Learning by Liking- a Mere Exposure Version of the AGL Paradigm
Independent thesis Advanced level (degree of Magister)Student thesis
The artificial grammar learning (AGL) paradigm has been intensively researched since the 60-s. In general, these investigations attempt to study the implicit acquisition of structural regularities. Among other things, it has been suggested that the AGL paradigm can serve as a model for the process of acquiring a natural language. Thus it can serve as a well-controlled laboratory task that might be used to understand certain aspects of the process of language acquisition. For example the AGL paradigm has been used in an attempt to isolate the acquisition of syntactic aspects of language. Several experimental studies show that the participants acquire knowledge of the underlying rule system since they are able to differentiate grammatical strings from non-grammatical ones. It has been argued that the traditionally conducted AGL paradigm with grammaticality instructions might make the task explicit, at least during the test phase. In order to imitate the language learning process as close as possible, to rule out the possibility of an explicit component during the testing phase (i.e., keeping the retrieval process implicit) and to rule out explicit rule conformity or rule following, we modified the classical AGL paradigm. In a behavioural study we combined the AGL paradigm with an altered mere exposure paradigm in an attempt to better model aspects of language acquisition. We were able to show that subjects, classifying under mere exposure instructions, categorize grammatical and non-grammatical strings just as well as those solving the classification task with the grammaticality instructions. This indicates that the mere exposure version might serve as a more appropriate model for language acquisition.
Place, publisher, year, edition, pages
Institutionen för datavetenskap , 2004.
Interdisciplinary studies, artificial grammar learning, AGL, mere exposure, implicit memory, language acquisition
Social Sciences Interdisciplinary
IdentifiersURN: urn:nbn:se:liu:diva-2075ISRN: LIU-KOGVET-D--04/09--SEOAI: oai:DiVA.org:liu-2075DiVA: diva2:19404