FINE ReMorph · FINE (French, Italian, Norwegian, English) Reading through Morphology

There is still much room for improvement in reading intervention, testing and teaching in Europe. Morphology, in particular, has been neglected in reading acquisition theories, which have focused on narrow contexts including monomorphemic words, children in the first steps of reading acquisition, and the English language only. FINE ReMorph will determine whether morphological knowledge impacts reading development earlier in languages with richer morphology and whether different trajectories appear in languages with different orthographic and syllabic features.French, Italian, Norwegian, and English, four languages resulting in diverse combinations of morphological richness, orthographic depth, and syllabic complexity, will be compared. Language and reading will be tested in three different age ranges of school-aged children. Ocular movements will be tracked to determine the role of different morphological constituents in written-word recognition. I will coordinate my Associated partner and two Short-Visit Hosts remotely and through a 6-month secondment and two one-month short visits to ensure the smooth implementation of testing activities in every language under study.The project output will inform the scientific, clinical, and educational communities about the age of impact of morphology on reading in languages with different morphological, orthographic, and syllabic features. This will determine if, when, and how to introduce morphology instruction into scientific, clinical, and educational interventions in diverse languages. At my Host, I will acquire neuroscientific knowledge of neuroimaging techniques; on secondment, I will practice eye-tracking research; during my two short visits, I will improve my psychometric skills with the authors of the FINE ReMorph core test. The advanced technological/behavioral methods and transferrable skills acquired will increase my research profile competitivity and strengthen my interdisciplinary scientific network.