Author

Donya Rooein

2 papers indexed here

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#artificial intelligence Mar 2026

Can LLMs Model Incorrect Student Reasoning? A Case Study on Distractor Generation

This work examines how large language models reason about misconceptions when generating distractor answers for multiple-choice questions (MCQs) and introduces a taxonomy over reasoning strategies for distractor generation that is grounded in learning-science literature and empirical observation.

Yanick Zengaffinen, Andreas Opedal, Donya Rooein et al. · arXiv.org · 2 citations

#artificial intelligence Preprint Sep 2026

The Role of Implicit and Explicit Demographic Signals in Large Language Model-based Student Assessment

Large Language Models are now common in student assessment, but we know little about how student demographics affect their use. Sometimes, considering student demographics may be necessary -- for example, to improve readability for users with lower educational levels. However, it also risks being a cause of discriminat...

Donya Rooein, Luca Benedetto, Dirk Hovy · 0 citations