What: Towards a statistical learning theory of proficient reading
Where: BCBL Auditorium and zoom room # 1 (If you would like to attend to this meeting reserve at info@bcbl.eu)
Who: Professor Ram Frost, Department of Psychology, The Hebrew University, Israel.
When: Tuesday, Feb 28th at 02:00 PM
Over the course of the recent decades, Statistical Learning (SL)--the implicit learning from the statistical properties of sensory input across time and/or space, has become a key explanatory mechanism underlying the incidental learning of regularities across different domains of cognition. A statistical learning theory of proficient reading assumes that reading experience leads to a deep assimilation of the statistical structure of a writing system, enabling effective predictions on-the-fly, thus facilitating eye-movement behavior. From a cross-linguistic perspective, it highlights the different statistical regularities embedded in writing systems, specifying how these regularities can be learned and processed by a neurobiologically-constrained computational system. This new perspective reshuffles the cards in the taxonomy of writing systems and generates a large set of novel predictions regarding cross-linguistic differences in reading behavior. In this talk I will present the blue-prints of this approach as well as empirical evidence supporting it.