Science1 publisher2 min readPublished
Sensors inside an ink pen track writing difficulty across 700 Italian schoolchildren
Politecnico di Milano and the University of Insubria put sensors in an ink pen and had more than 700 schoolchildren write two tasks from Italy's standard writing battery on paper, then checked what the signals could tell them.
The Scientist · Science desk

What happened
- More than 700 primary and lower secondary school children wrote two tasks from Italy's BVSCO-3 battery using the THInkPen, a sensorised ink pen built by Politecnico di Milano and the University of Insubria.
- The sensors yielded indicators for pressure on the paper, movement fluency, pen inclination and how often signals reached the device, all computed while the child wrote.
- Binary classification models separated the students the battery scored as having writing difficulties from the rest, and explainable-AI methods returned reasons for below-average performance.
- The work appears in PLOS Digital Health, first-authored by Simone Toffoli, and describes itself as a cross-sectional population-based study.
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Why it matters
- capability Process data becomes collectable in a classroom without moving the child onto a tablet screen, so the measurement happens where children already write and with the tool they already hold.
- constraint Without accuracy figures or a longitudinal arm, a school can use this to decide who should take the battery, and it cannot yet be used in place of a clinical judgement.
- decision Waiting lists at Child and Adolescent Neuropsychiatry services are what a school-level screen would relieve, and it moves the first call on referral to teachers.
- precedent The pen is patented and was aimed at neurodegenerative screening before children, so a classroom rollout is a licensing negotiation with two universities.
BVSCO-3 scores the finished page, and it is the most widely used test in Italy for assessing writing difficulties, dysgraphia and dysorthography [3]. The pen adds measurement of the act while it is happening, which the team frames as enriching the information clinical tests provide, as the latest approved guidelines on Specific Learning Disorders require [17]. Across the sample, the digital indicators and the clinical scores were significantly and consistently related [5].
The classifiers had to agree with the battery, because the battery supplied the labels. Children counted as having writing difficulties were identified on the basis of their BVSCO-3 results [6]. Agreement with an established instrument is the right first thing to measure, but because the labels came from the battery, the models cannot show the pen flagging a child the battery scores as typical.
The grade analysis is a different sort of check, and a more informative one. The indicators reproduced the well-established improvement in writing from one grade to the next without ever being told which grade a child was in [7]. The design is cross-sectional [8], so each grade is a separate group of children measured once, not one cohort followed up through school.
Two tasks each, more than 700 children: at least 1,400 instrumented writing samples on paper [15]. The phys.org account of the work does not report the classifiers' accuracy or any head-to-head test against a tablet-based tool [18]. The case for paper, then, is that the child performs the ordinary school task while the sensors log it: the pen lays down ink and is held like any pen, which the team calls a substantial difference from screening tools such as tablets [9].
Both groups put the use case in the same place, which is the referral decision a school makes before a clinic sees the child. "The use of THInkPen to analyze not only the final written product, but the entire writing process, could support the early identification of writing difficulties in schools, thus facilitating the timely and effective activation of clinical services," said Simona Ferrante, the professor at DEIB who coordinated the Politecnico di Milano team [12].
Cristiano Termine, professor of child neuropsychiatry at the University of Insubria, put the school's side of it: "It therefore becomes essential to have reliable observation and screening tools that can help schools better understand the nature of these difficulties and identify at an earlier stage those situations that genuinely require referral to Child and Adolescent Neuropsychiatry services" [14].
What to watch
- Whether a follow-up study tracks the same children over several years, which is the only design that can test whether pen indicators flag difficulty before the battery does.
- Whether the PLOS Digital Health paper itself reports sensitivity and specificity for the binary classifiers, and on what held-out sample.
- Whether any Italian school district runs the pen as a pre-referral screen and reports what happened to its referral volume.