Abstract:

In the first years of schooling, children build the basis of their knowledge and life skills; this development may be hindered by specific learning disorders (SLDs) that impact learning and, consequently, self-esteem, with effects that last throughout life. Their screening is difficult because of the complexity in distinguishing a learning delay from an actual disorder at an early stage. Still, it is essential to detect as soon as possible the presence of SLDs to effectively treat them. This is the rationale of the IndiPote(dn)S project. It addresses children from the last year of kindergarten to the second year of primary school; first, teachers observe children in school activities and report their abilities following grids of learning weaknesses precursors, designed by psychologists and child neuropsychiatrists (CNP); then, weak children are trained with a Vademecum of pen-and-paper or manual activities; finally, they are observed again. If the problems are not solved, further insight from a CNP is asked with priority. The process is performed by trained teachers, who however introduce subjectivity. In this context, technology can be beneficial to detecting signs not visible to the naked eye, structuring data collection, and standardizing the observation and training, both fundamental to gaining insights on children's learning trajectory in the screening path. This work aimed to co-design and develop a complete instrument to systematize data collection (Aim 1) and provide technological support to the screening and training (Aim 2). As for Aim 1, after brainstorming with stakeholders to understand the paper-based process, a web-app platform was devised. Specifically, the web-app choice was made for its capability of running on different devices (e.g. PCs and tablets), requiring only Internet access to work. The platform provides basic functions to input data on class composition; grade-specific questionnaires on children’s weaknesses and their training; and outcome of CNPs’ visits. The platform was proposed to schools in iterative testing that lasted from 2019 to 2023 and involved more than 130 schools and 15 thousand children on average per year. Yearly enhancements have been made thanks to users’ feedback and prompts. During this period, the focus was to assess adherence by measuring compliance, and the effectiveness of the screening by measuring the percentage of true positives in the reporting to CNP. Since its potential in the pilot phase, a final scalable version of the platform was produced to enable widespread adoption. The mean compliance obtained during iterative testing was 87.5%, whereas the true positives in CNP reporting resulted to be 75.8%. As for Aim 2, the final platform was also enriched with a module able to connect the observation and training activities with technologies like serious games or smart objects, paired with a reasoner that will be used to provide suggestions on training, describe the learning trajectory, and predict the outcome. The use case of a smart ink pen for screening will be presented. In conclusion, the platform is a promising tool for weakness identification, fundamental for the SLDs screening.

Keywords:

Specific learning disorders, Co-design, Digital technologies.