Document Type

Working Paper

Publication Date

2026

Abstract

Teaching statistical reasoning to quantitatively unprepared liberal arts undergraduates is a long-standing challenge for instructors. Due to recent developments, demand for data-literate liberal arts graduates has taken a sharp upturn. As a result, a conundrum has developed: how to produce liberal arts graduates comfortable with both holistic perspectives and data analysis, without an unwieldy expansion of the curriculum. As a solution, this paper proposes reframing statistical problems as computational thinking tasks and using simulation programs generated by AI platforms (e.g., ChatGPT) as an alternative approach to presenting quantitative material. I demonstrate that this approach can be adapted to any programming skill level (including none) and illustrate its efficacy through several short case studies. This approach is shown to be quite flexible. With suitable modifications, it can be adapted for any college level. More generally, it shows how AI can be integrated into the teaching of statistical reasoning to allow a much deeper treatment of material that was possible previously, to a broader segment of students. Rather than see AI as a threat, it shows how AI can be integrated into pedagogy and help introduce techniques that were believed to be too complicated, at least for lower division liberal arts students.

Original Publication Citation

Eusufzai, Zaki. “Teaching Statistical Reasoning Using AI and Computational Storytelling in a Liberal Arts Classroom.” https://doi.org/10.64650/econ.2026.00473.

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