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Using Vision + Language Models to Predict Item Difficulty

AI & ML·2 min read·via ArXivOriginal source →

Using Vision + Language Models to Predict Item Difficulty

arXiv:2603.04670v1 Announce Type: new Abstract: This project investigates the capabilities of large language models (LLMs) to determine the difficulty of data visualization literacy test items. We explore whether features derived from item text (question and answer options), the visualization image, or a combination of both can predict item difficulty (proportion of correct responses) for U.S. adults. We use GPT-4.1-nano to analyze items and generate predictions based on these distinct feature

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