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Discussion of “Addressing the Challenges of AI-Generated Assignment Submissions in Education: Insights and Strategies”
Volume 24, Issue 1 (2026): Special Issue: Statistical aspects of Trustworthy Machine Learning, pp. 276–281
Pub. online: 11 February 2026      Type: Education In Data Science      Open accessOpen Access
Published
11 February 2026

References

 
Wang S, Xu L, Liu J, Zhai Y (2025). Addressing the Challenges of AI-Generated Assignment Submissions in Education: Insights and Strategies. Journal of Data Science, 24(1): 1–7. https://doi.org/10.6339/25-JDS1208
 
Wickham H, Cheng J, Jacobs A, Aden-Buie G, Schloerke B (2025). ellmer: Chat with Large Language Models. R package. https://CRAN.R-project.org/package=ellmer. https://doi.org/10.32614/CRAN.package.ellmer
 
Nicosia A (2025). contextR: Contextual statistics with large language models. R package, version v0.1.0. Zenodo. https://doi.org/10.5281/zenodo.18010065

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Copyright
2026 The Author(s). Published by the School of Statistics and the Center for Applied Statistics, Renmin University of China.
Open access article under the CC BY license.

Keywords
AI-assisted assessment contextualized assignments large language models R programming reproducible workflows statistics education

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