Can artificial intelligence read our handwriting? A comparison of humans and artificial intelligence in the future of assessment

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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Publication Details

Journal
PLoS ONE
Published
2026-09-21
DOI
https://doi.org/10.1371/journal.pone.0358694
Primary Topic
Writing and Handwriting Education
Type
article
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Can artificial intelligence read our handwriting? A comparison of humans and artificial intelligence in the future of assessment

Halil İbrahim Öksüz, İsmail Yaşartürk, Mustafa Öztürk, Ramazan Deniz
PLoS ONE
Writing and Handwriting Education
article

Can artificial intelligence read our handwriting? A comparison of humans and artificial intelligence in the future of assessment

Halil İbrahim Öksüz, İsmail Yaşartürk, Mustafa Öztürk, Ramazan Deniz
article en

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.

PLoS ONEVol. 21(9)
Gazi University (TR)
Quality Education
Openalex Percentile: Top 2%
Writing and Handwriting Education
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Can artificial intelligence read our handwriting? A comparison of humans and artificial intelligence in the future of assessment — Halil İbrahim Öksüz, İsmail Yaşartürk, et al. · PLoS ONE (2026) | TGRS Research Map | TGRS