Date
Publisher
arXiv
Large Language Models (LLMs) have shifted in just a few years from novelty to
ubiquity, raising fundamental questions for data science education. Tasks once
used to teach coding, writing, and problem-solving can now be completed by
LLMs, forcing educators to reconsider both pedagogy and assessment. To
understand how instructors are adapting, we conducted semi-structured
interviews with 42 instructors from 33 institutions in 10 countries in June and
July 2025. Our qualitative analysis reveals a pragmatic mix of optimism and
concern. Many respondents view LLMs as inevitable classroom tools -- comparable
to calculators or Wikipedia -- while others worry about de-skilling, misplaced
confidence, and uneven integration across institutions. Around 58 per cent have
already introduced demonstrations, guided activities, or make extensive use of
LLMs in their courses, though most expect change to remain slow and uneven.
That said, 31 per cent have not used LLMs to teach students and do not plan to.
We highlight some instructional innovations, including AI-aware assessments,
reflective use of LLMs as tutors, and course-specific chatbots. By sharing
these perspectives, we aim to help data science educators adapt collectively to
ensure curricula keep pace with technological change.
Study at a glance
- Question: How are data science instructors adapting their teaching, assessment, and views to large language models?
- Setting and data: 42 data science and statistics instructors across 33 institutions in 10 countries, June to July 2025.
- Method: Semi-structured interviews with qualitative coding.
Why it matters
Large language models can complete coding, writing, and problem-solving tasks, leaving educators uncertain about how to adapt their pedagogy, assessments, and curricula to keep pace with rapid technological change.
Key findings
- Most instructors held pragmatic views toward language models, but 31 percent had not used them to teach and had no plans to do so.
- Over half of respondents shifted toward in-class assessments, while 47 percent anticipated incorporating AI-integrated tasks into future coursework.
- Eighty-one percent of instructors who used models in teaching utilized ChatGPT, and 38 percent used Microsoft GitHub Copilot.
Summary drafted with AI from the full paper and may contain errors. See the full paper for details.
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