Lecture - Ram Frost: Visual statistical learning and writing systems: Learning to read a new orthography
Speaker: Prof Ram Frost, Hebrew University, Israel
Writing systems can be characterized by systematic co-occurrences of letter sequences, by correlations of in letter-to-sound mappings, and by correlations between form and semantic meaning through morphological structure.
Proficient readers implicitly develop sensitivities to these statistical properties. While learning to read in L2, they acquire a new lexical system, mainly by picking up and assimilating a new set of statistical regularities. However, like any cognitive ability, there are individual differences in the sensitivity to the correlations in the environment. What drives then the variance in statistical learning? Is this variance related to ease or difficulty of learning to read a new orthography? Drawing on information theory we entertain the theoretical hypothesis that rate of novel information (entropy) per time unit predicts perception of regularities in the visual modality for a given individual. The theoretical implications to learning to read in different writing systems will be discussed.
Speaker: Prof Ram Frost, Hebrew University, Israel, https://scholar.google.com/citations?user=rWjVoksAAAAJ
Bio : My research focuses on the cognitive processes involved in visual word recognition, investigating what is universal in the reading process across diverse languages, and what aspects of reading are unique to each language's orthographic and morphological system. My previous work focused on the orthographic depth hypothesis, and the strong phonological theory of reading. Presently, I am involved in a comprehensive research tracking neurobiological changes in L2 learning, and investigating statistical learning as an individual ability from a behavioural and neurobiological perspective. Most of my research is pursued in collaboration with Haskins Laboratories in New Haven, and with the Basque Center for Cognition, Brain and Language (BCBL).
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