Early diagnosis and targeted support of mathematical skills form a key foundation for students’ successful participation in future educational and everyday contexts. Yet, identifying students’ mathematical skills and potential difficulties at an early age, and providing individualized support is a challenging task for teachers. To counter these challenges, the overall purpose of MADITA was to address the need to support students’ math skills early on in schooling. MADITA contributed to the development of digital tools for diagnosis and support, to support educational staff (through providing the digital tool) and to support students at the whole spectrum of abilities in an inclusive education system in their mathematical learning, from students with special educational needs to students at the upper spectrum. It also aimed to strengthen students’ motivation and enjoyment of mathematics through the use of technology, supporting long-term engagement with mathematics and related fields. MADITA developed a digital AI-based app – the MADITA app – that diagnoses and supports students’ math skills at the beginning of schooling.
MADITA addressed a key challenge in several countries in the European Union: low proficiency in basic mathematical skills. Students who do not reach satisfactory competence in mathematics are not equipped with the basic skills to cope in a numerate society. Research shows that many students enter school with low early mathematical skills, and without timely and adequate support, these deficits often persist throughout primary education (e.g., Viesel-Nordmeyer et al., 2019), cascade into severe mathematical problems, and may result in functional innumeracy (Geary, 2013). This highlights the need for early identification and targeted support of students’ math skills. However, teachers often lack the time, resources, and tools to diagnose students’ mathematical competencies and provide individualized support, particularly in inclusive settings (e.g., DeSimone & Parmar, 2006). These challenges intensified during the COVID-19 pandemic due to remote teaching (e.g., Jaekel et al., 2021), and increased teacher workload (e.g., Luy, 2022), while suitable tools to support early diagnosis and individualized math learning were largely missing (e.g., Barlowits et al., 2021; Jaekel et al., 2021; Luy, 2022).