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Artificial grammar learning (AGL) is a paradigm of study within cognitive psychology and linguistics. Its goal is to investigate the processes that underlie human language learning by testing subjects' ability to learn a made-up grammar in a laboratory setting. It was developed to evaluate the processes of human language learning but has also been utilized to study implicit learning in a more general sense. The area of interest is typically the subjects' ability to detect patterns and statistical regularities during a training phase and then use their new knowledge of those patterns in a testing phase. The testing phase can either use the symbols or sounds used in the training phase or transfer the patterns to another set of symbols or sounds as surface structure.
Many researchers propose that the rules of the artificial grammar are learned on an implicit level since the rules of the grammar are never explicitly presented to the participants. The paradigm has also recently been utilized for other areas of research such as language learning aptitude, structural priming [1] and to investigate which brain structures are involved in syntax acquisition and implicit learning.
Apart from humans, the paradigm has also been used to investigate pattern learning in other species, e.g. cottontop tamarins and starlings.
- ^ Peter, Michelle; Chang, Franklin; Pine, Julian M.; Blything, Ryan; Rowland, Caroline F. (May 2015). "When and how do children develop knowledge of verb argument structure? Evidence from verb bias effects in a structural priming task". Journal of Memory and Language. 81: 1–15. doi:10.1016/j.jml.2014.12.002. hdl:11858/00-001M-0000-002B-4649-3. ISSN 0749-596X.