  We present a method for classifying syntactic errors in learner language,
namely errors whose correction alters the morphosyntactic structure of a
sentence.
  The methodology builds on the established Universal Dependencies syntactic
representation scheme, and provides complementary information to other
error-classification systems.
  Unlike existing error classification methods, our method is applicable across
languages, which we showcase by producing a detailed picture of syntactic
errors in learner English and learner Russian. We further demonstrate the
utility of the methodology for analyzing the outputs of leading Grammatical
Error Correction (GEC) systems.
