Artificial grammar learning (AGL) is an experimental paradigm that has been frequently adopted to test hypotheses of inductive language learning biases, which are assumed to be part of the unconscious, perhaps also innate, linguistic knowledge. However, previous AGL studies demonstrating some biased language learning for adult learners rarely supported their findings by measuring learners' awareness and took it for granted that target generalizations are acquired unconsciously with guidance of their implicit linguistic knowledge. Without awareness measures, there's always an alternative interpretation of adult learners' performance given the fact that adult learners frequently, if not always, rely on explicit learning, too. In this talk, my goal is to show how reaction time of grammaticality judgments and elicited productions in AGL studies could be used as an objective index of adult learners' awareness, which could help shed light on the nature of acquired linguistic knowledge and reach a more solid conclusion regarding hypothesized language learning biases.

Speaker
Professor Tsung-Yin CHEN (National Tsing Hua University)
Tsung-Ying Chen received his PhD in Linguistics in 2014 from the Department of Linguistics of the University of Alberta in Canada. He worked in Taiwan as a postdoc researcher at the Graduate Institute of Linguistics of National Chung Cheng University between 2015 and 2017 before joining the Department of Foreign Languages and Literature of National Tsing Hua University as a full-time faculty member in Fall 2017. Dr. Chen’s research interests cover theoretical and experimental phonology as well as language acquisition in general, and in more recent years, his works have concentrated on testing linguistic hypotheses experimentally with the artificial grammar learning paradigm.