What is it about?
Learning to code is challenging for anyone, but for first-year computer science students with neurodiverse needs like dyslexia, ADHD, or autism, traditional teaching materials can create extra barriers. DiverseClaire is a pilot study that uses generative AI to explore how Python programming materials are experienced by diverse learners. By identifying where those barriers exist, it gives educators actionable feedback to redesign course content and formats to better suit all students. This work is a step toward reimagining inclusive education in CS1 classrooms.
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Why is it important?
This pilot explores perona modelling using generative AI to create a simulated student with characteristics such learning attitudes (such as prior knowledge and prior understanding) to mimic a diverse student in real life. This helps educators receive pro-active feedback to adjust and customise lecture slides that are tailored for learners by exploring experiments in a controlled environment with treatments in course formats and the course content.
Perspectives
Writing this article was a genuine pleasure, not least because it brought together co-authors with whom I was collaborating for the first time. The process naturally drew on an interdisciplinary research focus, one that sits at the intersection of medical science, learning science, and computer science while building empathy at the same time for the diverse learners who navigate these educational spaces every day. Ultimately, this work deepened my own involvement in inclusive education research, and reinforced why it matters.
wendy Wong
University of New South Wales
Read the Original
This page is a summary of: DiverseClaire: Simulating Students to Improve Introductory Programming Course Materials for All CS1 Learners, February 2026, ACM (Association for Computing Machinery),
DOI: 10.1145/3770761.3777340.
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