ABSTRACT
In this article, we present a study on computer-aided error analysis. For this, the main focus is the identification of the most frequent etiological errors and the tendency of use at different levels of the language in two sub-corpus CAELE and COELE-V. Each one constituted by 200 texts. The objective is to determine the influence of the L1 on errors caused by negative transfer in the written skill of ELE learners (CAELE) and participants of virtual communities (COELE-V), both of B1 competence levels. The results show that the most frequent negative transfer errors in both subcorpus refer to the definite article and the preposition “a”. In relation to the similarities and differences between the two learning environments, it was verified that in the omission of the defined article in both subcorpus, the errors and negative transfer tendencies of English as L1 are similar. However, the order in the frequencies between both subcorpus is differentiating. Regarding the omission of the preposition “a”, both subcorpus presented a greater frequency in the omission to introduce direct or indirect object of person. However, differences are observed between both subcorpus in the false selection of the preposition “a” instead of the prepositions “of”, “para” and “en”.
KEYWORDS:
computer-aided error analysis (CEA); computer learner corpora (CLC); negative transfer in ELE; prepositions in ELE; articles in ELE