Corrective Feedback in First Language Acquisition Sarah Hiller Abstract: Children learn their first language in interaction with proficient users. This naturally exposes them to positive input, i.e. grammatically correct utterances in context. It is still unclear however, whether they also receive negative input. That is, responses informing them about the inadequacy of a grammatically erroeous utterance. In the present study we investigate parental reformulations, or corrective feedback, as a possible candidate for a conversational pattern conveying this information. Reformulations occur as a response to a wide variety of child errors. They indicate an error while simultaneously presenting its corrected form. We investigate whether these types of responses are indeed helpful for language acquisition. To this end, a large scale empirical analysis is employed. All relevant transcripts available from the part of CHILDES database in English language are used (MacWhinney, 2000a). Candidate child-adult utterance pairs in a subset of files are manually annotated for the presence of corrective feedback and for the corrected errors. These manually annotated exchanges serve as the training set for an automatic classifier aimed at distinguishing corrective feedback from non-corrective feedback instances. The predictive accuracy scores, however, show that the phenomenon is too diverse to be captured globally with our approach. Hence the investigated phenomenon is restrained to responses following a subject omission error in the child utterance. We develop automatic extraction methods for both child utterances containing this error and responses correcting it in a reformulation. The effect of corrective feedback on language learning is investigated by testing whether a higher rate of corrective feedback coincides with a greater decrease of the amount of error made at a later moment compared to at the starting age. A correlation analysis gives a first pointer in this direction. A subsequent linear regression analysis confirms that corrective feedback increases explanatory force of the model beyond what other features achieve, after a lag of at least 9 months between start and end age, with a peak after a difference in time of around 14 months.