Neuroeducation and Mathematics: The formation of new educational practices Eleni Lekati 1 and Spyridon Doukakis 2 1 Department of Informatics, Ionian University,7 Tsirigoti Square, 49100 Kerkyra, Greece, elenlekati@ionio.gr 2 Department of Informatics, Ionian University,7 Tsirigoti Square, 49100 Kerkyra, Greece, sdoukakis@ionio.gr Abstract. Recent research in educational neuroscience has established the corre- lation between the way the human brain works and the process of perceiving and learning mathematical concepts. In this paper, a research approach is proposed, based on the principles of educational neuroscience, and focuses on the way stu- dents deal with new knowledge in mathematics. Initially, using neuroscientific techniques and a multidimensional approach to new knowledge, data will be col- lected from students. By collecting neurophysiological measurements and ana- lyzing the data, an attempt will be made to formulate learning paths for a better understanding of fractional concepts, based on the needs of each student. Keywords: Mathematics, Neuroeducation, teaching proposals, digital bi- omarkers Introduction The field of educational neuroscience is based on the intersection between psychology, neurology, and pedagogy. Its goal is to search for methods that contribute to increasing the understanding of how humans learn, as well as to the improvement of teaching methods and environments. Despite the vast amount of research from the 1900s to the present day, comprehension difficulties in mathematics continue to concern children and adults [1]. Adopting views from experts and scholars in the fields of psychology, neuroscience, and pedagogy, neuroscientific techniques are utilized, and experimental approaches are attempted in order to investigate issues related to education and teach- ing. As a newly emerging interdisciplinary field, neuroscience advances research in ed- ucation with techniques, which can contribute to the transformation and development of a better learning environment and indicative teaching practices. Techniques such as magnetic resonance imaging (MRI), electroencephalography (EEG), and near-infrared spectroscopy, as well as technologies such as eye trackers, facial expression recogni- tion, and smart watches allow the collection of neurophysiological measurements, in real conditions. At the same time, they contribute to the collection of digital biomarkers and the decoding of memory mechanisms [2].