MOSAIC is a computational model of language learning that simulates developmental changes in the rate of OI errors across several different languages by learning compound finite constructions from the right edge of the utterance (Freudenthal, Pine, Aguado-Orea, & Gobet, 2007; Freudenthal, Pine, & Gobet, 2006a, 2009).  However, MOSAIC currently only simulates the pattern of OI errors in declaratives, and there are important differences in the cross-linguistic patterning of OI errors in declaratives and Wh- questions.  In the present study, we describe a new version of MOSAIC that learns from both the right and left edges of the utterance.  These results show that MOSAIC is able to provide an integrated account of the cross-linguistic patterning of OI errors in declaratives and Wh- questions, and provide further support for the view, instantiated in MOSAIC, that OI errors are compound-finite utterances with missing modals or auxiliaries.
MOSAIC