class I teach focuses on data visualization. Students need to take information from a file like a spreadsheet and use software to create powerful visuals. One thing we can do is provide an initial prompt such as “using the programming language R, create a histogram of the carat variable from the well-known diamonds dataset.” ChatGPT can create some nice code for such a task, which students can then copy and paste, then modify. Requesting that students start with the AI-powered solution helps to showcase how AI can support and reinforce the acquisition of content knowledge. They see the answer to the questions:

  • What does the code look like to create a histogram?

  • How do I access a particular dataset in R?

It also helps students to consider synthesis, by providing instructors a tool for synthesis.

  • Now that you have working histogram code, make a histogram for a different dataset (that ChatGPT does not know).

  • Make your histogram more complex in a meaningful way. (As an instructor, you could even provide some examples of the types of complexity students might add.)

After this activity is finished, you can demonstrate to students that AI certainly helped to start the process, but there were a few adjustments that helped provide a complete solution to the problem at hand.

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ChatGPT is one of many generative artificial intelligence (AI) tools that has emerged recently, creating controversy in the education community with concerns about its potential to be used for plagiarism and to undermine students’ ability to think independently. Recent publications have criticized the use of ChatGPT and other generative AI tools in the classroom, with little focus on the potential benefits. This article focuses on the potential of ChatGPT as an educational tool for statistics and data science. It encourages readers to consider the history of trepidation surrounding introducing new technology in the classroom, such as the calculator. We explore the possibility of leveraging ChatGPT’s capabilities in statistics and data science education, providing examples of how ChatGPT can aid in developing course materials and suggestions for how educators can prompt students to interact with ChatGPT responsibly. As educators, we can guide the use of generative AI tools in statistics and data science classrooms so that students and educators can leverage the benefits of this technology.

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04

Using AI to Iterate on a Programming Task

Rich Ross

I share an activity students can do in class to help them learn about writing effective prompts and verifying the results of AI-powered solutions.

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Rich Ross

In my experience, this is a great activity to do in class. I have found that activities such as this one help students learn how to write effective prompts, how to verify the results of AI-powered solutions, and the potential to use ChatGPT as part of an iterative process in creating great work.

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