Work

Reflections on the Future of Statistics Education in a Technological Era

Year: 2026

Type: article

Abstract: ABSTRACT Keeping pace with rapidly evolving technology is a key challenge in teaching statistics. To equip students with essential skills for the modern workplace, educators must integrate relevant technologies into the statistical curriculum where possible. University‐level statistics education has experienced substantial technological change, particularly in the tools and practices that underpin teaching and learning. Statistical programming has become central to many courses, with R widely used and Python increasingly incorporated into statistics and data analytics programs. Additionally, coding practices, database management, and machine learning now feature within some statistics curricula. Looking ahead, we anticipate a growing emphasis on artificial intelligence (AI), particularly the pedagogical implications of generative AI tools such as ChatGPT. In this article, we discuss these technological developments and present our perspectives on their integration into contemporary statistics education.

Source: Teaching Statistics

DOI: 10.1002/test.70047

Authors: Craig Alexander, Jennifer Gaskell, Vinny Davies

Institution: University of Glasgow

Language: English

Topic: Statistics Education and Methodologies

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

SDG: Quality education

Open Access status: hybrid

Estimated APC paid: $2,900