ArticlePloS one2026
Can artificial intelligence read our handwriting? A comparison of humans and artificial intelligence in the future of assessment.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
4 authors.
Funding
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Abstract
The purpose of this study is to evaluate the legibility of fourth-grade elementary school students' handwriting and to examine the differences and relationships between two evaluators: a human researcher and artificial intelligence (ChatGPT). To this end, the study was conducted using the descriptive survey model, one of the quantitative research approaches. The study sample consisted of 67 fourth-grade students attending a public elementary school. The students' handwriting was evaluated using the Multidimensional Legibility Scale. Writing samples were collected from each student, including copying samples, dictated samples, and free writing samples. One class period was allocated for each writing task. The 201 handwriting samples obtained from the 67 students were evaluated by a researcher (the second author) and artificial intelligence (ChatGPT). According to the findings, no significant differences were detected between the artificial intelligence and the researcher in any writing type or subdimension, except for the slant subdimension of free writing. However, a high level of positive and significant correlation was identified between the two raters. Findings indicate that artificial intelligence can produce results comparable to those of expert raters when evaluating handwriting legibility. The fact that differences among raters are not statistically significant suggests that AI-based handwriting evaluations could serve as an objective and reliable alternative.
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