DIDUNAS - Digital Identification & Support of Under-Achieving Students

DIDUNAS addresses an issue of concern in several countries of European Union, that is, students' under-achievement in mathematics. Students who do not achieve a satisfactory level of competence in mathematics are not equipped with the basic skills to cope in a numerate society. Engagement with mathematical topics develops the knowledge, skills and thinking capacity required by the majority of available jobs in the modern world. Further, mathematics is not only a core topic across all curricula but also mathematics competence influences students’ performance in other science subjects. By focusing on students' under-achievement in mathematics, DIDUNAS intends to enhance students’ learning opportunities and to reduce the percentage of students who leave school early without a qualification to get a job, which hinders the future prosperity and social cohesion of the EU as it is a major risk for unemployment and poverty.

Student difficulties in mathematics are seen to begin from early primary education and can – due to insufficient support – cascade into severe mathematical problems during learner biographies, which can even lead to functional innumeracy of students when leaving school. Therefore, it is significant to identify and characterize learning difficulties early in schooling, for teachers to be aware of initial difficulties and unfavorable preconditions, and to foster students adequately. Yet, identifying student difficulties at an early age is a challenging task for teachers – not least because young children tend to lack the ability to report meta-cognitively about their difficulties.

The overall purpose of DIDUNAS is to address students' under-achievement in mathematics early in schooling in Grade 1, in particular to contribute to the identification of underachievement and to the support of under-achieving students. For this purpose, DIDUNAS will (1) develop a digital tool to identify under-achieving students using eye-tracking technology (DIDUNAS-ET), which will circumvent the issue of students’ problems to verbally report on their mathematical difficulties. Students will work on digital basic mathematical tasks at a computer screen and eye tracking will be used together with Artificial Intelligence (AI) to identify students in need based on their eye movements. Based on this, DIDUNAS will (2) develop an App for the identification of under-achieving students (DIDUNAS-App): To make DIDUNAS available to a wide range of users, the App will work without eye tracking. For this purpose, dependencies will be used that will be established using machine learning and statistical approaches. Through such dependencies, mathematical difficulties can be studied even without eye tracking, e.g., based on patterns of response times or student error rates. To support identified under-achieving students DIDUNAS will also develop (3) support material for students (e.g., worksheets that respond to particular student difficulties etc.), material for teachers, and for students’ parents (DIDUNAS-Material). These materials will contribute to support students adequately, based on the identified profiles of difficulties.

Finally, DIDUNAS will make the insights and tools developed in this project timely available to young students, teachers and parents in the EU and communicate them to institutions and policy makers with the goal to substantially lower the number of under-achievers in mathematics.

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