  This work examines the impact of cross-linguistic transfer on grammatical
errors in English as Second Language (ESL) texts. Using a computational
framework that formalizes the theory of Contrastive Analysis (CA), we
demonstrate that language specific error distributions in ESL writing can be
predicted from the typological properties of the native language and their
relation to the typology of English. Our typology driven model enables to
obtain accurate estimates of such distributions without access to any ESL data
for the target languages. Furthermore, we present a strategy for adjusting our
method to low-resource languages that lack typological documentation using a
bootstrapping approach which approximates native language typology from ESL
texts. Finally, we show that our framework is instrumental for linguistic
inquiry seeking to identify first language factors that contribute to a wide
range of difficulties in second language acquisition.
