Abstract This pilot study aimed to explore how a specific group of neurodivergent students in the 4th and 5th grades of elementary school represent scientists through drawing. To this end, the Draw-a-Scientist Test (DAST) was administered to 7 neurodivergent children with a diagnosed Autism Spectrum Disorder (ASD) who participated in the Young Scientists Project. The analysis of the drawing data was conducted using a multimodal vision-language model (ChatGPT, GPT-4o version) with the prompt “Evaluate the drawings using the Draw-a-Scientist Test checklist”, followed by independent researcher review to ensure consistency and contextual interpretation. Within this small pilot cohort ( n = 7), the drawings predominantly contained visual features commonly associated with traditional representations of scientists, featuring laboratory instruments, a predominantly laboratory environment, and male figures in 6 of the 7 drawings. Representations of scientists in diverse real-world contexts, or utilizing digital technology, books, or chemical formulas, were absent. While strictly illustrative and limited by the small sample size, these preliminary observations suggest a reliance on conventional perceptions of scientific figures among these participants. These preliminary observations warrant further investigation using larger cohorts to evaluate whether tailored, inclusive pedagogical strategies can broaden perceptions of science.
Supporting data, adapters, predictions and code for the article *Low-Cost LoRA Fine-Tuning of Small Language Models for Multi-Step Arithmetic Reasoning* by Jake O'Grady, Asena Isik Gürhan, Chee Fong Ting and Effirul Ramlan (University of Galway). We generated 20,000 GSM8K-derived arithmetic problems with step-by-step s...
O'Grady, Jake, Gürhan, Asena Isik, Chee, Fong Ting et al.· Zenodo (CERN European Organi...· 465 citations
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